Author Archives: Braden Kelley

About Braden Kelley

Braden Kelley is a Human-Centered Experience, Innovation and Transformation consultant at HCL Technologies, a popular innovation speaker, and creator of the FutureHacking™ and Human-Centered Change™ methodologies. He is the author of Stoking Your Innovation Bonfire from John Wiley & Sons and Charting Change (Second Edition) from Palgrave Macmillan. Braden is a US Navy veteran and earned his MBA from top-rated London Business School. Follow him on Linkedin, Twitter, Facebook, or Instagram.

Why Going AI Only is Dumb

Leave a reply

I’m Sorry Dave, But I Can’t Do That

LAST UPDATED: November 3, 2025 at 4:50PM

Why Going AI Only is Dumb

by Braden Kelley

Last month I had the opportunity to attend Customer Contact Week (CCW) in Nashville, Tennessee and following up on my article The Voicebots Are Coming I’d like to dig into the idea that companies like Klarna explored of eliminating all humans from contact centers. After all, what could possibly go wrong?

When I first heard that Klarna was going to eliminate humans from their contact centers and go all in on artificial intelligence I thought to myself that they would likely live to regret it. Don’t get me wrong, artificial intelligence (AI) voicebots and chatbots can be incredibly useful, and that proves out in the real world according to conference speakers that almost half of Fanatics calls are automated on the phone without getting to an agent. A lot of people are experimenting with AI but AI is no longer experimental. What Klarna learned is that when you choose to use AI to reduce your number of human agents, then if the AI is down you don’t have the ability anymore to just call in off duty agents to serve your customers.

But, on the flip side we know that having AI customer service agents as part of your agent mix can have very positive impacts on the business. Small businesses like Brothers That Just Do Gutters have found that using AI agents increased their scheduling of estimate visits over humans alone. National Debt Relief automated their customer insufficient funds (CIF) calls and added an escalation path (AI then agent) that delivered a 20% revenue lift over their best agents. They found that when an agent gets a NO, there isn’t much of an escalation path left. And, the delicate reality is that some people feel self conscious calling a human to talk about debt problems, and there may be other sensitive issues where callers would actually feel more comfortable talking to a voicebot than a human. In addition, Fanatics is finding that AI agents are resolving some issues FASTER than human agents. Taken together these examples show that often a hybrid approach (humans plus AI) yields better results than humans only or AI only, so design your approach consciously.

Now let’s look at some important statistics from Customer Management Practice research:

2/3 of people prefer calling in and talking by phone, but most of that is 55+ and the preference percentage declines every ten years younger you go until 30% for 18-24
3/4 of executives say more people want self service now than three years ago
3/4 of people want to spend less time getting support – so they can get back to the fun stuff, or back to business

Taken together these statistics help make the case for increasing the use of AI agents in the contact center. If you happen to be looking to use AI agents in servicing your customers (or even if you already are) then it is important to think about how you can use them to remove friction from the system and to strategically allocate your humans towards things that only humans can do. And if you need to win support from someone to go big with AI voicebots then pick an important use case instead of one that nobody cares about OR even better, pick something that you couldn’t have done before (example: a ride sharing company had AI voicebots make 5 million calls to have drivers validate their tax information).

Finally, as I was listening to some of these sessions it reminded me of a time when I was tasked with finding a new approach for staffing peak season for one of the Blue Cross/Blue Shield companies in the United States. At that time AI voicebots weren’t a thing and so I was looking at how we could partner with a vendor to have a small number of their staff on hand throughout the year and then rely on them to staff and train seasonal staff using those seasoned vendor staff instead of taking the best employees off the phone to train temps.

Even now, all contact centers will still need a certain level of human staffing. But, AI voicebots, AI simulation training for agents, and other new AI powered tools represent a great opportunity for creating a better solution for peak staffing in a whole host of industries with very cyclical contact demand that is hard to staff for. One example of this from Customer Contact Week was a story about how Fanatics must 5x their number of agents during high seasons and in practice this often results in their worst agents (temps they hired only for the season) serving some of their best customers (high $$ value clients).

Conclusion

AI voicebots can be a great help during demand peaks and other AI powered tools (QA, simulations, coaching, etc.) can help accelerate and optimize both your on-boarding of full-time agents, but also of seasonal agents as well. But don’t pare back your human agent pool too far!

What has been your experience with balancing human and AI agents?

Image credits: Google Gemini

Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Measuring Human vs. AI Satisfaction

Leave a reply

Insights from Customer Contact Week (Nashville)

LAST UPDATED: October 30, 2025 at 1:00PM

Measuring Human vs. AI Satisfaction

by Braden Kelley

One of the sessions I had the opportunity to attend at Customer Contact Week in Nashville featured Brian Cantor (Customer Management Practice), Gene Kropfelder (Ally Financial) and Scott Rhinehart (Alorica). Two overarching themes of the session were that bringing technology and human elements together continues to be a challenge and that with every interaction you are either building or destroying trust. Gene highlighted that his outlook is that people don’t need another bank they need a better bank, and this mindset is something that he tries to help permeate throughout the organization. Two ways they try to be that better bank in customer experience terms is by first, creating transparency around the wait times in different support channels and second, by trying to make every interaction feel different/better than the interactions they have with Ally’s competitors.

Artificial Intelligence (AI) was obviously a focus of the session and the fact that personalization requires knowing the interactions a customer has had and what they’ve been exposed to, but AI (or humans) have to leverage that knowledge in a helpful and not a creepy way.

When it comes to AI, it’s not what AI can do, but what does it do better and what activities should it take on. Implementing AI in any situation should start with a shared understanding of what problem you’re trying to solve, clearly defined outcomes (work backwards from these, utilizing well-defined checkpoints), a well-communicated WIFM (What’s in it for me?), and a crawl/walk/run approach. Don’t go too big too fast.

We have learned along the way that artificial intelligence can be very useful for helping support agents lean in with the information they (and customers) need. AI as a tool to summarize research query responses versus a list of search results (links). AI can help us understand where agents are spending the time and serve as a knowledge base auditor (article inconsistencies, gaps, etc.).

One important question that came up is “How can we help with handle time?”:

CSAT and NPS are important but handle time is important not just for the company (cost) but also for the customer – so they can get back to their life

A more challenging question that all contact center managers must ask is “How do you measure AI satisfaction versus human satisfaction?”:

The reason this is a challenging questions is because most of the easily solvable questions will go the AI and the cases that often don’t have a good resolution will be the ones that go to humans
At the same time we need to consider the impact of automating certain types of calls (often the easy ones). Will this make the human’s job more stressful (no easy calls)? Will they need more breaks as a result?
In the quest for efficiency be careful not to have your humans provide a robotic experience (reading scripts, no authority or decision making capability or flexibility)

Our humanity (both customer and employee) will always be important. Both have to learn to trust AI outputs, impacting the rate and amount of adoption, especially if you don’t have a plan for how to build that trust over time. And, it is important to have human retain accountability – AI generated, human reviewed before submission (i.e. call summaries). Finally, it is important to understand that while we may view the digital native generations as preferring a technological solution, the reality is that even the younger generations will still reach out for a human touchpoint on important questions/issues. So we humans are safe – for now.

HALLOWEEN BONUS: Save 30% on the eBook, hardcover or softcover of my latest book Charting Change (now in its second edition) — FREE SHIPPING WORLDWIDE — using code HAL30 until midnight October 31, 2025

Image credits: Customer Management Practice

Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

The Indispensable Role of CX

Leave a reply

Insights from CCW’s 25-Year Journey

LAST UPDATED: October 28, 2025 at 12:00PM

by Braden Kelley

I recently had the privilege of sitting down with Mario Matulich, President of Customer Management Practice, at Customer Contact Week (CCW) in Nashville. As an organization celebrating its 25th anniversary, CCW has been a critical barometer for the entire customer experience and contact center industry. Our conversation wasn’t just a look back, but a powerful exploration of the strategic mandate facing CX leaders today, particularly how we manage innovation and human-centered change in an era dominated by AI and tightening budgets.

CCW at 25: The Hub for Benchmarking and Breakthroughs

Mario underscored that CCW is far more than just a conference; it’s a living repository of industry knowledge. Professionals attend for actionable takeaways, which primarily fall into three categories: benchmarking performance against industry leaders, learning about new trends (like Generative AI’s impact), and, critically, sourcing the right vendors and capabilities needed to execute their strategies. It’s where leaders come to calibrate their investment strategies and learn how to do more with their finite resources.

This pursuit of excellence is driven by a single, powerful market force: The Amazon Effect. As Mario put it, customers no longer judge your experience solely against your industry peers. They expect every single touchpoint with your company to be as seamless, intuitive, and effective as the best experience they’ve had anywhere. This constantly escalating bar for Customer Effort Score (CES) and Customer Satisfaction (CSAT) makes a complacent CX investment a near-fatal strategic mistake. The customer experience must always be top-tier, or you simply lose the right to compete.

The Strategic Disconnect: CX vs. The Contact Center

One of the most valuable parts of our discussion centered on the subtle, yet crucial, distinction between a Customer Experience (CX) professional and a Contact Center (CC) professional. While both are dedicated to the customer journey, their scope and focus often differ:

The CX Professional: Often owns the entire end-to-end customer journey, from marketing to product use to support. Their responsibilities and definition of success are deeply influenced by where CX sits organizationally — is it under Marketing, Operations, or the CEO?
The CC Professional: Focused on the operational efficiency, quality, and effectiveness of the voice and digital support channels. Their reality is one of doing a lot with a little, constantly asked to manage complex interactions while being, ironically, often looked to as a prime source of cuts in a downturn.

Social media, for instance, is still a relevant customer service channel, not just a marketing one. However, the operational reality is that many companies, looking for cost-effective solutions, outsource social media support to Business Process Outsourcing (BPO) providers, highlighting the ongoing tension between strategic experience design and operational efficiency.

“Being a CX leader in your industry is not a temporary investment you can cut and reinstate later. Those who cut, discover quickly that regaining customer trust and market position is exponentially harder than maintaining it.” — Braden Kelley

AI in the Contact Center: From Hypothesis to Hyper-Efficiency

The conversation inevitably turned to the single biggest factor transforming the industry today: Artificial Intelligence. Mario and I agreed that while the promise of AI is vast, the quickest, most immediate win for nearly every organization lies in agent assist.

This is where Generative AI tools empower the human agent in real-time — providing instant knowledge base look-ups, auto-summarizing previous interactions, and drafting responses. It’s a human-centric approach that immediately boosts productivity and confidence, improving Agent Experience (AX) and reducing training time.

However, implementing AI successfully isn’t a “flip-the-switch” deployment. The greatest danger is the wholesale adoption of complex technology without rigor. True AI success, Mario noted, must be implemented via the classic innovation loop: hypothesis, prototyping, and testing. AI isn’t a solution; it’s a tool that must be carefully tuned and validated against human-centered metrics before scaling.

The Mandate for Enduring Investment

A recurring theme was the strategic folly of viewing CX as a cost center. In a downturn, the contact center is often the first place management looks for budgetary reductions. Yet, the evidence is overwhelming: CX leadership is not a temporary investment. When you are leading in your industry in customer experience, that position must be maintained. Cut your investment at your peril, and you risk a long, painful road to recovery when the market turns. The CX team, despite being resource-constrained, often represents the last line of defense for the brand, embodying the human-centered change we preach.

As CCW moves into its next 25 years, the lesson is clear: customer expectations are only rising. The best leaders will leverage AI not just to cut costs, but to augment their people and apply the innovation principles of rigorous testing to truly master the new era of customer orchestration. The commitment to a great customer experience is the single, enduring investment that will future-proof your business.

Image credits: Customer Management Practice

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article.

Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

The Voicebots are Coming

2 Replies

Your Next Customer Support Agent May Not Be a Human

LAST UPDATED: October 27, 2025 at 1:00PM
The Voicebots are Coming

by Braden Kelley

Last week I had the opportunity to attend Customer Contact Week (CCW) in Nashville, Tennessee and learn that the familiar, frustrating tyranny of the touch-tone IVR (Interactive Voice Response) system is finally ending. For too long, the gateway to customer service has felt like a maze designed to prevent contact, not facilitate it. But thanks to the rapid evolution of Conversational AI — fueled by Generative Large Language Models (LLMs) — the entire voice interaction landscape is undergoing a revolutionary, and necessary, change. As a thought leader focused on human-centered change, innovation and experience design, I can tell you the future of the call center isn’t purely automated; it’s intelligently orchestrated.

The voicebot — the modern AI-powered voice agent — is moving past its days as a simple chatbot with a synthesized voice. Today’s AI agents use Natural Language Processing (NLP) to understand intent, context, and even tone, allowing them to handle complex, multi-step issues with startling accuracy. More importantly, they are ushering in the era of the bionic contact center, where the human agent is augmented, not replaced. This hybrid model — where AI handles the heavy lifting and humans provide empathy, complex reasoning, and necessary approvals — is the key to achieving both massive scale and superior Customer Experience (CX).

Overcoming the Voice Friction: The Tech Foundation

The shift to true voice AI required overcoming significant friction points that plagued older systems:

Barge-In and Latency: Modern voicebots offer near-instantaneous response times and can handle barge-in (when a customer interrupts the bot) naturally, mimicking human conversation flow.
Acoustic Noise: Advanced speech recognition models are highly resilient to background noise and varied accents, ensuring high accuracy even in noisy home or car environments.
Intent Nuance: LLMs provide the deep contextual understanding needed to identify customer intent, even when the customer uses vague or emotional language, turning frustrated calls into productive ones.

The Dual Pillars of Voice AI in CX

Conversational AI is transforming voice service through two primary deployment models, both of which reduce Customer Effort Score (CES) and boost Customer Satisfaction (CSAT):

1. Full Call Automation (The AI Front Line)

This model is deployed for high-volume, routine, yet critical interactions. The voicebot connects directly to the company’s backend systems (CRM, ERP, knowledge base) to pull personalized information and take action in real-time. Crucially, these new AI agents move beyond rigid scripts, using Generative AI to create dynamic, human-like dialogue that resolves the issue instantly. This 24/7 self-service capability slashes queue times and dramatically lowers the cost-to-serve.

2. Human-AI Collaboration (The Bionic Agent)

This is where the real human-centered innovation lies. The AI agent handles the bulk of the call — identifying the customer, verifying identity, diagnosing the problem, and gathering data. When the request hits a complexity threshold — such as requiring a policy override, handling an escalated complaint, or needing a final human authorization — the AI performs a contextual handoff. The human agent receives the call along with a complete, structured summary of the conversation, the customer’s intent, and often a recommended next step, turning a frustrating transfer into a seamless, empowered human interaction.

OR, even better can be the solution where a single human agent provides approvals or other guidance to multiple AI voice agents that continue owning their calls while waiting for the human to respond (possibly simultaneously helping the customer with additional queries) before continuing with the conversation through to resolution.

Customer Contact Week Nashville

“The most powerful application of voice AI isn’t automation, it’s augmentation. By freeing human agents from transactional drudgery, we elevate them to be empathic problem solvers, enhancing both their job satisfaction and the customer’s outcome.” — Braden Kelley

Measuring the Success of the Handoff

The quality of the transitions between AI and human is the true measure of success. Leaders must track metrics that assess the efficacy of the handoff itself:

Repeat Story Rate: The percentage of customers who have to repeat information to the human agent after an AI handoff. This must be near zero.
Agent Ramp-up Time (Post-Transfer): The time it takes for the human agent to absorb the AI-generated context and take meaningful action. Lower is better.
Post-Handoff CSAT: The customer satisfaction score specifically captured after a complex AI-to-human transfer, measuring the seamlessness of the experience.

The Agentic Future

The voicebots are indeed coming, and they are bringing with them the most significant shift in customer service since the telephone itself. The next evolution will see agentic AI — bots that can dynamically choose between multiple tools and knowledge sources to resolve novel problems without being strictly pre-scripted. The challenge for leaders is to ensure that as this technology scales, our focus remains firmly on the human experience, leveraging the best of AI’s speed and the best of human empathy to create a truly effortless and satisfying customer journey.

🤖 Companies to Watch in AI Voicebots

The voicebot space is rapidly evolving, driven by generative AI, and the recent Customer Contact Week (CCW) in Nashville highlighted several key players. Companies to watch in this generative AI voicebot and contact center space include market-leading platforms like NICE, Genesys, Zoom and Five9, all of whom are heavily integrating generative and agentic AI features—such as real-time coaching and automated post-call summaries — into their core Contact Center as a Service (CCaaS) offerings.

Beyond the traditional CCaaS providers, specialist AI firms like Replicant, Voice.AI and ASAPP (who had a significant presence at the event) continue to stand out by focusing on either full end-to-end voice automation for complex transactions or providing advanced Human-in-the-Loop AI features to augment live agents, particularly in regulated industries like financial services.

Additionally, major cloud vendors like Google Cloud and AWS (Amazon Connect) are increasingly aggressive, leveraging their foundational AI models to provide scalable, next-generation AI agents and contact center platforms, ensuring they remain transformative forces in customer experience (CX) automation.

Image credits: Customer Management Practice, Google Gemini

Content Authenticity Statement: The topic area, key elements to focus on, vendors to mention, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article.

Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

The Marketing Guide for Humanity’s Next Chapter

Leave a reply

How AI Changes Your Customers

Exclusive Interview with Mark Schaefer

Mark W Schaefer

LAST UPDATED: October 1, 2025 at 12:00PM

The rise of artificial intelligence isn’t just an upgrade to our technology; it’s a fundamental shift in what it means to be human and what it takes to lead a successful business. We’ve entered a new epoch defined by “synthetic humanity,” a term coined by Mark Schaefer to describe AI interactions that are indistinguishable from real human connection. This blurring of lines creates an enormous opportunity, which Mark Schaefer refers to as a “seam” — a moment of disruption wide open for innovators. But as algorithms become more skilled at simulating empathy and insight, what must leaders do to maintain authenticity and relevancy? In this exclusive conversation, Mark Shaefer breaks down why synthetic humanity is the most crucial concept for leaders to grasp today, how to use AI as a partner rather than a replacement, and the vital role of human creativity in a world of supercharged innovation.

The Internet, Smartphones, Social Media, and Now AI, Have All Shifted Customer Expectations

Mark Schaefer is a globally-acclaimed author, keynote speaker, and marketing consultant. He is a faculty member of Rutgers University and one of the top business bloggers and podcasters in the world. How AI Changes Your Customers: The Marketing Guide to Humanity’s Next Chapter is his twelfth book, exploring what companies should consider when it comes to artificial intelligence (AI) and their customers.

Below is the text of my interview with Mark and a preview of the kinds of insights you’ll find in How AI Changes Your Customers presented in a Q&A format:

1. I came across the term ‘synthetic humanity’ fairly early on in the book. Why is this concept so important, and what are the most important aspects for leaders to consider?

“Synthetic humanity” is my term for describing the emerging wave of AI interactions that appear, sound, and even feel human — yet are not human at all. This is not science fiction. Already, chatbots can hold natural conversations, generate art, or simulate empathy in ways that blur the line between authentic and artificial.

For leaders, this matters because customers don’t care whether an experience is powered by code or carbon; they care about how it feels. If synthetic humanity can deliver faster, easier, and more personalized service, people will embrace it. The more machines convincingly mimic us, the more vital it becomes to emphasize distinctly human qualities like compassion, vulnerability, creativity, and trust.

Leaders must navigate two urgent questions: Where do we lean into automation for efficiency? And where do we intentionally preserve human touch for meaning? Synthetic humanity can scale interactions, but it cannot scale authenticity. The most successful brands will be those that strike this balance — leveraging AI’s strengths while showcasing the irreplaceable heartbeat of humanity.

2. We discuss disruption quite a bit here on this blog. Can you share a bit more with our innovators about ‘seams’ and the opportunities they create with AI or otherwise?

Throughout history, disruptions to the status quo, such as pandemics, wars, or economic recessions, can either sink a business or elevate it to new heights. Every disruption creates a seam — a moment where the fabric of culture, business, or belief rips just wide enough for an innovator to crawl through and create something new.

We might be living in the ultimate seam.

Google CEO Sundar Pinchai calls AI the most significant innovation in human history — more important than fire, medicine, or the internet. The power of AI seems absolute and threatening. For many, it’s terrifying.

Through my new book, I’m trying to get people to view disruption through a different lens: not fear, but immense possibility.

3. Given that AI has access to all of our accumulated wisdom, does it actually create unique insights and ideas, or will innovation always be left to the humans?

AI is extraordinary at remixing existing content. It can scan millions of data points, connect patterns we might miss, and surface possibilities at lightning speed. That feels like insight, and sometimes it is. However, there is a crucial distinction: AI doesn’t truly care. It lacks context, longing, and lived experience.

Innovation often begins with a problem that aches to be solved or a vision that comes from deep within human culture. AI can suggest ten thousand options, but only a person can say, “This one matters because it touches our values, our customers, our future.”

So the real power is in the partnership. AI accelerates discovery, clears away routine work, and even provokes us with new connections. Humans bring the spark of meaning, the intuition, and the courage to act on something that has never been tried before. Innovation is not being replaced. It is being supercharged. In my earlier book “Audacious: How Humans Win in an AI Marketing World,” I note that the bots are here, but we still own crazy!

This is a time for humans to transcend “competent.” Bots can be competent and ignorable.

4. Do you have any tips for us mere mortals on how to productively use AI without developing creative and intellectual atrophy?

Yes, and it starts with how you frame the role of AI in your life. If you treat it as a replacement, you risk letting your creative muscles go slack. If you treat it as a partner, you can actually get stronger.

Here are a few practical approaches. First, use AI to stretch your perspective, not to finish your work for you. Ask it to give you ten angles on a problem, then choose one and make it your own. Second, set boundaries. Write your first draft by hand or sketch ideas before you ever touch a prompt. Let AI react to your thinking, not define it. Third, use the tool to challenge yourself. Feed it your work and ask, “What am I missing? Where are my blind spots?”

Most importantly, keep doing hard things. Struggle is where growth happens. AI can smooth the path, but sometimes you need the climb. Treat the technology as a coach, not a crutch, and you will come out sharper, faster, and even more creative on the other side.

5. I’ve heard a little bit about AI literacy. What are some of the critical aspects that we should all be aware of or try to learn more about?

There are a few critical aspects everyone should know. First, bias. AI models are trained on human data, which means they inherit our blind spots and prejudices. If you don’t recognize this, you may mistake bias for truth. Second, limits. AI is confident even when it is wrong. Knowing how to fact-check and verify is essential. Third, prompting. The quality of your input shapes the quality of the output, so learning how to ask better questions is a new core skill.

Finally, ethics. Just because AI can do something does not mean it should. We all need to be asking: How does this affect privacy, autonomy, and trust?

AI literacy isn’t about becoming a coder. It is about being a thoughtful user, a skeptic when needed, and a leader who understands both the promise and the peril of these tools.

6. What do companies and sole proprietors worried about falling below the fold of the new AI-powered search results need to change online to stay relevant and successful?

I have many practical ideas about this in the book. In short, the old game of chasing clicks and keywords is fading. AI-powered search doesn’t just list links, it delivers answers. That means the winners will be those whose content and presence are woven deeply enough into the digital fabric that the algorithms can’t ignore them.

This requires a shift in focus. Instead of creating content that only ranks, create content that is referenced, cited, and trusted across the web. Build authority by being the source others turn to. Make your ideas so distinct and valuable that they become part of the training data itself. We are entering a golden age for PR!

It also means doubling down on brand signals that AI can’t manufacture. Human stories, original research, strong communities, and unique perspectives will travel farther than generic blog posts. And remember, AI models reward freshness and relevance, so showing up consistently matters.

The book also covers what I call “overrides.” If you create a meaningful, loyal relationship with customers and word of mouth recommendations, that will override the AI recommendations. We consider AI recommendations. We ACT on human recommendations.

7. ‘Weaponizing kindness’ was a terrifying headline I stumbled across in your book. What do organizations need to consider when using AI to interact with customers and what traps are out in front of them?

That phrase is unsettling for a reason. AI can mimic empathy so well that it risks crossing into manipulation. Imagine a chatbot that remembers your child’s name, mirrors your mood, or expresses concern in just the right tone. Done responsibly, that feels like service. Done carelessly, it feels like exploitation.

Organizations need to recognize that kindness delivered at scale is powerful, but if it is hollow or purely transactional, customers will sense it. The first trap is confusing simulation with sincerity. Just because an AI can sound caring does not mean it actually cares. The second trap is overreach. Using personal data to create hyper-tailored interactions can quickly slip from helpful to creepy.

The safeguard is transparency and choice. Be clear about when a customer is interacting with AI. Use technology to enhance human care, not replace it. Always provide people with a way to connect with a real person.

Kindness is a sacred trust in business. Weaponize it, and you erode the very loyalty and love you are trying to build. Use it authentically, and you create relationships no machine can ever replicate.

8. What changing customer expectations (thanks to AI) might companies easily overlook and pay a heavy price for?

One of the biggest shifts is speed. Customers already expect instant answers, but AI raises the bar even higher. If your competitor offers a seamless, AI-powered interaction that solves a problem in seconds, your slower, clunkier process will feel intolerable.

Another overlooked expectation is personalization. People are starting to experience products, services, and recommendations that feel almost eerily tailored to them. That sets a new standard. Companies still delivering one-size-fits-all communication will look outdated. Don’t confuse “personalization” with “personal.”

Perhaps the most subtle change is trust. As customers realize machines can fake warmth and empathy, they will value genuine human touch even more. If every interaction feels synthetic, you risk losing trust, especially if you’re not transparent about it.

The price of ignoring these shifts is steep: irrelevance. Customers rarely complain about unmet expectations anymore; they simply leave. The opportunity is to stay alert, listen closely, and respond quickly as AI reshapes what “good enough” looks like. The companies that thrive will be those that not only keep pace with AI, but also double down on the irreplaceable humanity customers still crave.

9. What unintended consequences of AI do you think companies might face and may not be preparing for? (overcoming AI slander and falsehoods might be one – agree or disagree? Others?)

I agree. In fact, I predict in the book that we cannot foresee AI’s biggest impact yet, as it will likely be an unintended consequence of the technology’s use in an unexpected way.

Where could that occur? Maybe reputational risk at scale. AI systems will generate falsehoods with the same confidence they generate facts, and those errors can stick. A single hallucination about your company, repeated enough times, becomes “truth” in the digital bloodstream. Most companies are not prepared for the speed and reach of misinformation of this kind.

Another consequence is customer dependency. If people hand over more of their decisions to AI, they may lose patience for complexity or nuance in your offerings. That can push companies toward oversimplification, even when a richer human experience would build deeper loyalty.

There is also the cultural risk. Employees might over-rely on AI, quietly eroding skills, judgment, and creativity. A workforce that outsources too much thinking can become brittle in ways that only show up during a crisis.

The real challenge is that these consequences don’t announce themselves. They creep in. Which means leaders must actively audit how AI is being used, question where it might distort reality or weaken capability, and set up safeguards now. The companies that prepare will navigate disruption. The ones that ignore it will be blindsided.

10. Can companies make TOO MUCH use of AI? If so, what would the impacts look like?

Yes, and we will start seeing this more often. It is a pattern that has repeated through history — over-indexing on tech and then bringing the people back in!

When companies lean too heavily on AI, they risk draining the very humanity that makes them memorable. On the surface, it might seem like efficiency: faster service, lower costs, and greater scale. But underneath, the impacts can be corrosive. You might be messing with your brand!

Customers may feel manipulated or devalued if a machine drives every interaction. Even perfect personalization can feel hollow if it lacks genuine care. Second, trust erodes when people sense that a brand hides behind automation rather than showing up with real human accountability. Third, within the company, over-reliance on AI can weaken employee judgment and creativity, resulting in a workforce that follows prompts rather than breaking new ground.

The real danger is commoditization. If every company automates everything, then no company stands out. The winners will be those who know when to say, “This moment deserves a person.” AI should be an amplifier, not a replacement. Too much of it and you don’t just lose connection, you lose your soul.

Conclusion

Thank you for the great conversation Mark!

I hope everyone has enjoyed this peek into the mind of the man behind the inspiring new title How AI Changes Your Customers: The Marketing Guide to Humanity’s Next Chapter!

Image credits: BusinessesGrow.com (Mark W Schaefer)

Content Authenticity Statement: If it wasn’t clear above, the short section in italics was written by Google’s Gemini with edits from Braden Kelley, and the rest of this article is from the minds of Mark Schaefer and Braden Kelley.

Sign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

You Just Got Starbucked

1 Reply

Layoffs, Store Closures & What It Means for Customer Service

LAST UPDATED: September 25, 2025 at 10:58PM
You Just Got Starbucked - Layoffs, Store Closures & What It Means for Customer Service

Exclusive Interview with Mario Matulich

In a world where corporate decisions often prioritize efficiency, the human element can be the first to suffer. The recent layoffs and restructuring at Starbucks, a brand synonymous with a unique, human-centered “third place” experience, have sent a tremor through the industry. In a wide-ranging interview, we will unpack the strategic and operational implications of these changes. Together, we will explore the difficult balance between trimming corporate fat and maintaining a brand built on emotional connection, diving into how these decisions could affect everything from in-store morale to the long-term loyalty of its customers. Central to the conversation is the following strategic question:

How can a company that has undergone significant corporate restructuring and layoffs maintain and restore a premium, human-centered customer experience?

Today we will explore this question, along with its various aspects with our special guest Mario Matulich, a practice lead at the Customer Management Practice with a diverse commercial understanding in a variety of industry verticals across the customer management sector. He is well versed in market research, product development, sales, marketing, and operations in addition to cross functional management and leadership development.

Without further ado, here is the Q&A I had with Mario on a range of topics regarding the recent Starbucks’ store closures and layoffs and their implications:

The Strategic Context of the Layoffs

Q: Starbucks’ leadership framed the recent restructuring as a necessary step for efficiency and a return to their core mission. From your perspective in customer management, how do these internal changes directly affect the external customer experience in the short and long term?
A: In the short term, layoffs, especially in corporate roles, can create gaps in innovation, brand narrative, and strategic support for store-level teams. Employees on the front lines may feel increased pressure, which can impact morale and the human connection customers expect. In the long term, if these gaps aren’t addressed, the result can be a more transactional experience that erodes both loyalty and trust.

Q: In many companies, layoffs are a last resort. Do you believe this restructuring reflects a failure of previous strategies, or is it a forward-thinking move to adapt to a changing market? What specific market trends do you think are driving these decisions?
A: I don’t view this restructuring as purely a failure of previous strategies, but rather as an attempt to adapt to a changing market. That said, Starbucks’ bigger challenge is restoring its customer experience. Trends such as rising demand for personalized, convenient, and high-value experiences, along with increased competition in the premium coffee market, make it clear that customers are evaluating Starbucks not just on price, but on the overall experience delivered.

Q: The layoffs primarily targeted corporate roles in marketing, technology, and creative. How does the loss of talent in these specific areas impact the company’s ability to innovate and maintain its brand narrative?
A: These areas are critical for innovation, storytelling, and digital experiences that connect customers to the brand. Losing talent here makes it more challenging to maintain a consistent, differentiated experience and risks further disengagement from customers.

Impact on the Human-Centered Experience

Q: Starbucks has long prided itself on the “third place” concept. How does restructuring and potential employee demoralization affect the in-store experience and the emotional connection customers have with the brand?
A: The “third place” experience relies on motivated and supported employees. Restructuring can disrupt this, as uncertainty and low morale may trickle down to in-store interactions. Customers may perceive a decline in warmth, attentiveness, and consistency, which can undermine the emotional connection.

Q: With fewer people in corporate roles, who now owns the responsibility for a seamless customer journey? Does this push more responsibility onto store-level partners, and if so, are they equipped to handle it?
A: While partners remain at the front line, the burden shouldn’t fall solely on them. Leadership must provide tools, guidance, and support to ensure a seamless experience, even as corporate teams shrink.

Q: Customer management is about building long-term loyalty. Do you believe this restructuring risks eroding the trust and loyalty of both employees and customers, and what would your practice recommend to mitigate that risk?
A: Yes, there’s definitely a risk. The key is to go back to the basics and make the experience personal, easy, and fast. Nail those, and customers’ trust and loyalty will .,¬./come back, and the layoffs won’t linger in their minds.

Measuring and Recovering from the Impact

Q: How would you advise Starbucks to measure the real-time impact of these changes on customer satisfaction? Beyond traditional metrics like NPS, what holistic experience measures should they be tracking?
A: Starbucks should look beyond NPS to measure speed of service, personalization, emotional connection, and overall experience consistency. These metrics provide a more comprehensive view of the customer journey and help identify gaps that layoffs may create.

Q: Layoffs can create a perception of instability. What is the most effective way for a company to communicate its recovery plan and rebuild confidence with its customer base after such a significant change?
A: Clear communication focused on restoring the core pillars of customer experience, personalization, ease, and speed, is key. Customers respond when they see tangible improvements in the experience they receive every day.

Q: In your experience, what is the typical timeline for a company to recover from the brand and cultural damage that can follow widespread layoffs? What are the critical milestones they should be focused on achieving?
A: Recovery timelines vary, but visible improvements in customer experience can begin within months if executed strategically. Critical milestones include reestablishing operational consistency, restoring employee morale, and relaunching key brand initiatives that reinforce the premium experience promise.

Future-Proofing for Long-Term Growth

Q: Looking ahead, how can Starbucks utilize this moment of disruption to adopt a more resilient and human-centered organizational model? What key lesson should other companies learn from their experience to avoid similar pitfalls?
A: Starbucks has a chance here to get back to what really made it successful: combining innovative, tech-forward solutions with a human touch, every time. The bigger lesson for any company is clear. Growth and cost-cutting shouldn’t come at the expense of the customer experience. People are willing to pay a premium, but only if the experience feels worth it.

Q: What message does it send that the popular Starbucks Roastery location in Capitol Hill in Seattle is being closed as part of this layoff and restructuring initiative? Why do you think they chose to do it?
A: Closing the Roastery signals a prioritization of efficiency over experiential destinations. While it may make financial sense in the short term, it also serves as a cautionary reminder that iconic, high-touch experiences are critical to maintaining brand differentiation and customer loyalty.

Conclusion

Thank you for the great conversation Mario!

Ultimately, the Starbucks case study is a powerful lesson for every organization. As Matulich’s insights make clear, the pursuit of efficiency and growth cannot come at the expense of the human experience that defines your brand. The true measure of a company’s resilience is not in its stock price, but in the trust it has built with its employees and customers. A single-minded focus on traditional metrics is insufficient; a holistic approach that values emotional connection and employee morale is the only path to sustainable growth. The greatest challenge for Starbucks now is to move beyond reacting to a difficult market and begin proactively shaping its future—not just through cost-cutting, but by recommitting to the core narrative that made it a cultural institution in the first place. The future of any business is not found in a spreadsheet; it’s built on a foundation of human connection, one interaction at a time.

Image credits: Pexels, Mario Matulich

Sign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

The Crisis Innovation Trap

Leave a reply

Why Proactive Innovation Wins

LAST UPDATED: September 3, 2025 at 12:00PM
The Crisis Innovation Trap

by Braden Kelley and Art Inteligencia

In the narrative of business, we often romanticize the idea of “crisis innovation.” The sudden, high-stakes moment when a company, backed against a wall, unleashes a burst of creativity to survive. The pandemic, for instance, forced countless businesses to pivot their models overnight. While this showcases incredible human resilience, it also reveals a dangerous and costly trap: the belief that innovation is something you turn on only when there’s an emergency. As a human-centered change and innovation thought leader, I’ve seen firsthand that relying on crisis as a catalyst is a recipe for short-term fixes and long-term decline. True, sustainable innovation is not a reaction; it’s a proactive, continuous discipline.

The problem with waiting for a crisis is that by the time it hits, you’re operating from a position of weakness. You’re making decisions under immense pressure, with limited resources, and with a narrow focus on survival. This reactive approach rarely leads to truly transformative breakthroughs. Instead, it produces incremental changes and tactical adaptations—often at a steep price in terms of burnout, strategic coherence, and missed opportunities. The most successful organizations don’t innovate to escape a crisis; they innovate continuously to prevent one from ever happening.

The Cost of Crisis-Driven Innovation

Relying on crisis as your innovation driver comes with significant hidden costs:

Reactive vs. Strategic: Crisis innovation is inherently reactive. You’re fixing a symptom, not addressing the root cause. This prevents you from engaging in the deep, strategic thinking necessary for true market disruption.
Loss of Foresight: When you’re in a crisis, all attention is on the immediate threat. This short-term focus blinds you to emerging trends, shifting customer needs, and new market opportunities that could have been identified and acted upon proactively.
Burnout and Exhaustion: Innovation requires creative energy. Forcing your teams into a constant state of emergency to innovate leads to rapid burnout, high turnover, and a culture of fear, not creativity.
Suboptimal Outcomes: The solutions developed in a crisis are often rushed, inadequately tested, and sub-optimized. They are designed to solve an immediate problem, not to create a lasting competitive advantage.

“Crisis innovation is a sprint for survival. Proactive innovation is a marathon for market leadership. You can’t win a marathon by only practicing sprints when the gun goes off.”

Building a Culture of Proactive, Human-Centered Innovation

The alternative to the crisis innovation trap is to embed innovation into your organization’s DNA. This means creating a culture where curiosity, experimentation, and a deep understanding of human needs are constant, not sporadic. It’s about empowering your people to solve problems and create value every single day.

Embrace Psychological Safety: Create an environment where employees feel safe to share half-formed ideas, question assumptions, and even fail. This is the single most important ingredient for continuous innovation.
Allocate Dedicated Resources: Don’t expect innovation to happen in people’s spare time. Set aside dedicated time, budget, and talent for exploratory projects and initiatives that don’t have an immediate ROI.
Focus on Human-Centered Design: Continuously engage with your customers and employees to understand their frustrations and aspirations. True innovation comes from solving real human problems, not just from internal brainstorming.
Reward Curiosity, Not Just Results: Celebrate learning, even from failures. Recognize teams for their efforts in exploring new ideas and for the insights they gain, not just for the products they successfully launch.

Case Study 1: Blockbuster vs. Netflix – The Foresight Gap

The Challenge:

In the late 1990s, Blockbuster was the undisputed king of home video rentals. It had a massive physical footprint, brand recognition, and a highly profitable business model based on late fees. The crisis of digital disruption and streaming was not a sudden event; it was a slow-moving signal on the horizon.

The Reactive Approach (Blockbuster):

Blockbuster’s management was aware of the shift to digital, but they largely viewed it as a distant threat. They were so profitable from their existing model that they had no incentive to proactively innovate. When Netflix began gaining traction with its subscription-based, DVD-by-mail service, Blockbuster’s response was a reactive, half-hearted attempt to mimic it. They launched an online service but failed to integrate it with their core business, and their culture remained focused on the physical store model. They only truly panicked and began a desperate, large-scale innovation effort when it was already too late and the market had irreversibly shifted to streaming.

The Result:

Blockbuster’s crisis-driven innovation was a spectacular failure. By the time they were forced to act, they lacked the necessary strategic coherence, internal alignment, and cultural agility to compete. They didn’t innovate to get ahead; they innovated to survive, and they failed. They went from market leader to bankruptcy, a powerful lesson in the dangers of waiting for a crisis to force your hand.

Case Study 2: Lego’s Near-Death and Subsequent Reinvention

The Challenge:

In the early 2000s, Lego was on the brink of bankruptcy. The brand, once a global icon, had become a sprawling, unfocused company that was losing relevance with children increasingly drawn to video games and digital entertainment. The company’s crisis was not a sudden external shock, but a slow, painful internal decline caused by a lack of proactive innovation and a departure from its core values. They had innovated, but in a scattered, unfocused way that diluted the brand.

The Proactive Turnaround (Lego):

Lego’s new leadership realized that a reactive, last-ditch effort wouldn’t save them. They saw the crisis as a wake-up call to fundamentally reinvent how they innovate. Their strategy was not just to survive but to thrive by returning to a proactive, human-centered approach. They went back to their core product, the simple plastic brick, and focused on deeply understanding what their customers—both children and adult fans—wanted. They launched several initiatives:

Re-focus on the Core: They trimmed down their product lines and doubled down on what made Lego special—creativity and building.
Embracing the Community: They proactively engaged with their most passionate fans, the “AFOLs” (Adult Fans of Lego), and co-created new products like the highly successful Lego Architecture and Ideas series. This wasn’t a reaction to a trend; it was a strategic partnership.
Thoughtful Digital Integration: Instead of panicking and launching a thousand digital products, they carefully integrated their physical and digital worlds with games like Lego Star Wars and movies like The Lego Movie. These weren’t rushed reactions; they were part of a long-term, strategic vision.

The Result:

Lego’s transformation from a company on the brink to a global powerhouse is a powerful example of the superiority of proactive innovation. By not just reacting to their crisis but using it as a catalyst to build a continuous, human-centered innovation engine, they not only survived but flourished. They turned a painful crisis into a foundation for a new era of growth, proving that the best time to innovate is always, not just when you have no other choice.

Eight I's of Infinite Innovation

The Eight I’s of Infinite Innovation

Braden Kelley’s Eight I’s of Infinite Innovation provides a comprehensive framework for organizations seeking to embed continuous innovation into their DNA. The model starts with Ideation, the spark of new concepts, which must be followed by Inspiration—connecting those ideas to a compelling, human-centered vision. This vision is refined through Investigation, a process of deeply understanding customer needs and market dynamics, leading to the Iteration of prototypes and solutions based on real-world feedback. The framework then moves from development to delivery with Implementation, the critical step of bringing a viable product to market. This is not the end, however; it’s a feedback loop that requires Invention of new business models, a constant process of Improvement based on outcomes, and finally, the cultivation of an Innovation culture where the cycle can repeat infinitely. Each ‘I’ builds upon the last, creating a holistic and sustainable engine for growth.

Conclusion: The Time to Innovate is Now

The notion of “crisis innovation” is seductive because it offers a heroic narrative. But behind every such story is a cautionary tale of a company that let a problem fester for far too long. The most enduring, profitable, and relevant organizations don’t wait for a burning platform to jump; they are constantly building new platforms. They have embedded a culture of continuous, proactive innovation driven by a deep understanding of human needs. They innovate when times are good so they are prepared when times are tough.

The time to innovate is not when your stock price plummets or your competitor launches a new product. The time to innovate is now, and always. By making innovation a fundamental part of your business, you ensure your organization’s longevity and its ability to not just survive the future, but to shape it.

Image credit: Pixabay

Content Authenticity Statement: The topic area and the key elements to focus on were decisions made by Braden Kelley, with help from Google Gemini to shape the article and create the illustrative case studies.

Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Why Context Engineering is the Next Frontier in AI

Leave a reply

Why Context Engineering is the Next Frontier in AI

by Braden Kelley and Art Inteligencia

Observing the rapid evolution of artificial intelligence, one thing has become abundantly clear: while raw processing power and sophisticated algorithms are crucial, the true key to unlocking AI’s transformative potential lies in its ability to understand and leverage context. We’ve seen remarkable advancements in generative AI and machine learning, but these technologies often stumble when faced with the nuances of real-world situations. This is why I believe context engineering – the discipline of explicitly designing and managing the contextual information available to AI systems – is not just an optimization, but the next fundamental frontier in AI innovation.

Think about human intelligence. Our ability to understand language, make decisions, and solve problems is deeply rooted in our understanding of context. A single word can have multiple meanings depending on the sentence it’s used in. A request can be interpreted differently based on the relationship between the people involved or the situation at hand. For AI to truly augment human capabilities and integrate seamlessly into our lives, it needs a similar level of contextual awareness. Current AI models often operate on relatively narrow inputs, lacking the broader understanding of user intent, environmental factors, and historical interactions that humans take for granted. Context engineering aims to bridge this gap, moving AI from being a powerful but often brittle tool to a truly intelligent and adaptable partner.

In the realm of artificial intelligence, context engineering is the strategic and human-centered practice of providing an AI system with the relevant background information it needs to understand a query or situation accurately. It goes beyond simple prompt design by actively building and managing the comprehensive context that surrounds an interaction. This includes integrating historical data, user profiles, real-time environmental factors, and external knowledge sources, allowing the AI to move from a narrow, transactional understanding to a more holistic, human-like awareness. By engineering this context, we enable AI to produce more accurate, personalized, and genuinely useful responses, bridging the gap between a machine’s logic and the nuanced complexity of human communication and problem-solving.

The field of context engineering encompasses a range of techniques and strategies focused on providing AI systems with relevant and actionable context. This includes:

Prompt Engineering: Crafting detailed and context-rich prompts that guide AI models towards desired outputs.
Memory Management: Implementing mechanisms for AI to remember past interactions and use that history to inform current responses.
External Knowledge Integration: Connecting AI systems to external databases, APIs, and real-time data streams to provide up-to-date and relevant information.
User Profiling and Personalization: Leveraging data about individual users to tailor AI responses to their specific needs and preferences.
Situational Awareness: Incorporating real-world contextual cues, such as location, time of day, and user activity, to make AI more responsive to the current situation.

A Human-Centered Blueprint for Implementation

Implementing context engineering is not a one-time technical fix; it is a continuous, human-centered practice that must be embedded into your innovation lifecycle. To move beyond a static, one-size-fits-all model and create truly intelligent, context-aware AI, consider this blueprint for action:

Step 1: Start with the Human Context. Before you even think about data streams or algorithms, you must first deeply understand the human being you are serving. Conduct ethnographic research, user interviews, and journey mapping to identify what context is truly relevant to your users. What are their goals? What unspoken needs do they have? What external factors influence their decisions? The most valuable context often isn’t in a database—it’s in the real-world experiences and emotional states of your users.
Step 2: Map the Contextual Landscape. Once you understand the human context, you can begin to identify and integrate the necessary data. This involves creating a “contextual map” that connects the human need to the available data sources. For a customer service AI, this map would link a customer’s inquiry to their purchase history, recent support tickets, and even their browsing behavior on your website. For a medical AI, the map would link a patient’s symptoms to their genetic data, environmental exposure, and family medical history. This mapping process ensures that the AI’s inputs are directly tied to what matters most to the user.
Step 3: Build a Dynamic Feedback Loop. The context of a situation is constantly changing. A great context-aware AI is not a static system but a learning one. Implement a continuous feedback loop where human users can correct the AI’s understanding, provide additional information, and refine its responses. This “human-in-the-loop” approach is vital for ethical and accurate AI. It allows the system to learn from its mistakes and adapt to new, unforeseen contexts, ensuring its relevance and reliability over time.
Step 4: Prioritize Privacy and Ethical Guardrails. The more context you provide to an AI, the more critical it becomes to manage that information responsibly. From the outset, you must design for privacy, collecting only the data you absolutely need and ensuring it is stored and used in a secure and transparent manner. Establish clear ethical guardrails for how the AI uses and interprets contextual information, particularly for sensitive data. This is not just a regulatory requirement; it is a fundamental aspect of building trust with your users and ensuring that your AI serves humanity, rather than exploiting it.

By following these best practices, you can move beyond simple, reactive AI to a proactive, human-centered intelligence that understands the world not just as a collection of data points, but as a rich tapestry of interconnected context. This is the work that will define the next generation of AI and, in doing so, will fundamentally change how technology serves humanity.

Case Study 1: Improving Customer Service with Context-Aware AI Assistants

The Challenge: Generic and Frustrating Customer Service Chatbots

Many companies have implemented AI-powered chatbots to handle customer inquiries. However, these chatbots often struggle with complex or nuanced issues, leading to frustrating experiences for customers who have to repeat information or are given irrelevant answers. The lack of contextual awareness is a major limitation.

Context Engineering in Action:

A telecommunications company sought to improve its customer service chatbot by implementing robust context engineering. They integrated the chatbot with their CRM system, allowing it to access the customer’s purchase history, past interactions, and current account status. They also implemented memory management so the chatbot could retain information shared earlier in the conversation. Furthermore, they used prompt engineering to guide the chatbot to ask clarifying questions and to tailor its responses based on the specific product or service the customer was inquiring about. For example, if a customer asked about a billing issue, the chatbot could access their latest bill and provide specific details, rather than generic troubleshooting steps. It could also remember if the customer had contacted support recently for a related issue and take that into account.

The Impact:

The context-aware chatbot significantly improved customer satisfaction scores and reduced the number of inquiries that had to be escalated to human agents. Customers felt more understood and received more relevant and efficient support. The company also saw a decrease in customer churn. This case study highlights how context engineering can transform a basic AI tool into a valuable and helpful resource by enabling it to understand the customer’s individual situation and history.

Key Insight: By providing AI customer service assistants with access to relevant customer data and interaction history, companies can significantly enhance the quality and efficiency of support, leading to increased customer satisfaction and loyalty.

Case Study 2: Enhancing Medical Diagnosis with Contextual Patient Information

The Challenge: Over-reliance on Isolated Symptoms in AI Diagnostic Tools

AI is increasingly being used to assist medical professionals in diagnosing diseases. However, early AI diagnostic tools often focused primarily on analyzing individual symptoms in isolation, potentially missing crucial contextual information such as the patient’s medical history, lifestyle, environmental factors, and even subtle cues from their recent health records.

Context Engineering in Action:

A research hospital in the Pacific Northwest developed an AI-powered diagnostic tool for a specific type of rare disease. Recognizing the importance of context, they engineered the AI to integrate a wide range of patient data beyond just the presenting symptoms. This included the patient’s complete medical history (past illnesses, medications, allergies), family medical history, lifestyle information (diet, exercise, smoking habits), recent lab results, and even notes from previous doctor’s visits. The AI was also connected to relevant medical literature to understand the broader context of the disease and potential co-morbidities. By providing the AI with this rich contextual information, the researchers aimed to improve the accuracy and speed of diagnosis, especially in complex cases where isolated symptoms might be misleading.

The Impact:

The context-aware AI diagnostic tool demonstrated a significantly higher accuracy rate in identifying the rare disease compared to traditional methods and earlier AI models that lacked comprehensive contextual input. It was also able to flag potential risks and complications that might have been overlooked otherwise. This case study underscores the critical role of context engineering in high-stakes applications like medical diagnosis, where a holistic understanding of the patient’s situation can lead to more timely and effective treatments.

Key Insight: Context engineering, by enabling a holistic view of a patient’s health and history, is crucial for improving the accuracy and reliability of AI in critical fields like medical diagnosis.

The Future of AI is Contextual

The future of AI is not about building bigger models; it’s about building smarter ones. And a smarter AI is one that can understand and leverage the richness of context, just as humans do. From a human-centered perspective, context engineering is the practice that makes AI more useful, more reliable, and more deeply integrated into our lives in a way that truly helps us. By moving beyond simple prompts and isolated data points, we can create AI systems that are not just powerful tools, but truly intelligent and invaluable partners. The work of bridging the gap between isolated data and meaningful context is where the next great wave of AI innovation will emerge, and it is a task that will demand our full attention.

Image credit: Pexels

Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

The Experience Nexus

1 Reply

Integrating an XMO with Customer, Employee and Partner Advisory Boards

The Experience Nexus - Integrating an XMO with Customer, Employee and Partner Advisory Boards

by Braden Kelley and Art Inteligencia

In today’s fiercely competitive landscape, merely meeting expectations isn’t enough; delivering exceptional experiences is the non-negotiable standard. Customers demand seamless, intuitive journeys. Employees seek engaging, meaningful work that fosters growth. Partners require transparent, collaborative relationships that drive mutual success. As a human-centered change and innovation thought leader, I advocate for a truly holistic approach: the Experience Management Office (XMO). However, an XMO, while powerful in its own right, truly achieves its potential when it’s synergistically integrated with the invaluable, unfiltered insights derived from Customer, Partner, and Employee Advisory Boards. This integration forms a dynamic “experience nexus” of feedback and action, ensuring that experience strategies are not just internally conceived, but genuinely co-created and reflective of the voices that matter most.

The Strategic Imperative of the Experience Management Office (XMO)

Historically, organizations managed customer experience (CX), employee experience (EX), and often partner experience (PX) in isolated silos. This fragmented approach frequently led to inconsistent experiences and missed opportunities for cross-functional improvements. The XMO emerges as the strategic orchestrator, unifying these disparate efforts under a single, cohesive umbrella. Its core mandate is to ensure consistency, proactively identify and eliminate friction points, and drive continuous improvement across all critical touchpoints for every stakeholder. An effective XMO establishes robust methodologies, deploys standardized tools, provides clear governance, and acts as a central repository for all experience data, translating raw insights into prioritized, actionable initiatives.

“An XMO, while powerful in its own right, truly achieves its potential when it’s synergistically integrated with the invaluable, unfiltered insights derived from Customer, Partner, and Employee Advisory Boards.”

Amplifying Voices: The Power of Advisory Boards

While the XMO provides the essential strategic framework and operational discipline, advisory boards inject the authentic, ground-level voice of your critical stakeholders. They offer invaluable qualitative feedback that complements quantitative data.

Customer Advisory Boards (CABs): Comprising your most engaged and influential customers, CABs provide unfiltered feedback on product utility, service delivery, and overall brand perception. They offer a direct window into evolving customer needs, emerging pain points, and often highlight competitive shifts or significant unmet market opportunities. Their strategic input can be a game-changer for product roadmaps and service enhancements.
Partner Advisory Boards (PABs): For organizations deeply reliant on a robust ecosystem of distributors, resellers, integrators, or technology alliances, PABs are indispensable. They offer critical insights into channel effectiveness, the viability of joint go-to-market strategies, and operational friction points that directly impact mutual profitability and success. A strong PAB can foster greater collaboration and loyalty.
Employee Advisory Boards (EABs): Your employees are the living embodiment of your organization’s culture and processes. They are on the front lines, experiencing internal systems and customer interactions firsthand. EABs provide invaluable, real-time feedback on workplace culture, operational inefficiencies, the effectiveness of internal tools, and the direct impact of leadership decisions on morale, productivity, and retention. They serve as both early warning systems and fertile ground for grassroots innovation within the Employee Experience (EX).

The Experience Nexus: From Feedback to Breakthrough Innovation

The true magic of this holistic model is realized when the XMO functions as the intelligent central hub, systematically receiving, synthesizing, and acting upon the rich insights generated by these diverse advisory boards (the strategic spokes). This creates a dynamic, continuous improvement loop, and crucially, an engine for genuine innovation. The XMO’s role goes beyond just operational excellence; it becomes a powerful catalyst for change. By gathering and cross-referencing insights from all three boards, the XMO can identify truly breakthrough opportunities that a siloed approach would miss. It’s in the intersection of these diverse perspectives that the most profound insights for innovation emerge.

Structured Feedback Ecosystem: The XMO establishes formalized, yet flexible, processes for advisory boards to submit feedback. This ensures insights are consistently captured, meticulously categorized, intelligently prioritized, and seamlessly routed to the most relevant internal product, service, or operational teams.
Holistic Data Synthesis & Analysis: The XMO’s analytical capabilities are crucial here. It collates and cross-references qualitative insights from the advisory boards with quantitative experience data (e.g., NPS, CSAT, CES, employee engagement scores, churn rates, partner revenue contribution). This holistic analysis identifies systemic trends, uncovers root causes, and validates hypotheses across the entire experience landscape.
Actionable Insights & Strategic Prioritization: Armed with synthesized, validated data, the XMO plays a pivotal role in guiding leadership to prioritize experience initiatives. It ensures resources and effort are strategically allocated to areas that will deliver the most significant, cross-cutting impact across customer, employee, and partner journeys, driving maximum business value.
Innovation Acceleration: This is where the nexus truly shines. The XMO facilitates cross-functional “insight sharing” workshops, where product, engineering, and design teams are exposed directly to the synthesized feedback. For example, a common pain point from a Customer Advisory Board might be the lack of a specific feature, while an Employee Advisory Board highlights a related internal operational inefficiency, and a Partner Advisory Board reveals a similar competitive gap. When these three insights are combined, they don’t just solve a single problem; they can reveal a massive market opportunity for a new product, service, or business model. The XMO’s role is to identify and champion these “aha!” moments, channeling them directly into the innovation pipeline.
Transparent Closed-Loop Communication: Perhaps most critically, the XMO champions and facilitates regular, transparent communication back to the advisory boards. This demonstrates precisely how their invaluable feedback is being utilized, outlining the tangible progress of implemented initiatives, and celebrating the impact of their contributions. This transparency is vital; it builds deep trust, reinforces the perceived value of their participation, and encourages continued engagement.

Case Study 1: Global SaaS Provider – Unifying the Ecosystem Experience

From Fragmented Insights to Integrated Ecosystem Enhancement

A global B2B SaaS company faced challenges with inconsistent product adoption and suboptimal channel partner engagement. Their existing structure meant customer feedback was managed by the CX team, HR handled employee surveys, and the partner team conducted informal check-ins. This siloed approach led to fragmented insights and disjointed solutions, impacting their overall ecosystem health.

Recognizing the need for a unified strategy, they established a dedicated Experience Management Office (XMO) reporting directly to the Chief Operating Officer. The XMO’s clear mandate was to integrate and elevate all experience initiatives. Concurrently, they formalized their existing Customer Advisory Board (CAB) and launched a new, strategically focused Partner Advisory Board (PAB). The XMO developed a comprehensive quarterly insights report, meticulously combining feedback from the CABs, PABs, and internal employee surveys. A consistent, critical theme emerged from this integrated analysis: the onboarding experience for new customers and channel partners was clunky, inconsistent, and often frustrating across different product lines.

Leveraging this precise feedback, the XMO facilitated cross-functional workshops involving product development, sales, marketing, and customer support teams. This collaborative effort led to the rapid development and deployment of a unified onboarding platform and standardized, role-based training modules. The XMO rigorously tracked key metrics such as “time-to-first-value” for new customers and partner activation rates. Within 18 months, customer satisfaction scores related to onboarding surged by 25%, and partner-led sales increased by a remarkable 15%, demonstrating the profound, tangible benefits of integrating diverse external and internal voices through a centralized, action-oriented XMO.

Key Takeaway: A centralized XMO, fed by structured CAB and PAB insights, can drive enterprise-wide improvements in critical customer and partner journeys, leading to measurable business growth.

Addressing Inherent Challenges and Ensuring Success

Integrating an XMO with robust advisory boards, while incredibly powerful, is not without its inherent hurdles. Proactive mitigation strategies are essential:

Securing Executive Buy-in: This foundational step requires senior leadership to not only champion the XMO’s creation but also to genuinely value and act upon the feedback from advisory boards. Mitigation: Develop a compelling business case, demonstrate clear ROI by linking experience improvements directly to key business outcomes (e.g., revenue growth, cost reduction, retention), and involve executives directly in initial board meetings.
Resource Allocation: Establishing, staffing, and effectively maintaining both a strategic XMO and active advisory boards demands dedicated human and financial resources. Mitigation: Start small and iterate. Begin by focusing on the most critical experience touchpoints, prove incremental value, and then scale resources as the benefits become undeniable and quantifiable.
Preventing “Feedback Fatigue”: Advisory board members are busy, valuable individuals. Ensuring they feel their time is genuinely valued and their feedback consistently leads to tangible action is paramount. Mitigation: Maintain rigorous closed-loop communication, provide transparent updates on progress, celebrate their contributions publicly, and respect their time with concise, focused agendas and clear pre-reads.
Translating Insights into Action: Moving from qualitative feedback to concrete, measurable organizational actions can be complex and requires strong analytical and change management capabilities. Mitigation: The XMO must employ robust analytics, facilitate strong cross-functional collaboration to dismantle silos, and define clear ownership for implementing improvements.

Case Study 2: Regional Retail Bank – Synergistic Employee & Customer Elevation

Transforming Branch Operations Through Integrated Feedback

A prominent regional retail bank was grappling with a concerning decline in customer satisfaction related to in-branch service, compounded by alarmingly high employee turnover, particularly among its front-line tellers. Despite various internal initiatives, leadership struggled to pinpoint the true underlying root causes of these intertwined problems.

In response, the bank strategically established an XMO reporting within its operations department. Crucially, they simultaneously launched an active Employee Advisory Board (EAB), comprising a diverse cross-section of tellers, branch managers, and key back-office support staff. The EAB quickly identified several critical pain points: severely outdated core banking software leading to protracted transaction times, unclear escalation paths for complex customer issues, and insufficient, infrequent training for new product offerings. In parallel, the bank’s existing Customer Advisory Board (CAB) provided consistent feedback echoing concerns about excessive wait times, perceived inconsistencies in service quality, and a lack of personalized interaction.

The XMO proved to be the indispensable bridge. It meticulously analyzed the EAB’s feedback on software inefficiencies and training gaps, cross-referencing it with the CAB’s complaints about wait times and service quality. This integrated analysis revealed a direct, causal correlation: internal operational friction points directly translated into poor customer experiences. The XMO then championed a high-priority, cross-departmental project to modernize the core banking software, streamline digital workflows, and introduce a comprehensive, tiered training program for all branch staff, directly based on EAB recommendations. Regular, transparent updates on progress were provided to both advisory boards, reinforcing their critical role. Within a single year, teller turnover decreased by a remarkable 20%, and customer satisfaction with in-branch service experienced a significant, measurable improvement, unequivocally validating the transformative power of integrating direct employee insights into holistic customer experience enhancements.

Key Takeaway: Integrating EAB insights with CAB feedback via an XMO reveals systemic issues, leading to co-created solutions that dramatically improve both employee and customer experiences.

Conclusion: The Future of Holistic Experience Leadership

The strategic integration of a proactive Experience Management Office with thoughtfully structured Customer, Partner, and Employee Advisory Boards represents the pinnacle of human-centered innovation and leadership. This powerful nexus creates a robust, empathetic, and continuous feedback ecosystem that not only informs and validates but also dynamically refines an organization’s entire experience strategy. It ensures that all strategic decisions and operational improvements are profoundly grounded in real-world perspectives, fostering deeper trust across all stakeholder groups, accelerating the pace of meaningful innovation, and ultimately driving sustainable, differentiated growth. For leaders aspiring to truly excel in the experience economy, this holistic, integrated approach is not merely an option—it is an undeniable imperative. It’s about orchestrating a diverse symphony of voices to create a harmonious, compelling, and continuously improving experience for everyone involved, building loyalty and advocacy from the inside out.

Contact me if you’re interested in working together to build or enhance your Experience Management Office (XMO).

Accelerate your change and transformation success

Content Authenticity Statement: The ideas are those of Braden Kelley, with a little help from Google Gemini to shape the article and create the illustrative case studies.

Image credit: Unsplash

Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

The Unsung Heroes of Culture

Leave a reply

Employee Experience Advisory Boards and the XMO

The Unsung Heroes of Culture - Employee Experience Advisory Boards and the XMO

by Braden Kelley and Art Inteligencia

We live in an age where the war for talent is fiercer than ever, and employee engagement surveys, while useful, often feel like a lagging indicator. Organizations are realizing that a truly thriving culture isn’t built from the top down alone, nor can it be accurately measured by a single annual pulse check. To genuinely understand and nurture the employee experience, you need to go beyond surveys. You need a dedicated, empowered voice from within the ranks: the Employee Experience Advisory Board (EXAB).

For too long, the ‘people’ aspect of business has been relegated to HR, often seen as a cost center rather than a strategic imperative. But the truth is, the employee experience *is* the customer experience. It *is* the innovation engine. And it *is* the foundation of a resilient, high-performing organization. This is where the EXAB, working hand-in-hand with an Experience Management Office (XMO), becomes not just a nice-to-have, but a strategic necessity.

Why an Employee Experience Advisory Board?

An EXAB is a diverse group of employees, representing various levels, departments, and demographics, who serve as a living, breathing feedback loop for the organization. They are the frontline observers, the informal leaders, and the unvarnished truth-tellers who can articulate the nuances of the daily employee journey. Their value stems from several key areas:

Authentic Insights: Surveys tell you *what* happened; an EXAB tells you *why* and *how it felt*. They provide qualitative data that quantitative metrics often miss.
Early Warning System: They can spot emerging issues, potential pain points, and cultural shifts long before they escalate into widespread problems.
Design Thinking in Action: By involving employees in the design of their own experience, you foster a sense of ownership and co-creation. This moves beyond ‘listening’ to ‘co-creating.’
Bridging the Gap: EXABs serve as a crucial bridge between leadership and the broader employee base, fostering trust and transparency.
Innovation Catalysts: A positive employee experience directly fuels innovation. Engaged employees are more likely to contribute ideas, take risks, and collaborate effectively.

Integrating with the Experience Management Office (XMO)

While an EXAB provides invaluable insights, these insights must be acted upon systematically. This is where the Experience Management Office (XMO) comes in. An XMO is a centralized function dedicated to orchestrating, measuring, and improving all experience touchpoints – be they customer, employee, or partner. When an EXAB and XMO collaborate, a powerful synergy emerges:

The EXAB identifies opportunities, pain points, and innovative solutions directly from the employee perspective.
The XMO then takes these insights, analyzes them within the broader experience ecosystem, prioritizes initiatives, allocates resources, and implements changes. They provide the strategic framework and operational muscle.
The EXAB, in turn, can serve as a testing ground for proposed solutions and provide real-time feedback on their effectiveness, ensuring that changes resonate with the employee base.

Think of it this way: the EXAB are the eyes and ears on the ground, providing rich, contextual intelligence. The XMO is the brain and hands, translating that intelligence into actionable strategy and execution across the entire experience landscape. Without the EXAB, the XMO risks making decisions in a vacuum. Without the XMO, the EXAB’s valuable insights might remain unacted upon.

Case Studies in Collaboration: EXAB + XMO in Action

Case Study 1: “Ignite” at a Global Tech Giant

A major technology company, facing increasing attrition rates and feedback indicating a disconnect between leadership vision and daily employee reality, established an EXAB they called “Ignite.” Comprising 25 employees from diverse roles, Ignite met monthly with the newly formed XMO. One of Ignite’s early observations was a pervasive feeling among junior engineers that their ideas weren’t heard and that career progression was opaque. The XMO, informed by Ignite’s granular feedback, launched a series of “Innovator’s Guild” workshops, providing a structured forum for idea submission and mentorship. Simultaneously, they revamped career pathing resources and introduced a transparent internal mobility portal. Within 18 months, not only did attrition rates for junior engineers drop by 15%, but the company also saw a 20% increase in patent submissions directly linked to ideas generated through the guild. The EXAB’s qualitative insights directly fueled the XMO’s strategic interventions, leading to measurable improvements in both culture and innovation output.

Case Study 2: “CareConnect” at a Healthcare Provider

A large healthcare network, grappling with burnout among its nursing staff and a perceived lack of voice, established “CareConnect,” an EXAB specifically for frontline healthcare professionals. Their XMO, initially focused primarily on patient experience, quickly realized the inseparable link between employee well-being and patient outcomes. CareConnect highlighted critical issues such as inefficient shift scheduling, inadequate break facilities, and a desire for more mental health support. The XMO, leveraging this input, implemented a new AI-driven scheduling system that gave nurses more control, redesigned break rooms into “recharge zones,” and launched a comprehensive mental wellness program with on-site counselors. The impact was profound: a 10% reduction in nurse turnover, a significant improvement in patient satisfaction scores (as reported in post-visit surveys), and a visible boost in staff morale. This case demonstrates how an EXAB can pinpoint specific, actionable improvements that directly impact both employee well-being and core business objectives, with the XMO providing the structured approach to scale and sustain these changes.

Building a Culture of Continuous Improvement

The establishment of an EXAB, seamlessly integrated with an XMO, signals a fundamental shift in how organizations approach culture. It moves from a reactive, survey-driven approach to a proactive, co-creative one. It’s about empowering employees not just to report problems, but to be part of the solution. It’s about creating a living, breathing mechanism for continuous cultural improvement.

In a world of constant change, the most resilient and innovative organizations will be those that prioritize the human experience at their core. The Employee Experience Advisory Board and the Experience Management Office are not just strategic tools; they are the architects of a future where work isn’t just a place we go, but a place where we truly belong, contribute, and thrive. If you’re serious about creating a culture that attracts, retains, and inspires the best, it’s time to unleash the power of your people through these vital structures.

Contact me if you’re interested in working together to build or enhance your Experience Management Office (XMO).

Content Authenticity Statement: The ideas are those of Braden Kelley, with a little help from Google Gemini to shape the article and create the illustrative case studies.

Image credit: Unsplash

Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.