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Why Innovators Can’t Ignore the Quantum Revolution

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Why Innovators Can't Ignore the Quantum Revolution

GUEST POST from Art Inteligencia

In the world of innovation, we are always looking for the next big thing—the technology that will fundamentally change how we solve problems, create value, and shape the future. For the past several decades, that technology has been the classical computer, with its exponential increase in processing power. But a new paradigm is on the horizon, one that promises to unlock capabilities previously thought impossible: quantum computing. While it may seem like a distant, esoteric concept, innovators and business leaders who ignore quantum computing are doing so at their own peril. This isn’t just about faster computers; it’s about a complete re-imagining of what is computationally possible.

The core difference is simple but profound. A classical computer is like a single light switch—it can be either ON or OFF (1 or 0). A quantum computer, however, uses qubits that can be ON, OFF, or in a state of superposition, meaning it’s both ON and OFF at the same time. This ability, combined with entanglement, allows quantum computers to perform calculations in parallel and tackle problems that are intractable for even the most powerful supercomputers. The shift is not incremental; it is a fundamental leap in computational power, moving from a deterministic, linear process to a probabilistic, multi-dimensional one.

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Quantum as an Innovation Engine: Solving the Unsolvable

For innovators, quantum computing is not a threat to be feared, but a tool to be mastered. It provides a new lens through which to view and solve the world’s most complex challenges. The problems that are “hard” for classical computers—like simulating complex molecules, optimizing global supply chains, or cracking certain types of encryption—are the very problems where quantum computers are expected to excel. By leveraging this technology, innovators can create new products, services, and business models that were simply impossible before.

Key Areas Where Quantum Will Drive Innovation

  • Revolutionizing Material Science: Simulating how atoms and molecules interact is a notoriously difficult task for classical computers. Quantum computers can model these interactions with unprecedented accuracy, accelerating the discovery of new materials, catalysts, and life-saving drugs in fields from energy storage to pharmaceuticals.
  • Optimizing Complex Systems: From optimizing financial portfolios to routing delivery trucks in a complex network, optimization problems become exponentially more difficult as the number of variables increases. Quantum algorithms can solve these problems much faster, leading to incredible efficiencies and cost savings.
  • Fueling the Next Wave of AI: Quantum machine learning (QML) can process vast, complex datasets in ways that are impossible for classical AI. This could lead to more accurate predictive models, better image recognition, and new forms of artificial intelligence that can find patterns in data that humans and classical machines would miss.
  • Securing Our Digital Future: While quantum computing poses a threat to current encryption methods, it also offers a solution. Quantum cryptography promises to create uncrackable communication channels, leading to a new era of secure data transmission.

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Case Study 1: Accelerating Drug Discovery for a New Tomorrow

A major pharmaceutical company was struggling to develop a new drug for a rare disease. The traditional method involved months of painstaking laboratory experiments and classical computer simulations to model the interactions of a new molecule with its target protein. The sheer number of variables and possible molecular configurations made the process a slow and expensive trial-and-error loop, often with no clear path forward.

They partnered with a quantum computing research firm to apply quantum simulation algorithms. The quantum computer was able to model the complex quantum mechanical properties of the molecules with a level of precision and speed that was previously unattainable. Instead of months, the simulations were run in days. This allowed the human research team to rapidly narrow down the most promising molecular candidates, saving years of R&D time and millions of dollars. The quantum computer didn’t invent the drug, but it acted as a powerful co-pilot, guiding the human innovators to the most probable solutions and dramatically accelerating the path to a breakthrough.

This case study demonstrates how quantum computing can transform the bottleneck of complex simulation into a rapid discovery cycle, augmenting the human innovator’s ability to find life-saving solutions.

Case Study 2: Optimizing Global Logistics for a Sustainable Future

A global shipping and logistics company faced the monumental task of optimizing its entire network of ships, trucks, and warehouses. Factors like fuel costs, weather patterns, traffic, and delivery windows created a mind-bogglingly complex optimization problem. The company’s classical optimization software could only provide a suboptimal solution, leading to wasted fuel, delayed deliveries, and significant carbon emissions.

Recognizing the limitations of their current technology, they began to explore quantum optimization. By using a quantum annealer, a type of quantum computer designed for optimization problems, they were able to model the entire network simultaneously. The quantum algorithm found a more efficient route and scheduling solution that reduced fuel consumption by 15% and cut delivery times by an average of 10%. This innovation not only provided a significant competitive advantage but also had a profound positive impact on the company’s environmental footprint. It was an innovation that leveraged quantum computing to solve a business problem that was previously too complex for existing technology.

This example shows that quantum’s power to solve previously intractable optimization problems can lead to both significant cost savings and sustainable, planet-friendly outcomes.

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The Innovator’s Call to Action

The quantum revolution is not a distant sci-fi fantasy; it is a reality in its nascent stages. For innovators, the key is not to become a quantum physicist overnight, but to understand the potential of the technology and to start experimenting now. Here are the steps you must take to prepare for this new era:

  • Educate and Evangelize: Start a dialogue about quantum computing and its potential applications in your industry. Find internal champions who can explore this new frontier and evangelize its possibilities.
  • Find Your Partners: You don’t have to build your own quantum computer. Partner with academic institutions, research labs, or quantum-as-a-service providers to start running pilot projects on a cloud-based quantum machine.
  • Identify the Right Problems: Look for the “intractable” problems in your business—the optimization challenges, the material science hurdles, the data analysis bottlenecks—and see if they are a fit for quantum computing. These are the problems where a quantum solution will deliver a true breakthrough.

The greatest innovations are born from a willingness to embrace new tools and new ways of thinking. Quantum computing is the most powerful new tool we have ever seen. For the innovator of tomorrow, understanding and leveraging this technology will be the key to staying ahead. The quantum leap is upon us—are you ready to take it?

Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.

Image credit: Gemini

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Boring AI is the Key to Better Customer Service

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Boring AI is the Key to Better Customer Service

GUEST POST from Shep Hyken

Boring can be a good thing. When something works the way it’s supposed to, it shouldn’t be a surprise. There shouldn’t be friction or drama if a customer has a problem or wants a question answered. It should just be easy. And when it comes to customer service, “easy” and “boring” are good. The experience should just happen the way the customer wants it to happen. You might call that boring. I call that excellent.

That was the beginning of a conversation I had with Damon Covey, general manager of unified communications and collaboration for GoTo, on Amazing Business Radio. GoTo is one of the leading cloud communications companies, providing software and solutions to companies of all sizes and helping them implement AI systems that work, without the complexity and stress that can come from new technology. Covey’s goal for our conversation was to demystify AI, cutting through the noise and complexities of flashy AI and taking it down to a practical level. Boring was the word he liked to use, emphasizing it should be easy, simple and uncomplicated.

In our discussion, Covey said that large companies used to make six- and seven-figure investments to implement AI. Today, AI technology is far superior and, at the same time, much less expensive, so even the smallest companies can afford it. They can get advanced technology for hundreds of dollars, not hundreds of thousands of dollars. Covey said, “For example, a small bike shop or an automotive dealership can now provide the same advanced customer service options as large corporations.” With that in mind, here are the main takeaways from our conversation:

Conversational AI

Until recently (within the past two or three years), a basic chatbot had to follow pre-set rules. Conversational AI provides a much broader opportunity, allowing a computer to interact with people in a natural, human-like manner. Today, AI can understand and respond to customers’ questions and issues with much more flexibility. It has the capability to recognize different languages and understand fumbled phrases, much like a human would. By using conversational AI, businesses can provide 24/7 service, allowing them to respond to customer queries and schedule appointments even when the customer contacts them outside of regular business hours.

Treat AI Like a Team Member

If you hire a new employee, you train them. Treat your AI solutions the same way. Covey said that, similar to training an employee, you need to set specific parameters and provide the AI with the necessary information to ensure it stays within the scope of your business requirements. He emphasized the importance of making sure the AI only draws from the information provided by your business, such as your website, FAQ pages, product manuals, etc., rather than pulling from a source outside of your company, to maintain accuracy and relevance. Covey said that AI should be continuously optimized and trained over time to improve its performance, much like you would train and coach a human employee to expand their capabilities.

Productivity: Automating Processes

Covey talked about automating processes. Anything you do more than three times can be a candidate for AI automation. For example, AI can integrate with a business’ telecommunications system to automate the process of taking notes during calls. It can then summarize the call, put the information into the customer’s record and create a list of next steps, if appropriate. This is a simple function that helps employees be more productive. Instead of an employee typing notes and summarizing the call, AI can handle the task so the employee can move on to helping the next customer.

Augmenting the Business

AI can help businesses do things they don’t normally do, such as remain open for certain functions (like customer support) after hours. It can act as an after-hours receptionist, answering phone calls, setting appointments or providing basic information to customers after business hours. That turns a business that’s typically open during traditional hours to a 24/7 operation.

It is Easier Than You Think

At the end of the interview, Covey dropped a nugget of wisdom that is the perfect way to close this article. For many, especially smaller organizations, deciding what technology to use and how to best use AI can be a daunting decision. It shouldn’t be. Covey says, “Start with the problem you want to solve, and solve for that problem.” He added that you should start using the technology for small problems. Once you understand how it works, the more complicated issues will be easier to solve for.

And that brings us back to where we started. AI doesn’t need to be complicated or flashy. It should be boring—in a good way. Start small, focus on one problem at a time and let AI do what it’s supposed to do: make customer service easier and more efficient. When done right, your customers won’t be amazed by the AI—they’ll just be amazed by how easy it is to do business with you.

Image Credit: Unsplash

This article was originally published on Forbes.com

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Nothing and Everything Has Changed in Customer Service

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Nothing and Everything Has Changed in Customer Service

GUEST POST from Shep Hyken

With all the talk of AI, ChatGPT and more, I’m often asked when interviewed, “What’s changed in customer service?”

My answer is accurate: Nothing!

For thousands of years – actually about 3,775 years – when customers have had a problem or question, they have contacted the company they are doing business with and hoped that it would be resolved to their satisfaction. That’s the way it’s been and will continue to be for thousands of years to come.

But there’s also another answer to the same question about what’s changed: Everything!

By everything, I’m referring to the latest methods of responding to customers’ questions and handling their problems and complaints. I mentioned that for 3,775 years, customers have been contacting companies when they have problems or questions. About 10 years ago, I wrote a Forbes.com article when I learned that tucked away in the British Museum is an ancient complaint that dates back to 1750 B.C.

Nanni, the customer, bought copper ore from a supplier, Ea-Nasir. Unhappy with his purchase, Nanni sent a letter in the form of a stone tablet with the engraved complaint. Loosely translated, the “letter” opens with these words, “What do you take me for that you treat somebody like me with such contempt?” The rest of the letter was a demand that he receive what he thought was right.

Ancient Customer Service Shep Hyken

Customers still complain, and companies – at least the good ones – respond and properly take care of their customers. But how they do so has radically changed.

What may have started as an engraved complaint on a stone tablet eventually turned into handwritten letters, then phone calls, emails, chat, and more modern-day ways of communicating. AI has become the topic of the day, and the strides made in automation and self-service have come a long way.

While many companies are still improving and trying to keep up with the technology, customers who take advantage of the new ways to get questions answered and complaints resolved are very happy with the companies that have kept up with the latest ways to manage the customer experience.

At its core, customer service hasn’t changed. Customers still want to be heard, understood and valued. Sometimes, they even want a little empathy. However, what has changed is the way we deliver that experience. The tools may have evolved from stone tablets to AI chatbots, but the goal remains the same: take care of the customer.

Companies that embrace new technologies while staying true to the timeless principles of great service – listening, responding quickly, and meeting or exceeding expectations – are the ones that will keep their customers coming back. The best companies know that while everything seems to change, the most important thing never changes: a relentless focus on the customer!

Image Credit: Pixabay

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Top 10 Human-Centered Change & Innovation Articles of April 2025

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Top 10 Human-Centered Change & Innovation Articles of April 2025Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are April’s ten most popular innovation posts:

  1. Innovation or Not? – Kawasaki Corleo — by Braden Kelley
  2. From Resistance to Reinvention — by Noel Sobelman
  3. How Innovation Tools Help You Stay Safe — by Robyn Bolton
  4. Should My Brand Take a Political Stand? — by Pete Foley
  5. Innovation Truths — by Mike Shipulski
  6. Good Management is Not Good Strategy — by Greg Satell
  7. ChatGPT Blew My Mind with its Strategy Development — by Robyn Bolton
  8. Five Questions Great Leaders Always Ask — by David Burkus
  9. Why So Many Smart People Are Foolish — by Greg Satell
  10. Beyond Continuous Improvement Culture — by Mike Shipulski

BONUS – Here are five more strong articles published in March that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Build a Common Language of Innovation on your team

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last four years:

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Six Revolutionary AI CX and Customer Service Strategies

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Six Revolutionary AI CX and Customer Service Strategies

GUEST POST from Shep Hyken

Artificial Intelligence (AI) is reshaping customer service and customer experience faster than we could ever imagine. But some are getting it wrong. While everyone’s racing to implement AI, many are missing the most important part – keeping the human element alive. Smart companies have found the balance between the human touch and the digital experience.

One of my favorite AI and marketing experts is Ford Saeks, who recently released his latest book, AI Mindshift: Unleash the Power of AI, Avoid the Pitfalls, and Keep the Human Experience. The book is filled with practical strategies and tactics to help organizations leverage AI while maintaining the personal touch. The book isn’t about which specific AI tools to use. Many of those will be obsolete in a very short time. It’s about how to think about AI, hence the title, AI Mindshift. With that in mind, here are some of my top takeaways from the book:

  1. The Human-AI Balance Is Essential: This is the book’s central theme. Don’t fall into the trap of thinking AI can replace your customer service team. Instead, let AI handle the routine questions and problems while keeping your people focused on what they do best – building relationships and handling more complicated issues. This creates efficiency without sacrificing the personal touch customers value.
  2. Speed Matters: Your customers want answers now, not later. AI can deliver immediate first responses through chatbots, but here’s the key – make sure your customers can seamlessly transition to a human agent when needed. I refer to this as Time to Happiness – how quickly you can move a customer from frustrated to satisfied. The faster, the better.
  3. Feedback Is Your Friend: Create processes to continuously gather both customer and employee feedback about AI interactions. Consistently use this data to refine and improve your AI systems. If customers are frustrated with certain AI responses, fix them quickly. Otherwise, your faulty systems may frustrate your customers and drive them to the competition.

  1. Practice “Ethical AI” in Customer Service: Saeks emphasizes two big areas: transparency about when customers interact with AI versus humans and making sure your AI technology protects your customers’ privacy and data.
  2. Proactive Support: If you want to impress your customers, identify issues or problems before the customer finds them. Then, tell them you did. AI can help identify these issues.
  3. Think Big, but Start Small: Begin AI implementation with specific, manageable customer service tasks rather than trying to overhaul everything at once. For example, start with AI handling basic FAQs, then gradually expand to more complex customer interactions as you learn what works. Remember the old saying, “Rome wasn’t built in a day.”

The bottom line is this: AI isn’t about replacing your customer service team. It’s about making them more amazing at what they do. Saeks’ book reminds us that the future of customer service and CX isn’t about choosing between AI and humans. It’s about combining both to create experiences that get your customers to say, “I’ll be back!”

Image Credit: Pexels, Shep Hyken

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Top 10 Human-Centered Change & Innovation Articles of March 2025

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Top 10 Human-Centered Change & Innovation Articles of March 2025Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are March’s ten most popular innovation posts:

  1. Turning Bold Ideas into Tangible Results — by Robyn Bolton
  2. Leading Through Complexity and Uncertainty — by Greg Satell
  3. Empathy is a Vital Tool for Stronger Teams — by Stefan Lindegaard
  4. The Role Platforms Play in Business Networks — by Geoffrey A. Moore
  5. Inspiring Innovation — by John Bessant
  6. Six Keys to Effective Teamwork — by David Burkus
  7. Product-Lifecycle Management 2.0 — by Dr. Matthew Heim
  8. 5 Business Myths You Cannot Afford to Believe — by Shep Hyken
  9. What Great Ideas Feel Like — by Mike Shipulski
  10. Better Decision Making at Speed — by Mike Shipulski

BONUS – Here are five more strong articles published in February that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

SPECIAL BONUS: While supplies last, you can get the hardcover version of my first bestselling book Stoking Your Innovation Bonfire for 44% OFF until Amazon runs out of stock or changes the price. This deal won’t last long, so grab your copy while it lasts!

Build a Common Language of Innovation on your team

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last four years:

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

FORO: The Fear of Reaching Out

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FORO: The Fear of Reaching Out

GUEST POST from Shep Hyken

We’ve all experienced long hold times, repeating our “story” because we get transferred from one customer service rep to another, etc. It’s an ugly customer service experience that gives many customers FORO, or the Fear of Reaching Out.

FORO is the result of an experience marred with time-wasting friction that makes customers dislike having to reach out to customer support. Our annual customer service and Customer Experience (CX) research (sponsored by RingCentral) finds that 43% of customers would rather clean a toilet than call customer support. The support experience can be so bad that 60% of customers admit to hanging up on a support agent, 34% admit to yelling at an agent, and 21% admit to cussing at an agent. So, it does make sense that customers would have FORO due to poor experiences they have had with some companies and brands (not all) in the past.

Because some companies get it right and others don’t, the inconsistency makes the customer wonder what the next time will be like. Their past frustration, anxiety or memory of a bad experience creates the unwillingness to call.

I had a chance to interview Gaurav Passi on Amazing Business Radio, and he introduced me to the concept of FORO. Passi is the co-founder and CEO of Zingly.AI, a platform that empowers customers to collaborate with a company, either through AI or with direct human-to-human interactions, to have their questions answered and problems resolved. Below are some of Passi’s most intriguing points, followed by my commentary:

  1. The next 15-20 years will be about the end customer experience. Many consulting companies and business experts recognize that customer experience is more important than a company’s product. Most customers can buy the same product—or at least similar products—from many different sources. What differentiates the companies and brands that sell these products is the experience. Passi agrees and adds that the way companies deliver support is changing. The future of CX is a blend of AI, digital and human/live support. That prompted me to ask Passi a question that concerns many people, especially customer support agents, “Do you see AI replacing live agents in that time frame?” He answered, “I don’t see a world where humans are completely taken out.”
  2. Customers don’t want to talk to a human being — until they do. Passi says that customers often don’t want to talk to a human. They just want an answer as quickly and efficiently as possible. If they can’t get it, then they want to talk to a human … as quickly and efficiently as possible. Even with many customers desiring this self-service approach, Passi cautions that companies should not make the mistake of 100% deflection to digital self-service. He asks, “Even if you achieve 100% deflection, what will happen to your customer satisfaction (CSAT) scores?” Passi shared an example of a client who had chosen to deflect 100% of customer support to digital self-service and had an outage. Because of the outage, the employees ended up talking to customers, human-to-human. Amazingly — or not — CSAT went up. Why? Passi says, “Because there was a human touch when needed.”
  3. Customer patience is at an all-time low. This is a primary symptom of FORO. Customers don’t have the time or patience to go online to a company’s website, find the customer support number, wait on hold, get authenticated, etc. They want, as Passi calls it, a “One shot, one kill experience.” Using the company’s self-service options, often fueled by AI, you ask a question, and an answer comes back. It’s as simple as that. The customer appreciates not having to get on the phone, wait on hold, etc., etc.
  4. AI is not the final answer! While AI is revolutionizing customer service and support by enabling businesses to scale their operations efficiently, maintaining the human touch with customers to foster genuine relationships is still important. But the human touch doesn’t have to kick in until it’s needed. And in the perfect world, the platform will recognize customers’ reactions when they aren’t getting the answers they need. Passi is proud of what he refers to as “the most magical component we’ve created in the past three years,” which is a technology that understands when the customer is not getting the right answer and seamlessly passes them to a human agent to take over.

If you’ve been following my work, you know I’m focused on helping my clients create amazing customer experiences. As Passi and I wrapped up our interview, he mentioned that amazing is what Zingly is about. He shared that his mission, like mine, is to help his customers create amaZINGLY great experiences for their customers. With an increasing demand for customers to have more control over how, when and on which devices they communicate with businesses, the combination of AI and human expertise, paired with transparency and collaboration with customers, can create a more personalized, effective and amaZINGLY great customer experience.

Image Credit: Pixabay

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Unlocking Trapped Value with AI

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Unlocking Trapped Value with AI

GUEST POST from Geoffrey A. Moore

Anyone who has used Chat GPT or any of its cousins will testify to its astonishing ability to provide valuable responses to virtually any query. This is hardly a threat—indeed, it is a boon. So, what are we worrying about?

Well, there is the issue of veracity, of course, and it is true, GPT-enabled assistants can indeed make mistakes. But, come on—humans don’t? We are not looking for gospel truth here. We want highly probable, highly informed answers to questions where we need guidance, and it is clear that GPT-enabled applications are outstanding at meeting this need, for at least three reasons. They are remarkably well-informed. They are available 24/7 on demand with no hold time. And they have infinite patience. So, let’s not kid ourselves. We are massively better off for their emergence on the scene.

What we should be worrying about, on the other hand, is their impact on jobs to be done, employment, and career development. A simple way to think about this is that for any of us to earn money, we have to release some form of trapped value. A bank clerk helps a customer get access to the trapped value in their savings account. A bus driver helps a passenger cope with their trapped value by transporting them to the location where they need to be. A lawyer helps a client get access to trapped value by constructing a contract that meets their needs while protecting against risk. A teacher helps a student access trapped value by helping her solve problems she couldn’t handle before. The principle applies to every job. All systems have points of trapped value, and all jobs are organized around releasing and capturing that value.

Now, let’s introduce generative AI. All of a sudden, a whole lot of trapped value that funded a whole lot of jobs can now be released for free (or virtually for free). Those jobs can be protected in the short term but not forever. In other words, the environment really has changed, and we must assess our new circumstances or fall behind. This is Darwinism at work. Evolution never stops. It can’t. As long as there is change, there will be dislocation, which in turn will stimulate innovation. That’s life.

But here’s the good news. The universe can never eliminate trapped value, it can only move it from place to place. That is, there are always emergent problems to solve, always new opportunities to capitalize on, because every system always traps value somewhere. What Darwinism requires is that we detect the new value traps and redirect our activity to engage with them.

Publicly funded agencies sometimes interpret this as a mandate for training programs, but we have to be careful here. Training works well for disseminating established skills that address known problems. It does not work well, however, where the problems are still being determined and the skills are as yet undeveloped. Novelty, in other words, demands creativity. It is simply not negotiable.

Getting back to the impact of generative AI, we should understand that it is an advisory technology. It is not automation. That is, it is not eliminating the need for human beings to make judgment calls. Rather, it is accelerating the preparation for so doing and framing the options in ways that make decision-making more straightforward. By solving for the old value traps, it is giving us the opportunity to up our game. It’s our job to step up to add net new value to the equation.

The best way to do this is to ferret out the emerging new value traps. Who is the customer now? What is the bottleneck that is holding them back? How could that bottleneck be broken open? What is the reward for so doing? These are the fundamental questions that drive any business model. We know how to do this. It’s just that we have been riding on the inertia of the past set of solutions for so long we may have atrophied in some of the muscles we need now. One thing we need not worry about is the universe running out of trapped value. If you are ever in doubt, just read the day’s headlines and be reassured. The world needs our help. Any tool that helps us do our part better is a blessing.

That’s what I think. What do you think?

Image Credit: Pexels

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Beyond the AI Customer Experience Hype

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Beyond the AI Customer Experience Hype

GUEST POST from Shep Hyken

I’ve been writing a lot about artificial intelligence (AI) and the digital customer experience (CX). Many of the executives I interview and the articles I refer to are all about how AI is revolutionizing, changing, helping and sometimes hurting CX. So we’ve heard from experts. How about if we heard from the customers?

That’s exactly what we did in our annual customer service and CX research sponsored by RingCentral. We asked more than 1,000 U.S. consumers about their experiences with AI and digital customer support, and here are the basic findings for 2024:

The Good

  1. Sixty-two percent of U.S. consumers expect that AI (and related technologies) will be the primary mode of customer service in the future. But how about today? As you will see in some of the findings below, not everyone feels AI is ready for primetime customer service and CX.
  2. Thirty-eight percent believe AI and related technologies will lead to more personalized customer experiences. Personalization has been a hot topic for marketing and CX leaders. AI is giving companies and brands far greater capabilities to use customer data to create a personalized experience. Customers enjoy doing business with companies that recognize them and use the information they have to create a better experience.
  3. Forty-nine percent think AI technologies have the potential to improve the overall customer experience. This is good news, however, the next group of findings shows that companies still have an uphill battle to get customers to adopt and embrace a CX fueled by AI.

The Bad

  1. Only 32% of customers have successfully resolved a customer service issue using AI or ChatGPT technologies. That number is low. One theory is that customers often don’t realize AI is what’s behind what they are doing. Some think AI is chatbots and automated voice response systems that interact with them like a human would or should.
  2. Fifty-six percent of customers admit to being scared of technologies like AI and ChatGPT. Some of these customers may have watched movies where computers take over the world or robots go rogue, none of which are grounded in reality. However, some customers simply don’t trust the technology because of past bad experiences.
  3. Sixty-three percent of customers are frustrated with self-service options using AI, ChatGPT and similar technologies. Frustration is different than being scared, but it has the same impact: customers would rather avoid technology and talk to a live human for support and service.

As I studied the significance of these findings as a whole, the overarching theme of why AI has not caught on as a viable and reliable customer support option is inconsistency. Included in the annual study is a finding that 70% of customers choose talking to a live customer service agent on the phone as their primary channel for customer service.

Why? It’s easier, and customers know what to expect when they talk and interact with live agents. What they don’t want to experience is a self-service solution powered by AI that takes them through a series of prompts that eventually lead to a dead end, where they end up having to call the company anyway.

There’s good reason for the fear and frustration. As more customers are exposed to AI and start to understand it, their inconsistent experiences from one company to the next are creating a confidence problem. The latest technology, which is very cost-effective for even small businesses, has not been purchased and implemented by a majority of businesses.

As of the beginning of this year, just 27% of customers think self-service or automated customer support using AI-powered technology can deliver as good of a customer experience as a live agent. That number will eventually go up, although not as quickly as it needs to. Once companies recognize that bad service equates to lost business, they will make the investment to do it right. It’s not an option if they want their customers to say, “I’ll be back!”

This article was originally published on Forbes.com

Image Credits: Unsplash

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Innovation or Not – AI Birdwatching

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Innovation or Not - AI Birdwatching

GUEST POST from Art Inteligencia

Welcome to another installment of the “Innovation or Not” series, where we dissect intriguing products and services to determine whether they truly represent ingenuity, or if they’re just another notch on the belt of incremental progress. Today, we’re venturing into the realm of birdwatching — a niche hobby that surprisingly intersects with cutting-edge artificial intelligence and automated insights into our avian neighbors.

Introducing FeatherSnap

The product up for review is the FeatherSnap bird feeder camera. At its core, FeatherSnap is a bird feeder equipped with a camera that not only captures images of our feathery friends but also uses AI to identify species and offer insights to the user. The idea itself blends the tranquility of birdwatching with the technological advancements of AI and machine learning. It also has a smart design to integrate the food storage into the structure itself to save space, and has solar panels to power the onboard technology. But the question remains: is this a pleasant convenience or a groundbreaking innovation?

The Tech Behind FeatherSnap

FeatherSnap integrates a high-quality camera with AI capabilities to recognize and catalog bird species visiting your garden or backyard. It allows the user to receive real-time alerts on their smartphone, providing information about the birds that stop by for a snack. This records data such as the species, time of day, and frequency of visits, creating a rich, personalized avian database over time.

“AI birdwatching may be niche, but it bridges a gap between nature enthusiasts and technology, making the act of observation more engaging and informed.”

Innovation Analysis

When assessing FeatherSnap through the lens of innovation, we explore several key criteria:

  • Originality: AI-augmented birdwatching is a fresh take on a traditional hobby, significantly enhancing the user experience.
  • Technology Application: The application of AI in identifying bird species represents an advancement in both hobbyist technology and AI’s practical capabilities.
  • Value Creation: FeatherSnap adds substantial value to the birdwatching experience by providing educational insights and personalized interaction with nature.
  • Market Impact: While its potential market may seem limited to bird enthusiasts, the push towards automated, intelligent environmental engagement could have broader applications.

Final Verdict: Innovation or Not?

So, is FeatherSnap an innovation or not? Taking all factors into consideration, I would argue that FeatherSnap qualifies as an innovation. Despite its niche market, it presents a clever integration of AI with everyday life that could inspire further applications across different domains. The product encourages a deeper interaction with nature and presents a template for utilizing technology to enrich leisure activities.

In the broader context of our tech-driven world, FeatherSnap’s introduction to the market both exemplifies ingenuity in leisure tech and challenges developers to think creatively about AI’s scope and potential in nature-based contexts.

As we reflect on this product, it reminds us that innovation isn’t always about life-changing inventions but also about elevating the simple joys of life with smart adaptations.

I encourage you to share your thoughts and opinions on FeatherSnap and whether you consider it groundbreaking or just another incremental product in the tech landscape. Until next time, keep questioning and exploring the ever-changing facets of innovation around you.

Image credit: FeatherSnap

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