How Compensation Reveals Culture

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Five Questions with Kate Dixon

How Compensation Reveals Culture

GUEST POST from Robyn Bolton

It’s time for your company’s All-Hands meeting. Your CEO stands on stage and announces ambitious innovation goals, talking passionately about the importance of long-term thinking and breakthrough results. Everyone nods enthusiastically, applauds politely, and returns to their desks to focus on hitting this quarter’s numbers.  After all, that’s what their bonuses depend on.

Kate Dixon, compensation expert and founder of Dixon Consulting, has watched this contradiction play out across Fortune 500 companies, B Corps, and startups. Her insight cuts to the heart of why so many innovation initiatives fail: we’re asking people to think long-term while paying them to deliver short-term.

In our conversation, Kate revealed why most companies are inadvertently sabotaging their own innovation efforts through their compensation structures—and what the smartest organizations are doing differently.

Robyn Bolton: Kate, when I first heard you say, “compensation is the expression of a company’s culture,” it blew my mind.  What do you mean by that?

Kate Dixon: If you want to understand what an organization values, look at how they pay their people: Who gets paid more? Who gets paid less? Who gets bigger bonuses? Who moves up in the organization and who doesn’t? Who gets long-term incentives?

The answers to these questions, and a million others, express the culture of the organization.  How we reward people’s performance, either directly or indirectly, establishes and reinforces cultural norms.  Compensation is usually the biggest, if not the biggest, expenses that a company has so they’re very thoughtful and deliberate about how it is used.  Which is why it tells you what the company actually does value.

RB: What’s the biggest mistake companies make when trying to incentivize innovation?

KD: Let’s start by what companies are good at when it comes to compensations and incentives.  They’re really good about base pay, because that’s the biggest part of pay for most people in an organization. Then they spend the next amount of time and effort trying to figure out the annual bonus structure. After that comes other benefits, like long term incentives, assuming they don’t fall by the wayside.

As you know, innovation can take a long time to payout, so long-term incentives are key to encouraging that kind of investment.  Stock options and restricted shares are probably the most common long-term incentives but cash bonuses, phantom stock, and ESOP shares in employee-owned companies are also considered long term incentives.

Large companies are pretty good using some equity as an incentive, but they tie it t long term revenue goals, not innovation. As you often remind us, “innovation is a means to the end, which is growth,” so tying incentives to growth isn’t bad but I believe that we can do better. Tying incentives to the growth goals and how they’re achieved will go a long way towards driving innovation.

RB: I’ve worked in and with big companies and I’ve noticed that while they say, “innovation is everyone’s job,” the people who get long-term incentives are typically senior execs.  What gives?

Long-term incentives are definitely underutilized, below the executive level, and maybe below the director level. Assuming that most companies’ innovation efforts aren’t moonshots that take decades to realize, it makes a ton of sense to use long-term incentives throughout the organization and its ecosystem.  However, when this idea is proposed, people often pushback because “it’s too complex” for folks lower in the organization, “they wouldn’t understand.” or “they won’t appreciate it”. That stance is both arrogant and untrue.  I’ve consistently seen that when you explain long-term incentives to people, they do get it, it does motivate them, and the company does see results.

RB: Are there any examples of organizations that are getting this right?

We’re seeing a lot more innovative and interesting risk-taking behaviors in companies that are not primarily focused on profit.

Our B Corp clients are doing some crazy, cool stuff.  We have an employee-owned company that is a consulting firm, but they had an idea for a software product.  They launched it and now it’s becoming a bigger and bigger part of their business.

Family-owned or public companies that have a single giganto shareholder are also hotbeds of long-term thinking and, therefore, innovation.  They don’t have that same quarter to quarter pressure that drives a relentless focus on what’s happening right now and allows people to focus on the future.

What’s the most important thing leaders need to understand about compensation and innovation?

If you’re serious about innovation, you should be incentivizing people all over the organization.  If you want innovation to be a more regular piece of the culture so you get better results, you’ve got to look at long term incentives.  Yes, you should reward people for revenue and short-term goals.  But you also need to consider what else is a precursor to our innovation. What else is makes the conditions for innovating better for people, and reward that, too.

Kate’s insight reveals the fundamental contradiction at the heart of most companies’ innovation struggles: you can’t build long-term value with short-term thinking, especially when your compensation system rewards only the latter.

What does your company’s approach to compensation say about its culture and values?

Image credit: Pexels

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Learning Business and Life Lessons from Monkeys

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Learning Business and Life Lessons from Monkeys

GUEST POST from Greg Satell

Franz Kafka was especially skeptical about parables. “Many complain that the words of the wise are always merely parables and of no use in daily life,” he wrote. “When the sage says: ‘Go over,’ he does not mean that we should cross to some actual place… he means some fabulous yonder…that he cannot designate more precisely, and therefore cannot help us here in the very least.

Business pundits, on the other hand, tend to favor parables, probably because telling simple stories allows for the opportunity to seem both folksy and wise at the same time. When Warren Buffet says “Only when the tide goes out do you discover who’s been swimming naked,” it doesn’t sound so much like an admonishment.

Over the years I’ve noticed that some of the best business parables involve monkeys. I’m not sure why that is, but I think it has something to do with taking intelligence out of the equation. We’re often prone to imagining ourselves as the clever hero of our own story and we neglect simple truths. That may be why monkey parables have so much to teach us.

1. Build The #MonkeyFirst

When I work with executives, they often have a breakthrough idea they are excited about. They begin to tell me what a great opportunity it is and how they are perfectly positioned to capitalize on it. However, when I begin to dig a little deeper it appears that there is some major barrier to making it happen. When I try to ask about it, they just shut down.

One reason that this happens is that there is a fundamental tension between innovation and operations. Operational executives tend to focus on identifying clear benchmarks to track progress. That’s fine for a typical project, but when you are trying to do something truly new and different, you have to directly confront the unknown.

At Google X, the tech giant’s “moonshot factory,” the mantra is #MonkeyFirst. The idea is that if you want to get a monkey to recite Shakespeare on a pedestal, you start by training the monkey, not building the pedestal, because training the monkey is the hard part. Anyone can build a pedestal.

The problem is that most people start with the pedestal, because it’s what they know and by building it, they can show early progress against a timeline. Unfortunately, building a pedestal gets you nowhere. Unless you can actually train the monkey, working on the pedestal is wasted effort.

The moral: Make sure you address the crux of the problem and don’t waste time with peripheral issues.

2. Don’t Get Taken In By Coin Flipping Monkeys

We live in a world that worships accomplishment. Sports stars who have never worked in an office are paid large fees to speak to corporate audiences. Billionaires who have never walked a beat speak out on how to fight crime (even as they invest in gun manufacturers). Others like to espouse views on education, although they have never taught a class.

Many say that you can’t argue with success, but consider this thought experiment: Put a million monkeys in a coin flipping contest. The winners in each round win a dollar and the losers drop out. After twenty rounds, there will only be two monkeys left, each winning $262,144. The vast majority of the other monkeys leave with merely pocket change.

How much would you pay the winning monkeys to speak at your corporate event? Would you invite them to advise your company? Sit on your board? Would you be interested in their views about how to raise your children, invest your savings or make career choices? Would you try to replicate their coin-flipping success? (Maybe it’s all in the wrist).

The truth is that chance and luck play a much bigger part in success than we like to admit. Einstein, for example, became the most famous scientist of the 20th century not just because of his discoveries but also due to an unlikely coincidence. True accomplishment is difficult to evaluate, so we look for signals of success to guide our judgments.

The moral: Next time you judge someone, either by their success or lack thereof, ask yourself whether you are judging actual accomplishment or telltale signs of successful coin flipping. It’s harder to tell the difference than you’d think.

3. The Infinite Monkey Theorem

There is an old thought experiment called the Infinite Monkey Theorem, which is eerily disturbing. The basic idea is that if there were an infinite amount of monkeys pecking away on an infinite amount of keyboards they would, in time, produce the complete works of Shakespeare, Tolstoy and every other literary masterpiece.

It’s a perplexing thought because we humans pride ourselves on our ability to recognize and evaluate patterns. The idea that something we value so highly could be randomly generated is extremely unsettling. Yet there is an entire branch of mathematics, called Ramsey Theory, devoted to the study of how order emerges from random sets of data.

While the infinite monkey theorem is, of course, theoretical, technology is forcing us to confront the very real dilemma’s it presents. For example, music scholar and composer David Cope has been able to create algorithms that produce original works of music that are so good even experts can’t tell they are computer generated. So what is the value of human input?

The moral: Much like the coin flipping contest, the infinite monkey theorem makes us confront what we value and why. What is the difference between things human produced and identical works that are computer generated? Are Tolstoy’s words what give his stories meaning? Or is it the intent of the author and the fact that a human was trying to say something important?

Imagining Monkeys All Around Us

G. H. Hardy, widely considered a genius, wrote that “For any serious purpose, intelligence is a very minor gift.” What he meant was that even in purely intellectual pursuits, such as his field of number theory, there are things that are far more important. It was, undoubtedly, intellectual humility that led Hardy to Ramanujuan, perhaps his greatest discovery of all.

Imagining ourselves to be heroes of our own story can rob us of the humility we need to succeed and prosper. Mistaking ourselves for geniuses can often get us into trouble. People who think they’re playing it smart tend to make silly mistakes, both because they expect to see things that others don’t and because they fail to look for and recognize trouble signs.

Parables about monkeys can be useful because nobody expects them to be geniuses, which demands that we ask ourselves hard questions. Are we doing the important work, or the easiest tasks to show progress on? If monkeys flipping coins can simulate professional success, what do we really celebrate? If monkeys tapping randomly on typewriters can create masterworks, what is the value of human agency?

The truth is that humans are prone to be foolish. We are unable, outside a few limited areas of expertise, to make basic distinctions in matters of importance. So we look for signals of prosperity, intelligence, shared purpose and other things we value to make judgments about what information we should trust. Imagining monkeys around us helps us to be more careful.

Sometimes the biggest obstacle between where we are now and the fabulous yonder we seek is just the few feet in front of us.

— Article courtesy of the Digital Tonto blog
— Image credit: Flickr

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7 Things Leaders Need to Know About Team AI Usage

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7 Things Leaders Need to Know About Team AI Usage

GUEST POST from David Burkus

Leaders, we need to talk about intelligence.

By now you’ve–hopefully–started to take it as seriously as many leaders of industry have been. Either way you look at artificial intelligence, good or bad, it is here to stay. And so we need to start thinking of answers for several questions at the intersection of leadership and AI.

How can it be used effectively, not just to cut costs but to supercharge productivity? How can we use artificial intelligence to supplement our solid foundational leadership? Where should we NOT be using artificial intelligence?

It’s still early in the new world of artificial intelligence in the workplace. A lot of companies are delaying hiring, some are already cutting teams to embrace the optimistic promises AI will bring. But I don’t think we should be all in…yet.

I do know one thing to be true: Leaders using AI will quickly outpace leaders who don’t. And it’s important you get equipped, and in the right way.

Artificial intelligence will make good managers better, but not mediocre bosses better

They say a great actor can bring a C+ movie script up to a B+ or even an A if they are really good. But if a C+ actor is given a C+ script, then it’s going be a C+ movie. The same goes for artificial intelligence and leadership. You need to be a great leader before you start implementing artificial intelligence. AI will not bump up a mediocre manager and turn them into a great leader. It’s not some miracle machine. The truth is you need to have your foundations as a manager be solid first. AI is a good supplement for already successful managers.

Don’t use artificial intelligence to monitor

Often the first temptation of leaders experimenting with AI is to find a productivity AI tool out there, plug it into their IT systems, and start virtually looking over their team’s shoulders to monitor output. There are already dozens of stories…horror stories…of companies doing just that. And it’s not a good look, and deeply hurts morale.

If you need a technology tool to ensure your people are actually working when they say they are, you screwed up a long time ago—back during the hiring process.

And the current research on this isn’t in artificial intelligence’s favor. If AI is used to “collect and analyze data about workers,” then eight out of ten workers say AI use on them would definitely or probably make them feel inappropriately watched. In addition, about a one third of the public does not think AI would lead to equitable evaluations. A majority also agrees this would lead to the information collected about workers being misused (66%).

Artificial intelligence is good at turning anything and everything into a metric. Time is an easy metric. Number of sales calls is an easy metric. Messages on slack is an easy metric. How often you move your mouse is an easy, and terrifying, metric. But just because you have easy numbers to pull on your team doesn’t mean they are the right metrics to be pulling.

Leadership is really about people, not the metrics. How you solicit and give feedback is important. How you support and grow individual employees is important. Inspiring your team and being transparent is important. If you monitor your team endlessly, and your team knows that you’re outsourcing the process of harvesting that data with artificial intelligence, it creates distance between you and them.

And that ultimately works against you in the long run. People don’t like leaders who seem far from them and far from…reality.

Become fluent in artificial intelligence, or risk getting lost in translation

There’s some interesting data from Deloitte on AI that came out in Spring 2024. Organizations reporting “very high” Generative AI expertise expect to change their talent strategies even faster, with 32 percent already making changes. According to their findings, a lot of companies are redesigning work processes and changing workflows to integrate AI at different points.

You’re probably already experiencing this with Google, Microsoft and others integrating artificial intelligence into their core products like email and chats.

Another big focus is going to be on AI fluency. Deloitte found that 47 percent of respondents are dedicating time towards it. The leadership who gets educated on AI early, and keeps training consistently on as it develops, will be the best equipped to shepherd their teams going forward. It’s inevitable that career paths and job descriptions are going to evolve. It’s up to you to stay current.

You NEED to know what the technology is, how it’s being used, and how it’s helping those you’re serving. Be it clients, customers, the public–whomever. Saying you just typed some words into a text box and out came some more words….is not a good answer. Or a good look for you. You sound like you’re treating it like magic, when it’s actually just code.

Turn your conversations and meetings into a database

Middle managers spend a lot of time, arguably too much time, sending progress reports up the chain to the C-Suite and marching orders down to the individual contributors at the bottom. And there’s a fair amount of investigating to find out where things really stand, and time can be spent having to meet multiple people to get all the correct and current information. This is a time slog.

Meanwhile, there are dozens of AI tools now that just take notes. Notes from meetings. Notes from calls. They take the transcript and pair it down to the key takeaways, action items, attendance –a full brief for your records.

So, instead of asking someone to take notes during a meeting or having all your notes in the chat only to evaporate once the zoom call ends, you have a searchable document that you can reference, build on, and keep track of. New hires can use the database to catch up, and senior leaders can get a quick read of the progress and where everything stands.

Use AI/Chat bots to offload small, clerical questions

Here’s a situation: You run a small team and maybe you have a few new hires. You’re going to get a bunch of clerical questions from them over their first 90 days. That’s normal. That’s how it’s supposed to be. Onboarding takes time. “Who’s the point person for this? What’s so and so’s email from HR? What’s the policy for remote days at the company?”

Here’s where artificial intelligence can be really useful. Depending on the sort of chat platform you use– Slack, Teams, whatever, you could make a simple chat bot that you upload a full archive of the company’s policies and your own team norms, clerical details– everything new hires will probably ask you about. So, when those quick questions, quick stop-and-chats happen, the chat-bot can take care of that.

This shouldn’t subtract your time with your new hires. This just subtracts the lower stakes conversations. Now, you have more time for the high-level conversations with them. More coaching. More mentorship. More progression towards team goals. It might sound simple but…that’s because it is.

Use AI as an audience for decisions before taking them public

Being in a leadership role requires making decisive decisions. You include feedback and perspectives from your team as much as possible. Do the research. Talk to people. But then comes the actual decision making. And that is often just you, alone, with your thoughts.

Instead of making your pros and cons list, one practical thing to try is inputting proposed decisions or actions in an AI tool and then asking for all the counterpoints and possible outcomes.

You could even scale this out to your whole team. Ideally, teams should be leveraging task-focused conflict in team discussions to spark new and better ideas. But conflict can be tricky. So, what if AI is always the devil’s advocate? As your team is generating or discussing ideas, you can be feeding those ideas into an AI tool and asking it for counterpoints or how competitors might respond.

Don’t let it make the decision for you but do let it help guide you to possible solutions.

Get the legal clearance before going too deep

One last disclaimer: check with your human resources or your senior leadership, your informational technology (IT) people—or honestly, all of them—to know the boundaries you can work within when using AI tools.

Many of the tools out there are free and still in beta mode or come with a small fee. And most of the larger AI companies are taking whatever data you input and using it to better refine their product. Your company may have rules on the books about data privacy. Certainly, if you work in legal, healthcare, or government services, you’re dealing with sensitive data that may be protected.

Get clear answers before using any AI tools. Until someone above you with authority gives you the OK, you should probably just play with the tools on your own time with your own personal projects.

Conclusion

Artificial intelligence is just getting started in the workplace. And it’s all playing out in real time. If you’re a manager starting to get your hands dirty with these new tools, acknowledge to your team that this is all a work in progress and the norms around AI are likely to evolve. Be sure to keep the playing field level with your team. Practice that transparency, onboard everyone to the tools you’re using and that they can use and see where this takes you. Remember, AI, at its best, is here to enhance our human capabilities, not replace them.

AI will never take the place of a great boss…. but it might be better than being managed by a bad one.

Image credit: David Burkus

Originally published at https://davidburkus.com on September 9, 2024.

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The Future of Military Innovation is Analog, Digital, and Human-Centered

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The Hybrid Advantage

The Future of Military Innovation is Analog, Digital, and Human-Centered

GUEST POST from Art Inteligencia

In the high-stakes world of defense and security, the innovation conversation is often hijacked by the pursuit of the most complex, esoteric, and expensive technology — hypersonic weapons, next-generation stealth fighters, and pure AI command structures. But as a human-centered change and innovation thought leader, I argue that this obsession with technological complexity is a critical strategic mistake. The future of military innovation isn’t a matter of choosing between analog or digital; it’s about mastering Hybrid Resilience — the symbiotic deployment of low-cost, human-centric, and commercially available technologies that create disproportionate impact. The best solutions are often not the most advanced, but the ones that are simplest to deploy, easiest to maintain, and most effective at leveraging the human element at the edge of the conflict.

The true measure of innovation effectiveness is not its unit cost, but its cost-per-impact ratio. When simplicity meets massive scale, the result is a disruptive force that can overwhelm even the most sophisticated, closed-loop military industrial complexes. This shift is already defining modern conflict, forcing traditional defense giants to rethink how they invest and innovate.

The New Equation: Low-Cost Digital and The Power of Speed

The most devastating innovations often come with the smallest price tags, leveraging the widespread accessibility of digital tools and talent. The goal is to maximize chaos and damage while minimizing investment.

Operation Spiderweb: Asymmetric Genius Deep Behind Enemy Lines

The coordinated drone attacks known as “Operation Spiderweb” perfectly illustrate the principle of low-cost, high-impact hybrid warfare. This was not a cyberattack, but an ingenious physical and digital operation in which Ukrainian Security Services (SBU) successfully smuggled over 100 small, commercially available FPV (First-Person View) drones into Russia, hidden inside wooden structures on trucks. The drones were then launched deep inside Russian territory, far beyond the reach of conventional long-range weapons, striking strategic bomber aircraft at five different airbases, including one in Eastern Siberia — a distance of over 4,000 km from Ukraine. With a relatively small financial investment in commercial drone technology and a logistics chain that leveraged analog disguise and stealth, Ukraine inflicted an estimated sizable financial damage — potentially billions of dollars — on critical, irreplaceable Russian military assets. This was a triumph of human-centered strategic planning over centralized, predictable defense.

This principle of scale and rapid deployability is also seen in the physical domain. The threat posed by drone swarms that China can fit in a single shipping container is precisely that they are cheap, numerous, and rapidly deployable. This innovation isn’t about the individual drone’s complexity, but the simplicity of its collective deployment. The containerized system makes the deployment highly mobile and scalable, transforming a single cargo vessel or truck into an instant, overwhelming air force.

The Return of Analog: Simplicity for Survivability

While the digital world provides scale, the analog world provides resilience. True innovation anticipates technological failure, deliberately integrating low-tech, human-proof solutions for survivability.

Take, for example, the concept of drones connected with physical connection (optical fiber cables). In an era of intense electronic warfare and GPS denial, a drone linked by a physical fiber-optic cable is uncorruptible by jamming. The drone’s data link, command, and control remain secure, offering an unassailable digital tether in a highly contested electromagnetic environment. This is an elegant, human-centered solution that embraces an “old” technology (the cable) to solve a cutting-edge digital problem (signal jamming). Similarly, in drone defense, the most effective tool for neutralizing small, hostile drones is often not a multi-million-dollar missile system, but a net gun. These net guns in drone defense are a low-tech, high-effectiveness solution that causes zero collateral damage, is easily trainable, and is vastly cheaper than the target itself. They are the ultimate embodiment of human ingenuity solving a technical problem with strategic simplicity.

The Chevy ISV: Commercial Off-the-Shelf Agility

The Chevy ISV (Infantry Squad Vehicle) is a prime example of human-centered innovation prioritizing Commercial Off-the-Shelf (COTS) solutions. Instead of spending decades and billions designing a bespoke vehicle, the U.S. military adapted a proven, commercially available chassis (the Chevy Colorado ZR2) to meet the requirements for rapid, light infantry mobility. This approach is superior because COTS is faster to acquire, cheaper to maintain (parts are globally accessible), and inherently easier for a soldier to operate and troubleshoot. The ISV prioritizes the soldier’s speed, autonomy, and operational simplicity over hyper-specialized military complexity. It’s innovation through rapid procurement and smart adaptation.

The Human-Augmented Future: Decentralized Command

The most cutting-edge military innovation is the marriage of AI and decentralized human judgment. The future warfighter isn’t a passive recipient of intelligence; they are an AI-augmented decision-maker. For instance, programs inspired by DARPA’s vision for adaptive, decentralized command structures use AI to process the vast amounts of sensor data (the digital part) but distribute the processed intelligence to small, autonomous human teams (the analog part) who make rapid, contextual decisions without needing approval from a centralized HQ. This human-in-the-loop architecture values the ethical judgment, local context, and adaptability that only a human can provide, allowing for innovation and mission execution at the tactical edge.

The Innovation Ecosystem: Disruptors on the Front Line

The speed of defense innovation is now being set by agile, often venture-backed startups, not just traditional primes. Companies like Anduril are aggressively driving hardware/software integration and autonomous systems with a focus on COTS and rapid deployment. Palantir continues to innovate on the data side, making complex intelligence accessible and actionable for human commanders. In the specialized drone space, companies are constantly emerging with highly specialized, affordable solutions that utilize commercial components and open-source principles to achieve specialized military effects. These disruptors are forcing the entire defense industry to adopt a “fail-fast” mentality, shortening development cycles from decades to months by prioritizing iterative, human-centered feedback and scalable digital infrastructure.

Conclusion: The Strategy of Strategic Simplicity

The future of military innovation belongs to those who embrace strategic simplicity. It is an innovation landscape where a low-cost digital intrusion can be more damaging than a high-cost missile, where resilience is built with fiber-optic cable, and where the most effective vehicle is a clever adaptation of a commercial pickup truck. Leaders must shift their focus from what money can buy to what human ingenuity can create. By prioritizing Hybrid Resilience — the thoughtful integration of analog durability, digital scale, and, most importantly, human-centered design — we ensure that tomorrow’s forces are not only technologically advanced but also adaptable, sustainable, and capable of facing any challenge with ingenuity and strategic simplicity.

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: Pexels

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

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Top 10 Human-Centered Change & Innovation Articles of September 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 September’s ten most popular innovation posts:

  1. McKinsey is Wrong That 80% Companies Fail to Generate AI ROI — by Robyn Bolton
  2. Back to Basics for Leaders and Managers — by Robyn Bolton
  3. Growth is Not the Answer — by Mike Shipulski
  4. The Most Challenging Obstacles to Achieving Artificial General Intelligence — by Art Inteligencia
  5. Charlie Kirk and Innovation — by Art Inteligencia
  6. You Just Got Starbucked — by Braden Kelley
  7. Metaphysics Philosophy — by Geoffrey Moore
  8. Invention Through Co-Creation — by Janet Sernack
  9. Sometimes Ancient Wisdom Needs to be Left Behind — by Greg Satell
  10. The Crisis Innovation Trap — by Braden Kelley and Art Inteligencia

BONUS – Here are five more strong articles published in August 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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An Industrial Call-To-Arms for the Environment

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An Industrial Call-To-Arms for the Environment

GUEST POST from Mike Shipulski

What is your obligation to improve the health of our planet?

For the CEO – Look around. Look at Europe. Look at China’s plans. Look at the startups. I know you want to achieve your growth objectives, but if you don’t take seriously the race toward cleaner products and services, you’ll go out of business. You can see this as a problem or an opportunity. Bury your head or put on your track shoes and run! It’s your choice.

Look at the oceans. Look at the landfills. Look at the rise in global temperatures. Just look. This isn’t about ROI, this is about survival. Growth objectives aside, no one will buy things when they are struggling to survive in an uncertain future. Your same old dirty products won’t cut it anymore. So, what are you going to do?

For an example of a path forward, look to the companies in the oil business. Their recipe is clear. They’ve got to use their large but ever-diminishing profits to buy themselves into technologies and industries that will ultimately eat their core business. Though the timing is uncertain, it’s certain that improvements in cleaner technologies will demand they make the change.

Whatever you do, don’t wait. You don’t have much time. Cleaner technologies are getting better every day. It’s time to start.

For Marketing – Look at the upstarts. Look at the powerful companies in adjacent markets who will soon be your direct competitors. Look at your stodgy, unprofitable competitors who are now sufficiently desperate to try anything. Their next marketing push will be built on the bedrock of an improved planet. They’ll be almost as good as you in the traditional areas of productivity and quality and they’ll blow your doors off with their meaner and greener products. Customers will choose green over brown. And they’ll look for real improvements that make the planet smile. The time for green-washing is past. That trick is out of gas.

You need to help customers with new jobs to be done. They care about their environment. They care about their carbon footprint. They care about clean water. And they care about recycling and reuse. It’s real. They care. Now it’s up to you to help them make progress in these areas. It will be a tough road to convince your company that things need to change, but that’s why you’re in Marketing.

You’re already behind. It’s time to start. And it’s up to you to lead the charge.

For Manufacturing – Look at your Value Stream Maps (VSMs). Assign a carbon footprint to each link in the chain. And do the same with water consumption. Assess each process step for carbon and water and rank them worst to best. For the worst, run carbon kaizens and improve the carbon footprint. And run water kaizens for the thirstiest processes.

And look again at your VSMs, and look more broadly. Look back into the supply chain, rank for carbon and water and improve the ones that need the treatment. And teach your suppliers how to do it. And look forward into your distribution channels and improve or eliminate the worst actors. And then propose to Marketing that you teach your customers how to use VSMs to clean up their act. And challenge Engineering to change the design to eliminate the remaining bad actors.

You’ve made good progress with your value streams. Now it’s time to help others make the progress that must be made. As subject matter experts, it’s your time to shine. And, please, start now.

For Engineering – Look at your products. Look at how they’re used. Look at how they’re delivered. Look at how they’re made. Look at how they’re recycled. Sure, your products provide good functionality, but throughout their life cycle they also create carbon dioxide and consume water. And you’re the only ones that can design out the environmental impact.

Learn how to do a Life Cycle Assessment (LCA). Learn which elements of the product create the largest problems. For all the parts that make up the product, sort them worst to best to prioritize the design work. It’s time for radical part count reduction. Try to design out half the parts. It’s possible. And the payoff is staggering. What’s the carbon footprint of a part that was designed out of the product?

Or, to make a more radical improvement, consider an Innovation Burst Event (IBE) to make a fundamental change in the way your products/services impact the environment. With this approach, your innovation work, by definition, will make the planet smile.

It’s time to be open-minded. Ask Manufacturing for the worst processes (including supply chain and distribution) and try to design them out. Design out the part, or change the material, or change the design to enable a friendlier process. Manufacturing can only improve a bad process, but you can design them out altogether. There’s power in that, but with power comes responsibility.

And it’s time for you to take responsibility.

For Everyone in Industry – Regardless of your company, your country or your political affiliation, we can all agree that all our lives get better as the health of our planet improves. And everyone can agree that cleaner air is better. And everyone can agree it’s the same for our water – cleaner is better. And that’s a whole lot of agreement.

As industry leaders, I challenge you to build on that common ground. As industry leaders, I challenge you to improve our planet one product at a time and one process at a time. And as industry leaders, I challenge you to help each other. There’s no competitive disadvantage when you help a company outside your industry. And there’s no shame in learning from companies outside your industry. And it’s good for the planet and profits. There’s nothing in the away. It’s time to start.

As an industry leader, if you want to make a difference in the health of our planet, drop a comment.

Image credit: Pixabay

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Four Keys to a World-Class Customer Experience

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Four Keys to a World-Class Customer Experience

GUEST POST from Shep Hyken

I’m going to start this article with a theme I’ve preached for years: When it comes to customer service and experience, our customers no longer compare us just to our competitors. Their mental benchmark, whether they know it or not, comes from the best experience they have had from any company or brand. It’s companies like Amazon, Apple, Costco, Chick-fil-A, and others that excel in providing an experience that gets customers to come back, that become our customers’ standard for service. When they have anything other than a positive experience, they may say something like, “Why can’t they be as good as _____?” (Fill in the blank with their favorite company.)

With that in mind, I’d like to offer up the idea that if we focus on creating an experience based on trying to be better than a competitor, and that may mean you are the best in your industry, it still may not meet a customer’s expectations. All you are is the best dog in a horse race.

Being best in your industry means best in class, but as I just mentioned, it may not be enough. What you want to do is start comparing yourself – as in your company – to the obvious customer experience leaders. No, you may not be able to do what Amazon or Apple do, but using them as a model can help you move from best in class to world class.

Best in Class Shep Hyken Cartoon

So, how can you make this shift? Start by identifying what makes world-class companies so appealing to their customers. In my annual customer service and customer experience (CX) research, we find the best companies and brands share certain traits:

  1. Consistency – Customers can predict their experience every time. It’s not great one time and the next time just average. Consistency creates predictability, and if the consistent experience is what customers want and know they will get, they come back.
  2. Quick Response – Whether it’s Amazon’s instant confirmation emails or a faster-than-expected returned phone call or email, customers love it when the companies they do business with are fast in their communication.
  3. Empowered Employees – Your customers are frustrated when they are dealing with employees who aren’t allowed to make decisions. If you hire good people and train them well, let them do their job. Not only will customers be happy, but your employees will appreciate the company they work for even more.
  4. Friction-Free – I wrote an entire book on this topic, The Convenience Revolution. Find ways to be easy to do business with. Eliminate anything that is a hassle or has friction associated with it.

Here’s why I love these ideas. You don’t have to be Amazon or Apple to implement any of these. Any company, regardless of size or industry, can do this. You don’t need a technology budget to respond to customers quickly or empower your team.

Look at your customer journey and ask: What would world-class companies, such as Amazon, do at this touch point?” Or, “How would Apple handle this situation?” This exercise can reveal the opportunities you might miss when you’re only comparing yourself to your direct competitors.

Image Credits: Pixabay

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FLASH SALE – 50% off the best book for Planning Change & Transformation

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48 hours only!

Charting Change Second EditionExciting news!

The publisher of my second book – Charting Change – is having a 24-hour FLASH SALE and so you can get the hardcover, softcover or the eBook for 50% off the list price using CODE 50FLSH until October 3, 2025, 11:59PM EDT. The new second edition includes loads of new content including additional guest expert sections and chapters on business architecture, project and portfolio management, and digital and business transformations!

I stumbled across this and wanted to share with everyone so if you haven’t already gotten a copy of this book to power your digital transformation or your latest project or change initiative to success, now you have no excuse!

Click here to get your copy of Charting Change for 50% off using CODE 50FLSH

Of course you can get 10 free tools here from the book, but if you buy the book and contact me I will send you 26 free tools from the 50+ tools in the Change Planning Toolkit™ – including the Change Planning Canvas™!

*If discount is not applied automatically, please use this code: 50FLSH. The discount is available through October 3, 2025. This offer is valid for English-language Springer, Palgrave & Apress books & eBooks. The discount is redeemable on link.springer.com only. Titles affected by fixed book price laws, forthcoming titles and titles temporarily not available on link.springer.com are excluded from this promotion, as are reference works, handbooks, encyclopedias, subscriptions, or bulk purchases. The currency in which your order will be invoiced depends on the billing address associated with the payment method used, not necessarily your home currency. Regional VAT/tax may apply. Promotional prices may change due to exchange rates.

This offer is valid for individual customers only. Booksellers, book distributors, and institutions such as libraries and corporations please visit springernature.com/contact-us. This promotion does not work in combination with other discounts or gift cards.

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The Marketing Guide for Humanity’s Next Chapter

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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?

How AI Changes Your Customers' MarketingThere 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.

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Three Steps from Stuck to Success

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Managing Uncertainty

Three Steps from Stuck to Success

GUEST POST from Robyn Bolton

When a project is stuck and your team is trying to manage uncertainty, what do you hear most often:

  1. “We’re so afraid of making the wrong decision that we don’t make any decisions.”
  2. “We don’t have time to explore a bunch of stuff. We need to make decisions and go.”
  3. “The problem is so multi-faceted, and everything affects everything else that we don’t know where to start.”

I’ve heard all three this week, each spoken by teams leads who cared deeply about their projects and teams.

Differentiating between risk and uncertainty and accepting that uncertainty would never go away, just change focus helped relieve their overwhelm and self-doubt.

But without a way to resolve the fear, time-pressure, and complexity, the project would stay stuck with little change of progressing to success.

Turn Uncertainty Into an Asset

It’s a truism in the field of innovation that you must fall in love with the problem, not the solution. Falling in love with the problem ensures that you remain focused on creating value and agnostic about the solution.

While this sounds great and logically makes sense, most struggle to do it. As a result, it takes incredible strength and leadership to wrestle with the problem long enough to find a solution.

Uncertainty requires the same strength and leadership because the only way out of it is through it. And, research shows, the process of getting through it, turns it into an asset.

Three Steps to Turn Uncertainty Into an Asset

Research in the music and pharmaceutical industries reveals that teams that embraced uncertainty engaged in three specific practices:

  1. Embrace It: Start by acknowledging the uncertainty and that things will change, go wrong, and maybe even fail. Then stay open to surprise and unpredictability, delving into the unknown “by being playful, explorative, and purposefully engaging in ventures with indeterminate outcome.”
  2. Fix It: Especially when dealing with Unknowable Uncertainty, which occurs when more info supports several different meanings rather than pointing to one conclusion, teams that succeed make provisional decisions to “fix” an uncertain dimension so they can move forward while also documenting the rationale for the fix, setting a date to revisit it, and criteria for changing it.
  3. Ignore It: It’s impossible to embrace every uncertainty at once and unwise to fix too many uncertainties at the same time. As a result, some uncertainties, you just need to ignore. Successful teams adopt “strategic ignorance” “not primarily for purposes of avoiding responsibility [but to] allow postponing decisions until better ideas emerge during the collaborative process.

This practice is iterative, often leading to new knowledge, re-examined fixes, and fresh uncertainties. It sounds overwhelming but the teams that are explicit and intentional about what they’re embracing, fixing, and ignoring are not only more likely to be successful, but they also tend to move faster.

Put It Into Practice

Let’s return to NatureComp, a pharmaceutical company developing natural treatments for heart disease.

Throughout the drug development process, they oscillated between addressing What, Who, How, and Where Uncertainties. They did that by changing whether they embraced, fixed, or ignored each type of uncertainty at a given point:

As you can see, they embraced only one type of uncertainty to ensure focus and rapid progress. To avoid the fear of making mistakes, they fixed uncertainties throughout the process and returned to them as more information came available, either changing or reaffirming the fix. Ignoring uncertainties helped relieve feelings of being overwhelmed because the team had a plan and timeframe for when they would shift from ignoring to embracing or fixing.

Uncertainty is Dynamic – You Need to Be Dynamic, Too

You’ll never eliminate uncertainty. It’s too dynamic to every fully resolve. But by dynamically embracing, fixing, and ignore it in all its dimensions, you can accelerate your path to success.

Image credit: Pexels

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