Category Archives: Change

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

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

  1. Is OpenAI About to Go Bankrupt? — by Chateau G Pato
  2. The Rise of Human-AI Teaming Platforms — by Art Inteligencia
  3. 11 Reasons Why Teams Struggle to Collaborate — by Stefan Lindegaard
  4. How Knowledge Emerges — by Geoffrey Moore
  5. Getting the Most Out of Quiet Employees in Meetings — by David Burkus
  6. The Wood-Fired Automobile — by Art Inteligencia
  7. Was Your AI Strategy Developed by the Underpants Gnomes? — by Robyn Bolton
  8. Will our opinion still really be our own in an AI Future? — by Pete Foley
  9. Three Reasons Change Efforts Fail — by Greg Satell
  10. Do You Have the Courage to Speak Up Against Conformity? — by Mike Shipulski

BONUS – Here are five more strong articles published in November 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!

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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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Voting Open – Top 40 Innovation Authors of 2025

Vote for Top 40 Innovation AuthorsHappy Holidays!

For more than a decade I’ve devoted myself to making innovation insights accessible for the greater good, because I truly believe that the better our organizations get at deliveriseng value to their stakeholders the less waste of natural resources and human resources there will be.

As a result, we are eternally grateful to all of you out there who take the time to create and share great innovation articles, presentations, white papers, and videos with Braden Kelley and the Human-Centered Change and Innovation team. As a small thank you to those of you who follow along, we like to make a list of the Top 40 Innovation Authors available each year!

Our lists from the ten previous years have been tremendously popular, including:

Top 40 Innovation Bloggers of 2015
Top 40 Innovation Bloggers of 2016
Top 40 Innovation Bloggers of 2017
Top 40 Innovation Bloggers of 2018
Top 40 Innovation Bloggers of 2019
Top 40 Innovation Bloggers of 2020
Top 40 Innovation Bloggers of 2021
Top 40 Innovation Bloggers of 2022
Top 40 Innovation Bloggers of 2023
Top 40 Innovation Bloggers of 2024

Do you just have someone that you like to read that writes about innovation, or some of the important adjacencies – trends, consumer psychology, change, leadership, strategy, behavioral economics, collaboration, or design thinking?

Human-Centered Change and Innovation is now looking to recognize the Top 40 Innovation Authors of 2025.

It is time to vote and help us narrow things down.

The deadline for submitting votes is December 31, 2025 at midnight GMT.

Build a Common Language of Innovation on your team

The ranking will be done by me with influence from votes and nominations. The quality and quantity of contributions to this web site by an author will be a BIG contributing factor (through the end of the voting period).

You can vote in any of these three ways (and each earns points for them, so please feel free to vote all three ways):

  1. Sending us the name of the author by @reply on twitter to @innovate
  2. Adding the name of the author as a comment to this article’s posting on Facebook
  3. Adding the name of the author as a comment to this article’s posting on our Linkedin Page (Be sure and follow us)

The official Top 40 Innovation Authors of 2025 will then be announced here in early January 2026.

Here are the people who received nominations this year along with some carryover recommendations (in alphabetical order):

Adi Gaskell – @adigaskell
Alain Thys
Alex Goryachev
Andy Heikkila – @AndyO_TheHammer
Annette Franz
Arlen Meyers – @sopeofficial
Art Inteligencia
Ayelet Baron
Braden Kelley – @innovate
Brian Miller
Bruce Fairley
Chad McAllister – @ChadMcAllister
Chateau G Pato
Chris Beswick
Chris Rollins
Dr. Detlef Reis
Dainora Jociute
Dan Blacharski – @Dan_Blacharski
Daniel Burrus – @DanielBurrus
Daniel Lock
David Burkus
Dean and Linda Anderson
Dennis Stauffer
Diana Porumboiu
Douglas Ferguson
Drew Boyd – @DrewBoyd
Frank Mattes – @FrankMattes
Geoffrey A Moore
Gregg Fraley – @greggfraley
Greg Satell – @Digitaltonto
Helen Yu
Howard Tiersky
Janet Sernack – @JanetSernack
Jeffrey Baumgartner – @creativejeffrey
Jeff Freedman – @SmallArmyAgency
Jeffrey Phillips – @ovoinnovation
Jesse Nieminen – @nieminenjesse
John Bessant
Jorge Barba – @JorgeBarba
Julian Birkinshaw – @JBirkinshaw
Julie Anixter – @julieanixter
Kate Hammer – @Kate_Hammer
Kevin McFarthing – @InnovationFixer
Leo Chan
Lou Killeffer – @LKilleffer
Manuel Berdoy

Accelerate your change and transformation success

Mari Anixter- @MariAnixter
Maria Paula Oliveira – @mpaulaoliveira
Matthew E May – @MatthewEMay
Michael Graber – @SouthernGrowth
Mike Brown – @Brainzooming
Mike Shipulski – @MikeShipulski
Mukesh Gupta
Nick Jain
Nick Partridge – @KnewNewNeu
Nicolas Bry – @NicoBry
Nicholas Longrich
Norbert Majerus and George Taninecz
Pamela Soin
Patricia Salamone
Paul Hobcraft – @Paul4innovating
Paul Sloane – @paulsloane
Pete Foley – @foley_pete
Rachel Audige
Ralph Christian Ohr – @ralph_ohr
Randy Pennington
Richard Haasnoot – @Innovate2Grow
Robert B Tucker – @RobertBTucker
Robyn Bolton – @rm_bolton
Saul Kaplan – @skap5
Shep Hyken – @hyken
Shilpi Kumar
Scott Anthony – @ScottDAnthony
Scott Bowden – @scottbowden51
Shelly Greenway – @ChiefDistiller
Soren Kaplan – @SorenKaplan
Stefan Lindegaard – @Lindegaard
Stephen Shapiro – @stephenshapiro
Steve Blank
Steven Forth – @StevenForth
Tamara Kleinberg – @LaunchStreet
Teresa Spangler – @composerspang
Tom Koulopoulos – @TKspeaks
Tullio Siragusa
Yoram Solomon – @yoram

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We’re curious to see who you think is worth reading!

Nominations Open – Top 40 Innovation Authors of 2025

Nominations Open for the Top 40 Innovation Authors of 2025Human-Centered Change and Innovation loves making innovation insights accessible for the greater good, because we truly believe that the better our organizations get at delivering value to their stakeholders the less waste of natural resources and human resources there will be.

As a result, we are eternally grateful to all of you out there who take the time to create and share great innovation articles, presentations, white papers, and videos with Braden Kelley and the Human-Centered Change and Innovation team. As a small thank you to those of you who follow along, we like to make a list of the Top 40 Innovation Authors available each year!

Our lists from the ten previous years have been tremendously popular, including:

Top 40 Innovation Bloggers of 2015
Top 40 Innovation Bloggers of 2016
Top 40 Innovation Bloggers of 2017
Top 40 Innovation Bloggers of 2018
Top 40 Innovation Bloggers of 2019
Top 40 Innovation Bloggers of 2020
Top 40 Innovation Bloggers of 2021
Top 40 Innovation Bloggers of 2022
Top 40 Innovation Bloggers of 2023
Top 40 Innovation Bloggers of 2024

Do you have someone that you like to read that writes about innovation, or some of the important adjacencies – trends, consumer psychology, change, leadership, strategy, behavioral economics, collaboration, or design thinking?

Human-Centered Change and Innovation is now looking for the Top 40 Innovation Authors of 2025.

The deadline for submitting nominations is December 24, 2025 at midnight GMT.

You can submit a nomination either of these two ways:

  1. Sending us the name of the author and the url of their blog by @reply on twitter to @innovate
  2. Sending the name of the author and the url of their blog and your e-mail address using our contact form

(Note: HUGE bonus points for being a contributing author)

So, think about who you like to read and let us know by midnight GMT on December 24, 2025.

We will then compile a voting list of all the nominations, and publish it on December 25, 2025.

Voting will then be open from December 25, 2025 – January 1, 2026 via comments and twitter @replies to @innovate.

The ranking will be done by me with influence from votes and nominations. The quality and quantity of contributions by an author to this web site will be a contributing factor.

Contact me with writing samples if you’d like to publish your articles on our platform!

The official Top 40 Innovation Authors of 2025 will then be announced on here in early January 2026.

We’re curious to see who you think is worth reading!

SPECIAL BONUS: From now until December 31, 2025 you can get either the hardcover or softcover of my latest best-selling book Charting Change (free shipping worldwide) for only £/$/€ 23.99 (~36% OFF).

Support this blog by getting your copy of Charting Change

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Change is Never Simple or Linear

Change is Never Simple or Linear

GUEST POST from Greg Satell

I still remember the excitement I felt seeing Kyiv, Ukraine for the first time in 2002. I had been living in Eastern Europe for five years by that time and had the privilege of witnessing first-hand how formerly communist countries moved boldly into a new future of peace and prosperity. Still, Kyiv was different somehow, bigger, more raw and bursting with potential.

An often repeated quip at the time was, “Ukraine is like Poland in 1993… and always will be.” Unlike the Visegrad countries of Poland, Czech, Slovakia and Hungary, Ukraine had been an actual Soviet Republic and the degree of institutional and societal rot created greater challenges. Kyiv in 2002 was, in many ways, a cynical place.

Today, no one can deny that a paradigm shift has occurred. No longer seen as a corrupt backwater, Ukraine has inspired the world with its ingenuity, humanity and courage. Its president, Volodomyr Zelensky, is an international hero. Yet the transformation, while still incomplete, didn’t come easily and it has important lessons that we can learn from.

A Material Desire

In the early 2000s, Ukraine felt like a place in limbo. Ravaged by the 1998 ruble crisis and often considered to be a sub-market of Russia, most multinational companies were running their Ukrainian operations from Moscow. The highly publicized murder of journalist Georgiy Gongadze in 2000 just added to the feeling that the country was stuck in a hopeless limbo.

When I first arrived, there was a palpable sense of political apathy. Many Ukrainians traveled to Europe and, with its neighbor Poland ascending to the EU, were more than aware that they were being left behind. Still, it didn’t seem like anything could be done about the corrupt powers that ruled the country, so why worry about things that didn’t concern you?

That began to change in 2004, when a relatively boring technocratic reformer named Viktor Yushchenko, who was credited with taming hyperinflation as a central banker and helping to improve the economy as Prime Minister, emerged as the opposition candidate for President. Powerful interests opposed his reforms. He was poisoned, leaving his face disfigured. Many expected his candidacy to end there, but it transformed him into an inspirational leader.

The forces backing his opponent, an almost cartoonish thug named Viktor Yanukovych, tried to falsify the election, which led to the Orange Revolution. I remember that, at first, the effort often seemed futile. But we persevered and the Supreme Court of Ukraine nullified the falsified election results. Against seemingly all odds, Yushchenko rose to the presidency.

A Failure To Survive Victory

We had won, or so we thought. The rightful candidate was elected, justice was done and it seemed like a new era had dawned. Yet soon it became clear that things were not going well. The unity of Yushchenko’s coalition broke down and infighting ensued. Planned reforms stalled in a morass of corruption and incompetence. The financial crisis at the end of 2008 put the last nail in the coffin.

In 2010, Victor Yanukovych, the same man we marched against, rose to the presidency. He was even worse than we had feared. He changed the Constitution to grab more power and threw his opponent, Yulia Tymoshenko, in jail to cripple the opposition. Corruption reached new heights (experts estimate that the regime looted as much as $100 billion—an amount almost equal to the entire GDP of Ukraine).

Things came to a head when Yanukovych backed out of a trade agreement with the EU. It was the final straw. It is one thing to steal, to make a mockery of the rule of law and to run the country far below any reasonable standard of governance. But the prospect of EU integration had come to symbolize inclusion into Europe and a chance to, someday, live a normal life. People once again took to the streets in what came to be called the Euromaidan protests.

The regime fought back, but to little avail. Riot police attacked, yet more people came to Kyiv’s central square, known as the “Maidan.” Yanukovych passed a law outlawing the protests and even more came. Things escalated and the regime started shooting the protestors. Soon there were Molotov cocktails, helmets, and improvised shields. In the end more than 100 people were dead in the streets.

The world took notice and the diplomats came. Meanwhile, away from the cameras, other meetings were held in Parliament. The oligarchs, facing sanctions against their western assets, and even Yanukovych’s allies in his own party, had enough. Suddenly bereft of any support, the corrupt strongman fled from the country. An interim government was announced and Petro Poroshenko was elected president later that Spring.

The Rise Of A Consciousness Based On Shared Values

The Orange Revolution got its name because Orange was the campaign color of Yushchenko’s party, Our Ukraine. It was about changing who was in power in the hopes that he could change things. That was our mistake. You can never base a transformation in any one person, policy or program. It always needs to be rooted in shared values.

“In 2015 we were fighting for an idea. That’s why 2015 was different,” Mustafa Nayem, who initiated the protests, would later tell me. They were called “Euromaidan,” because they were about values, specifically European Values. It was a realization that the material aspirations could not be met without a fundamental change in beliefs and how the country saw itself.

“Immediately after Maidan [in 2005], all the people went home and they calmed down,” Nayem told me. “We lost the chance to push the government towards some changes. In 2013, and after Maidan in 2014, many people are still angry, they’re still active, they’re still pushing. And the inner process of these protests is still proceeding. We have this conversion of civil society.”

These events came to be known as the Revolution of Dignity, because it was the moment that the Ukrainian people demanded to have their sovereignty as an independent country recognized, no matter what the cost. That’s what led Putin to annex Crimea, invade Donbas in 2014 and then the entire country in 2022.

To Shift Opinions You Need To Shift Networks

From the outside, Ukraine’s story can seem like a real life version of the hero’s journey, in which an ordinary person is called to greatness and tested in some profound way which leads to a transformation. Yet Volodymyr Zelensky is not Luke Skywalker, Vladimir Putin is not Darth Vader and Russia does not dominate the universe.

While it is true that Zelensky has a particular set of talents that earlier leaders, such as Viktor Yushchenko, lacked, he has been shaped by context at least as much as he has shaped events. Not only is he a member of the first Ukrainian generation to have little memory or nostalgia for the Soviet Union, he is operating in an ecosystem prepared by two revolutions.

To truly shape events, you must shape networks. That is why Russia is failing and Ukraine is succeeding. One thing I noticed living in both countries is that Ukrainians had a deep desire to connect to the world, while Russians were much more suspicious, fearing that taking in elements of other cultures would corrupt their own.

It is networks of unseen connections that lead to transformation and change. You can’t overpower, you need to attract small groups, loosely connected and united by shared purpose to achieve great things. That never happens in a straightforward manner. We live in a world not of linear cause and effect, but of complex ecosystems, which we need to grow and nurture if they are to achieve their full potential.

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

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Will our opinion still really be our own in an AI Future?

Will our opinion still really be our own in an AI Future?

GUEST POST from Pete Foley

Intuitively we all mostly believe our opinions are our own.  After all, they come from that mysterious thing we call consciousness that resides somewhere inside of us. 

But we also know that other peoples opinions are influenced by all sorts of external influences. So unless we as individuals are uniquely immune to influence, it begs at the question; ‘how much of what we think, and what we do, is really uniquely us?’  And perhaps even more importantly, as our understanding of behavioral modification techniques evolves, and the power of the tools at our disposal grows, how much mental autonomy will any of us truly have in the future?

AI Manipulation of Political Opinion: A recent study from the Oxford Internet Institute (OII) and the UK AI Security Institute (AISI) showed how conversational AI can meaningfully influence peoples political beliefs. https://www.ox.ac.uk/news/2025-12-11-study-reveals-how-conversational-ai-can-exert-influence-over-political-beliefs .  Leveraging AI in this way potentially opens the door to a step-change in behavioral and opinion manipulation inn general.  And that’s quite sobering on a couple of fronts.   Firstly, for many today their political beliefs are deeply tied to our value system and deep sense of self, so this manipulation is potentially profound.  Secondly, if AI can do this today, how much more will it be able to do in the future?

A long History of Manipulation: Of course, manipulation of opinion or behavior is not new.  We are all overwhelmed by political marketing during election season.  We accept that media has manipulated public opinion for decades, and that social media has amplified this over the last few decades. Similarly we’ve all grown up immersed in marketing and advertising designed to influence our decisions, opinions and actions.  Meanwhile the rise in prominence of the behavioral sciences in recent decades has provided more structure and efficiency to behavioral influence, literally turning an art into a science.  Framing, priming, pre-suasion, nudging and a host of other techniques can have a profound impact on what we believe and what we actually do. And not only do we accept it, but many, if not most of the people reading this will have used one or more of these channels or techniques.  

An Art and a Science: And behavioral manipulation is a highly diverse field, and can be deployed as an art or a science.   Whether it’s influencers, content creators, politicians, lawyers, marketers, advertisers, movie directors, magicians, artists, comedians, even physicians or financial advisors, our lives are full of people who influence us, often using implicit cues that operate below our awareness. 

And it’s the largely implicit nature of these processes that explains why we tend to intuitively think this is something that happens to other people. By definition we are largely unaware of implicit influence on ourselves, although we can often see it in others.   And even in hindsight, it’s very difficult to introspect implicit manipulation of our own actions and opinions, because there is often no obvious conscious causal event. 

So what does this mean?  As with a lot of discussion around how an AI future, or any future for that matter, will unfold, informed speculation is pretty much all we have.  Futurism is far from an exact science.  But there are a couple of things we can make pretty decent guesses around.

1.  The ability to manipulate how people think creates power and wealth.

2.  Some will use this for good, some not, but given the nature of humanity, it’s unlikely that it will be used exclusively for either.

3.  AI is going to amplify our ability to manipulate how people think.  

The Good news: Benevolent behavioral and opinion manipulation has the power to do enormous good.  Whether it’s mental health and happiness (an increasingly challenging area as we as a species face unprecedented technology driven disruption), health, wellness, job satisfaction, social engagement, important for many of us, adoption of beneficial technology and innovation and so many other areas can benefit from this.  And given the power of the brain, there is even potential for conceptual manipulation to replace significant numbers of pharmaceuticals, by, for example, managing depression, or via preventative behavioral health interventions.   Will this be authentic? It’s probably a little Huxley dystopian, but will we care?  It’s one of the many ethical connundrums AI will pose us with.

The Bad News.  Did I mention wealth and power?  As humans, we don’t have a great record of doing the right thing when wealth and power come into the equation.  And AI and AI empowered social, conceptual and behavioral manipulation has potential to concentrate meaningful power even more so than today’s tech driven society.  Will this be used exclusively for good, or will some seek to leverage for their personal benefit at the expense of the border community?   Answers on a postcard (or AI generated DM if you prefer).

What can and should we do?  Realistically, as individuals we can self police, but we obviously also face limits in self awareness of implicit manipulations.  That said, we can to some degree still audit ourselves.  We’ve probably all felt ourselves at some point being riled up by a well constructed meme designed to amplify our beliefs.   Sometimes we recognize this quickly, other times we may be a little slower. But just simple awareness of the potential to be manipulated, and the symptoms of manipulation, such as intense or disproportionate emotional responses, can help us mitigate and even correct some of the worst effects. 

Collectively, there are more opportunities.  We are better at seeing others being manipulated than ourselves.  We can use that as a mirror, and/or call it out to others when we see it.  And many of us will find ourselves somewhere in the deployment chain, especially as AI is still in it’s early stages.  For those of us that this applies to, we have the opportunity to collectively nudge this emerging technology in the right direction. I still recall a conversation with Dan Ariely when I first started exploring behavioral science, perhaps 15-20 years ago.  It’s so long ago I have to paraphrase, but the essence of the conversation was to never manipulate people to do something that was not in there best interest.  

There is a pretty obvious and compelling moral framework behind this. But there is also an element of enlightened self interest. As a marketer working for a consumer goods company at the time, even if I could have nudged somebody into buying something they really didn’t want, it might have offered initial success, but would likely come back to bite me in the long-term.  They certainly wouldn’t become repeat customers, and a mixture of buyers remorse, loss aversion and revenge could turn them into active opponents.  This potential for critical thinking in hindsight exists for virtually every situation where outcomes damage the individual.   

The bottom line is that even today, we already ave to continually ask ourselves if what we see is real, if our beliefs are truly our own, or have they been manipulated? Media and social media memes already play the manipulation game.   AI may already be better, and if not, it’s only a matter of time before it is. If you think we are politically polarized now, hang onto your hat!!!  But awareness is key.  We all need to stay aware, be conscious of manipulation in ourselves and others, and counter it when we see it occurring for the wrong reasons.

Image credits: Google Gemini

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Bringing Energy Back to Work

Bringing Energy Back to Work

GUEST POST from Geoffrey A. Moore

There are all kinds of survey data these days indicating that morale in the workplace is lower than it used to be and, more importantly, than it ought to be. This has got managers scurrying about trying to find ways to make their employees happier. One word of advice on this: Stop!

It is not your job to make the people on your team happy. That is their job. Your job is to make their work important. Now, as a bonus, there is a strong correlation between meaningful work and worker happiness, so there is a two-birds-for-one-stone principle operating here. It’s just that you have to keep your eye on the lead bird. Employee happiness is a trailing indicator. Customer success is the leading one.

Your team’s customers can be internal or external — it just depends on your performance contract, the one that sets out the outcomes your organization has been funded to deliver. To be meaningful, in one way or another, those outcomes must contribute materially to the overall success of your enterprise’s mission. Your job is to highlight that path, to help your team members see it as a North Star to guide the focus and prioritization of their work. That is what gives their work meaning. Their performance metrics should align directly with the outcomes you have contracted to deliver – else why are they doing the work?

Performance management in this context is simply redirecting their energy to align as closely as possible to the deliverables of your organization’s performance contract. The talent you recruit and develop should have the kind of disposition and gifts that motivate them to want to do this kind of work. If there is a mismatch, help them find some other kind of work that is a better fit for them, and backfill their absence with someone who is a better fit for you. Performance management is not about weeding out—it is about re-potting.

Finally, if we bring this mindset to our current challenges with institutionalizing remote/hybrid operating models, too often this is being framed as an issue of improving employee happiness. Again, not your job. Instead, the focus should be on how best to meet the needs of the customers you have elected to serve. That is, instead of designing enterprise-out, with our heads down in our personal and team calendars, we need to design customer-in, with our heads up looking at where the trapped value is in their world, aligning our energies to release that trapped value, and organizing our operating model to maximize our impact in so doing. If we are not in service to our customers, what use are we?

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

Image Credit: Pexels

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Focus on Shaping Networks Not Opinions

Focus on Shaping Networks Not Opinions

GUEST POST from Greg Satell

Anybody who has ever been married or had kids knows how difficult it can be to convince even a single person. To persuade dozens or hundreds — much less thousands or millions — to change their mind about something important seems like a pipe dream. Yet that doesn’t stop people from spending significant time and energy to do just that.

In fact, there is a massive industry dedicated to shaping opinions. Professionals research attitudes, identify “value propositions,” craft messages and leverage “influencers” in the hopes that they can get people to change their minds. Yet despite the billions of dollars invested each year, evidence of consistent success remains elusive.

The truth is that the best indicator of what people do and think is what the people around them do and think. Instead of trying to shape opinions, we need to shape networks. That’s why we need to focus our efforts on working to craft cultures rather than wordsmithing slogans. To do that, we need to understand the subtle ways we influence each other.

The Influencer Myth

Malcolm Gladwell, blockbuster book, The Tipping Point, popularized his “Law of the Few,” which he stated as: “The success of any kind of social epidemic is heavily dependent on the involvement of people with a particular and rare set of social gifts.” This reenergized earlier ideas about opinion leaders, the supposedly secret people who somehow have outsize influence on others.

Perhaps not surprisingly, the communications industry quickly jumped to promote the idea of secret “influentials” living among us. Clearly, if you’re looking to shape opinions, being able to identify such people would be incredibly valuable and, it goes without saying, firms who could claim an expertise in leveraging those powers could earn outsized fees.

Yet the actual evidence that these people actually exist is incredibly thin. Even the original opinion leader research found that influence was highly contextual. In a more recent study of e-mails, it was found that highly connected people weren’t necessary to produce a viral cascade. In another, based on Twitter, it was found that they aren’t even sufficient. So called “Influentials” are only slightly more likely to produce viral chains.

Duncan Watts, co- author of both studies and a pioneer in the science of networks told me, “The Influentials hypothesis, is a theory that can be made to fit the facts once they are known, but it has little predictive power. It is at best a convenient fiction; at worst a misleading model. The real world is much more complicated.”

The Framingham Heart Study

While there is little evidence to suggest that there are special people secretly influencing our attitudes and decisions, there is abundant evidence that completely normal people exert influence all the time. We may ask our nephew about what app to download, or a co-worker about where to go for dinner. We all have people in our lives that we go to for advice about particular things.

Decades of scientific research suggests that the best indicator of what we think and do is what the people around us think and do. A famous series of studies performed in the 1950s—replicated countless times since then—found that when confronted with a overwhelming opinion, people will conform to the majority even if it is obviously wrong.

More recent research indicates that the effect applies not only to people we know well, but that extends even to second and third-degree relationships. So not only our friends, but the friends of their friends as well—many of whom we may have never met—influence us. This effect not only applies to our opinions, but also things like smoking and obesity and behaviors related to cooperation and trust.

The evidence is, in fact, overwhelming. Working to shape opinions is bound to be a fruitless exercise unless we are able to shape the networks in which ideas, attitudes and behaviors form. Fortunately, there are some fairly straightforward ways to do that.

Starting With A Majority

When we’re passionate about an idea, we want it to spread. We want to tell everyone, especially, for psychological reasons which are not quite clear to me, the opposition. There is some strange quirk embedded in human nature that makes us want to try to convince those who are most hostile to the proposition. We want to convince skeptics.

As should be clear by now, that’s a very bad idea. An idea in its early stages is, almost by definition, not fully formed. It hasn’t been tested and doesn’t have a track record. You also lack experience in countering objections. Taking an idea in its infancy into hostile territory almost guarantees failure.

The simple alternative is to start with a majority, even if that majority is only three people in a room of five. You can always expand a majority out, but once you’re in the minority you’re going to get immediate pushback. Go out and find people who are as enthusiastic as you are, who are willing to support your idea, to strengthen it and help troubleshoot.

That’s how you can begin to gain traction and build a sense for shared purpose and mission. As you begin to work out the kinks, you can embark on a keystone project, show some success, build a track record and accumulate social proof. As you gain momentum, you will find that there is no need to chase skeptics. They will start coming to you.

Small Groups, Loosely Connected, But United By A Shared Purpose

The biggest misconception about change is that once people understand it, they will embrace it and so the best way to drive change forward is to explain the need for change in a convincing and persuasive way. Change, in this view, is essentially a communication exercise and the right combination of words and images is all that is required.

Even assuming that it is practical to convince people that way, by the same logic they can just as easily have their mind changed right back by counter-arguments. So even successful shaping opinions is, at best, a temporary solution. Clearly, if we are going to bring about sustainable change, we need to shape not just opinions, but networks as well.

In my book Cascades, I explained how small groups, loosely connected but united by a shared purpose drive transformational change. It happens gradually, almost imperceptibly, at first. Connections accumulate under the surface, barely noticed, as small groups slowly begin to link together and congeal into a network. Eventually things hit a tipping point.

The good news is that decades of research suggest that tipping point is much smaller than most people think. Everett Rogers’ “S-curve” research estimated it at 10%-20% of a system. Erica Chenoweth’s research calculated the tipping point to be at 3.5% of a society. Damon Centola at the University of Pennsylvania suggests the tipping point to be at 25% of an organization.

I would take each of these numbers with a grain of salt. The salient point here is that nowhere does the evidence suggest we need anything close to 51% support for change to take hold. Our job as leaders is to cultivate networks, help them connect and inspire them with a sense of shared values and shared purpose.

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

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Three Reasons Change Efforts Fail

Three Reasons Change Efforts Fail

GUEST POST from Greg Satell

There’s no question we have entered a transformative age, with major shifts in technology, resources, demography and migration. Over the next decades, we will have to move from digital from post-digital, from carbon to zero-carbon and from the Boomer values to those of Millennials and Zoomers. Migration will strain societies’ social compact.

Unfortunately, we’re really bad at adapting to change. We’ve known about the climate threat for decades, but have done little about it. The digital revolution, for all the hoopla, has been a big disappointment, falling far short of its promise to change the world for the better. Even at the level of individual firms, McKinsey finds that the vast majority of initiatives fail.

One key factor is that we too often assume that change is inevitable. It’s not. Change dies every day. New ideas are weak, fragile, and in need of protection. If we’re going to bring about genuine transformation, we need to take that into account. The first step is to learn the reasons why change fails in the first place. These three are a good place to start.

1. A Flawed Idea

One obvious reason that change fails is that the idea itself is flawed in some way. Barry Libenson found this out when he was hired to be CIO at the industrial conglomerate Ingersoll Rand. It was his first CIO role and Barry was eager to please the CEO, who he saw as a mentor. So he agreed to aggressive very performance targets for modernizing systems.

Yet while Barry was being financially incentivized to upgrade technology, each of the division leaders were financially incentivized to maximize profit growth. Every dollar they invested in modernizing systems would eat into their performance bonus. Perhaps not surprisingly, Barry’s modernization program didn’t go as well as he’d hoped.

There are a number of tools that can help to troubleshoot ideas and uncover flaws. Pre-mortems force you to imagine how a project could fail. Red Teams set up a parallel group specifically to look for flaws. Howard Tiersky, CEO of the digital transformation agency From Digital and author of the Wall Street Journal bestseller Winning Digital Customers, often uses de Bono’s Six Thinking Hats to help the team take different perspectives.

Most of all, we need to come to terms with the reality that our ideas are always wrong. Sometimes they’re off by a little and sometimes they’re off by a lot, but they’re always wrong, so we always need to be on the lookout for problems. As the physicist Richard Feynman put it.“The first principle is that you must not fool yourself — and you are the easiest person to fool. So you have to be very careful about that.”

2. Failure To Build Trust

Proposed in 1983 by Ira Magaziner, the Rhode Island’s Greenhouse Compact is still considered to be an impressive policy even today, 40 years later. In fact, the bipartisan CHIPS Act is based on the same principle, that targeted, strategic government investments can help simulate economic development in the private sector.

The plan in Rhode Island was to establish four research centers or “greenhouses” throughout the state to help drive development in new technologies, like robotics, medicine and thin film materials, as well as existing industries in which the state had built-in advantages, such as tourism, boat-building and fishing. It quickly gained support among the state’s elite

Yet things quickly soured. There were a number of political scandals that reduced faith in Rhode Island’s government and fed into the laissez-faire zeitgeist of the Reagan era. Critics called the plan “elitist,” for taxing “ordinary” citizens to subsidize greedy corporations. When the referendum was held, it plan got less than a fifth of the vote.

Magaziner’s mistake — one he would repeat with the healthcare plan during the Clinton Administration—was ignoring the need to build trust among constituencies. Getting the plan right is never enough. You need to methodically build trust and support as you go.

3. Identity and Dignity

One of the biggest mistakes change leaders make is assuming that resistance to change has a rational basis. They feel that if they listen to concerns and address them, they will be able to build trust and win over skeptics. Unfortunately, while doing those things is certainly necessary for a successful change effort, it is rarely sufficient.

The simple fact is that human beings form attachments to people, ideas and things and when they feel those attachments are threatened, it offends their identity, dignity and sense of self. This is the most visceral kind of resistance. We can argue the merits of a particular idea and methodically build trust, but we can’t ask people to stop being who they think they are.

Don’t waste your time trying to convince the unconvincible. Your efforts will be very unlikely to succeed and very likely to exhaust and frustrate you. The good news is that irrational resistors, if left to their own devices, will often discredit themselves eventually. You can also speed up the process by designing a dilemma action.

What can be hardest about change, especially when we feel passionately about it, is that at some point, we need to accept that others will not embrace it and we will have to leave some behind. Not every change is for everybody. Some will have to pursue a different journey, one to which they can devote their passions and seek out their own truths.

Change Is Not Inevitable

People like to quote the ancient Greek philosopher Heraclitus, who said things like “the only constant is change” and “no man ever steps in the same river twice, for it’s not the same river and he’s not the same man.” They’re clever quotes and they give us confidence that the change we seek is not only possible, but inevitable.

Yet while change in general may be inevitable, the prospects for any particular change initiative are decidedly poor and the failure to recognize that simple fact is why so many transformation efforts fall short. The first step toward making change succeed is to understand and internalize just how fragile a new, unproven initiative really is.

To bring genuine change about you can’t expect to just push forward and have everyone fall in line. No amount of executive sponsorship or program budget will guarantee victory. To move forward, you will need to listen to skeptics, identify and fix flaws in your idea to methodically build trust. Even then, you will have to outsmart those who have an irrational lust to kill change and who act in ways that are dishonest, underhanded and deceptive.

Change is always, at some level, about what people value. That’s why to make it happen you need to identify shared values that reaffirm, rather than undermine, people’s sense of identity. Recognition is often a more powerful incentive than even financial rewards. In the final analysis, lasting change always needs to be built on common ground.

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

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Embodied Artificial Intelligence is the Next Frontier of Human-Centered Innovation

LAST UPDATED: December 8, 2025 at 4:56 PM

Embodied Artificial Intelligence is the Next Frontier of Human-Centered Innovation

GUEST POST from Art Inteligencia

For the last decade, Artificial Intelligence (AI) has lived primarily on our screens and in the cloud — a brain without a body. While large language models (LLMs) and predictive algorithms have revolutionized data analysis, they have done little to change the physical experience of work, commerce, and daily life. This is the innovation chasm we must now bridge.

The next great technological leap is Embodied Artificial Intelligence (EAI): the convergence of advanced robotics (the body) and complex, generalized AI (the brain). EAI systems are designed not just to process information, but to operate autonomously and intelligently within our physical world. This is a profound shift for Human-Centered Innovation, because EAI promises to eliminate the drudgery, danger, and limitations of physical labor, allowing humans to focus exclusively on tasks that require judgment, creativity, and empathy.

The strategic deployment of EAI requires a shift in mindset: organizations must view these agents not as mechanical replacements, but as co-creators that augment and elevate the human experience. The most successful businesses will be those that unlearn the idea of human vs. machine and embrace the model of Human-Embodied AI Symbiosis.

The EAI Opportunity: Three Human-Centered Shifts

EAI accelerates change by enabling three crucial shifts in how we organize work and society:

1. The Shift from Automation to Augmentation

Traditional automation replaces repetitive tasks. EAI offers intelligent augmentation. Because EAI agents learn and adapt in real-time within dynamic environments (like a factory floor or a hospital), they can handle unforeseen situations that script-based robots cannot. This means the human partner moves from supervising a simple process to managing the exceptions and optimizations of a sophisticated one. The human job becomes about maximizing the intelligence of the system, not the efficiency of the body.

2. The Shift from Efficiency to Dignity

Many essential human jobs are physically demanding, dangerous, or profoundly repetitive. EAI offers a path to remove humans from these undignified roles — the loading and unloading of heavy boxes, inspection of hazardous infrastructure, or the constant repetition of simple assembly tasks. This frees human capital for high-value interaction, fostering a new organizational focus on the dignity of work. Organizations committed to Human-Centered Innovation must prioritize the use of EAI to eliminate physical risk and strain.

3. The Shift from Digital Transformation to Physical Transformation

For decades, digital transformation has been the focus. EAI catalyzes the necessary physical transformation. It closes the loop between software and reality. An inventory algorithm that predicts demand can now direct a bipedal robot to immediately retrieve and prepare the required product from a highly chaotic warehouse shelf. This real-time, physical execution based on abstract computation is the true meaning of operational innovation.

Case Study 1: Transforming Infrastructure Inspection

Challenge: High Risk and Cost in Critical Infrastructure Maintenance

A global energy corporation (“PowerLine”) faced immense risk and cost in maintaining high-voltage power lines, oil pipelines, and sub-sea infrastructure. These tasks required sending human crews into dangerous, often remote, or confined spaces for time-consuming, repetitive visual inspections.

EAI Intervention: Autonomous Sensory Agents

PowerLine deployed a fleet of autonomous, multi-limbed EAI agents equipped with advanced sensing and thermal imaging capabilities. These robots were trained not just on pre-programmed routes, but on the accumulated, historical data of human inspectors, learning to spot subtle signs of material stress and structural failure — a skill previously reserved for highly experienced humans.

  • The EAI agents performed 95% of routine inspections, capturing data with superior consistency.
  • Human experts unlearned routine patrol tasks and focused exclusively on interpreting the EAI data flags and designing complex repair strategies.

The Outcome:

The use of EAI led to a 70% reduction in inspection time and, critically, a near-zero rate of human exposure to high-risk environments. This strategic pivot proved that EAI’s greatest value is not economic replacement, but human safety and strategic focus. The EAI provided a foundational layer of reliable, granular data, enabling human judgment to be applied only where it mattered most.

Case Study 2: Elderly Care and Companionship

Challenge: Overstretched Human Caregivers and Isolation

A national assisted living provider (“ElderCare”) struggled with caregiver burnout and increasing costs, while many residents suffered from emotional isolation due to limited staff availability. The challenge was profoundly human-centered: how to provide dignity and aid without limitless human resources.

EAI Intervention: The Adaptive Care Companion

ElderCare piloted the use of adaptive, humanoid EAI companions in low-acuity environments. These agents were programmed to handle simple, repetitive physical tasks (retrieving dropped items, fetching water, reminding patients about medication) and, critically, were trained on empathetic conversation models.

  • The EAI agents managed 60% of non-essential, fetch-and-carry tasks, freeing up human nurses for complex medical care and deep, personalized interaction.
  • The EAI’s conversation logs provided caregivers with Small Data insights into the emotional state and preferences of the residents, allowing the human staff to maximize the quality of their face-to-face time.

The Outcome:

The pilot resulted in a 30% reduction in nurse burnout and, most importantly, a measurable increase in resident satisfaction and self-reported emotional well-being. The EAI was deployed not to replace the human touch, but to protect and maximize its quality by taking on the physical burden of routine care. The innovation successfully focused human empathy where it had the greatest impact.

The EAI Ecosystem: Companies to Watch

The race to commercialize EAI is accelerating, driven by the realization that AI needs a body to unlock its full economic potential. Organizations should be keenly aware of the leaders in this ecosystem. Companies like Boston Dynamics, known for advanced mobility and dexterity, are pioneering the physical platforms. Startups such as Sanctuary AI and Figure AI are focused on creating general-purpose humanoid robots capable of performing diverse tasks in unstructured environments, integrating advanced large language and vision models into physical forms. Simultaneously, major players like Tesla with its Optimus project and research divisions within Google DeepMind are laying the foundational AI models necessary for EAI agents to learn and adapt autonomously. The most promising developments are happening at the intersection of sophisticated hardware (the actuators and sensors) and generalized, real-time control software (the brain).

Conclusion: A New Operating Model

Embodied AI is not just another technology trend; it is the catalyst for a radical change in the operating model of human civilization. Leaders must stop viewing EAI deployment as a simple capital expenditure and start treating it as a Human-Centered Innovation project. Your strategy should be defined by the question: How can EAI liberate my best people to do their best, most human work? Embrace the complexity, manage the change, and utilize the EAI revolution to drive unprecedented levels of dignity, safety, and innovation.

“The future of work is not AI replacing humans; it is EAI eliminating the tasks that prevent humans from being fully human.”

Frequently Asked Questions About Embodied Artificial Intelligence

1. How does Embodied AI differ from traditional industrial robotics?

Traditional industrial robots are fixed, single-purpose machines programmed to perform highly repetitive tasks in controlled environments. Embodied AI agents are mobile, often bipedal or multi-limbed, and are powered by generalized AI models, allowing them to learn, adapt, and perform complex, varied tasks in unstructured, human environments.

2. What is the Human-Centered opportunity of EAI?

The opportunity is the elimination of the “3 Ds” of labor: Dangerous, Dull, and Dirty. By transferring these physical burdens to EAI agents, organizations can reallocate human workers to roles requiring social intelligence, complex problem-solving, emotional judgment, and creative innovation, thereby increasing the dignity and strategic value of the human workforce.

3. What does “Human-Embodied AI Symbiosis” mean?

Symbiosis refers to the collaborative operating model where EAI agents manage the physical execution and data collection of routine, complex tasks, while human professionals provide oversight, set strategic goals, manage exceptions, and interpret the resulting data. The systems work together to achieve an outcome that neither could achieve efficiently alone.

Your first step toward embracing Embodied AI: Identify the single most physically demanding or dangerous task in your organization that is currently performed by a human. Begin a Human-Centered Design project to fully map the procedural and emotional friction points of that task, then use those insights to define the minimum viable product (MVP) requirements for an EAI agent that can eliminate that task entirely.

UPDATE – Here is an infographic of the key points of this article that you can download:

Embodied Artificial Intelligence Infographic

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: 1 of 1,000+ quote slides for your meetings & presentations at http://misterinnovation.com

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The Tax Trap and Why Our Economic OS is Crashing

LAST UPDATED: December 3, 2025 at 6:23 PM

The Tax Trap and Why Our Economic OS is Crashing

GUEST POST from Art Inteligencia

We are currently operating an analog economy in a digital world. As an innovation strategist, I often talk about Braden Kelley’s “FutureHacking” — the art of getting to the future first. But sometimes, the future arrives before we have even unpacked our bags. The recent discourse around The Great American Contraction has illuminated a structural fault line in our society that we can no longer ignore. It is what I call the Tax Trap.

This isn’t just an economic glitch; it is a design failure of our entire social contract. We have built a civilization where human survival is tethered to labor, and government solvency is tethered to taxing that labor. As we sprint toward a post-labor economy fueled by Artificial Intelligence and robotics, we are effectively sawing off the branch we are sitting on.

The Mechanics of the Trap

To understand the Tax Trap, we must look at the “User Interface” of our government’s revenue stream. Historically, the user was the worker. You worked, you got paid, you paid taxes. The government then used those taxes to build roads, schools, and safety nets. It was a closed loop.

The introduction of AI as a peer-level laborer breaks this loop in two distinct places, creating a pincer movement that threatens to crush fiscal stability.

1. The Revenue Collapse (The Input Failure)

Robots do not pay payroll taxes. They do not contribute to Social Security or Medicare. When a logistics company replaces 500 warehouse workers with an autonomous swarm, the government loses the income tax from 500 people. But it goes deeper.

In the race for AI dominance, companies are incentivized to pour billions into “compute” — data centers, GPUs, and energy infrastructure. Under current accounting rules, these massive investments can often be written off as expenses or depreciated, driving down reportable profit. So, not only does the government lose the payroll tax, but it also sees a dip in corporate tax revenue because on paper, these hyper-efficient companies are “spending” all their money on growth.

2. The Welfare Spike (The Output Overload)

Here is the other side of the trap. Those 500 displaced warehouse workers do not vanish. They still have biological needs. They need food, healthcare, and housing. Without wages, they turn to the public safety net.

This creates a terrifying feedback loop: Revenue plummets exactly when demand for services explodes.

The Innovation Paradox: The more efficient our companies become at generating value through automation, the less capable our government becomes at capturing that value to sustain the society that permits those companies to exist.

A Human-Centered Design Flaw

As a champion of Human-Centered Change, I view this not as a political problem, but as an architectural one. We are trying to run a 21st-century software (AI-driven abundance) on 20th-century hardware (labor-based taxation).

The “Great American Contraction” suggests that smart nations will reduce their populations to avoid this unrest. While logically sound from a cold, mathematical perspective, it is a defensive strategy. It is a retreat. As innovators, we should not be looking to shrink to fit a broken model; we should be looking to redesign the model to fit our new reality.

The current system penalizes the human element. If you hire a human, you pay payroll tax, health insurance, and deal with HR complexity. If you hire a robot, you get a capital depreciation tax break. We have literally incentivized the elimination of human relevance.

Charting the Change: The Pivot to Value

How do we hack this future? We must decouple human dignity from labor, and government revenue from wages. We need a new “operating system” for public finance.

We must shift from taxing effort (labor) to taxing flow (value). This might look like:

  • The Robot Tax 2.0: Not a penalty on innovation, but a “sovereign license fee” for operating autonomous labor units that utilize public infrastructure (digital or physical).
  • Data Dividends: Recognizing that AI is trained on the collective knowledge of humanity. If an AI uses public data to generate profit, a fraction of that value belongs to the public trust.
  • The VAT Revolution: Moving toward taxing consumption and revenue rather than profit. If a company generates billions in revenue with zero employees, the tax code must capture a slice of that transaction volume, regardless of their operational costs.

The Empathy Engine

The Tax Trap is only fatal if we lack imagination. “The Great American Contraction” warns of scarcity, but automation promises abundance. The bridge between the two is distribution.

If we fail to redesign this system, we face a future of gated communities guarded by drones, surrounded by a sea of irrelevant, under-supported humans. That is a failure of innovation. True innovation isn’t just about faster chips or smarter code; it’s about designing systems that elevate the human condition.

We have the tools to build a world where the robot pays the tax, and the human reaps the creative dividend. We just need the courage to rewrite the source code of our economy.


The Great American Contraction Infographic

Image credits: Google Gemini

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