Category Archives: Psychology

Time to Stretch Yourself

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Time to Stretch Yourself

GUEST POST from Mike Shipulski

If the work doesn’t stretch you, choose new work. Don’t go overboard and make all your work stretch you and don’t choose work that will break you. There’s a balance point somewhere between 0% and 100% stretch and that balance point is different for everyone and it changes over time. Point is, seek your balance point.

To find the right balance point, start with an assessment of your stretch level. List the number of projects you have and sum the number of major deliverables you’ve got to deliver. If you have more than three projects, you have too many. And if you think you take on more than three because you’re superhuman, you’re wrong. The data is clear – multitasking is a fallacy. If you have four projects you have too many. And it’s the same with three, but you’d think I was crazy if I suggested you limit your projects to two. The right balance point starts with reducing the number of projects you work on.

Now that you eliminated four or five projects and narrowed the portfolio down to the vital two or three, it’s time to list your major deliverables. Take a piece of paper and write them in a column down the left side of the page. And in a column next to the projects, categorize each of them as: -1 (done it before), 0 (done something similar), 1 (new to me), 2 (new to team), 3 (new to company), 5 (new to industry), 11 (new to world).

For the -1s, teach an entry level person how to do it and make sure they do it well. For the 0s, find someone who deserves a growth opportunity and let them have the work. And check in with them to make sure they do a good job. The idea is to free yourself for the stretch work.

For the 1s, find the best person in the team who has done it before and ask them how to do it. Then, do as they suggest but build on their work and take it to the next level.

For the 2s, find the best person in the company who has done it before and ask them how to do it. Then, build on their approach and make it your own.

For the 3s, do your research and find out who in your industry has done it before. Figure out how they did it and improve on their work.

For the 5s, do your research and figure out who has done similar work in another industry. Adapt their work to your application and twist it into something magical.

And for the 11s, they’re a special project category that live in rarified air and deserve a separate blog post of their own.

Start with where you are – evaluate your existing deliverables, cull them to a reasonable workload and assess your level of stretch. And, where it makes sense, stop doing work you’ve done before and start doing work you haven’t done yet. Stretch yourself, but be reasonable. It’s better to take one bite and swallow than take three and choke.

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The Language of Thought

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The Language of Thought

GUEST POST from Geoffrey Moore

Where do thoughts come from? Is there any structure to them before they manifest themselves in language? Is there a universal grammar that underlies every actual grammar?

These questions have been asked many times before. My answers are as follows:

  • They come from below, not above.
  • They do have a readily describable structure.
  • That structure does indeed underly every actual grammar.

The first answer is the most important one. If the language of thought precedes symbolic language, then symbolic language is emergent from it, and the way to study is not through self-examination but rather by observing the behavior of non-language speaking agents. Of these my favorite two are babies and dogs. Both exhibit a myriad of strategic behaviors that imply thought but clearly do not entail language. So, based on observing them, what can we say about the structure of such thinking?

Babies and dogs, I propose, process the following five concepts routinely and effectively:

  1. Agents. They recognize and respond to people and animals that can interact with them, as indicated by their eye contact, their coming and going, and response to commands and gestures.
  2. Objects. They recognize and can discriminate among objects that interest them, both inanimate and animate, including foods, toys, playmates, and parents. They do not distinguish between animate and inanimate objects in any consistent way.
  3. Actions. They initiate and respond to actions in ways that further their interests, be that in feeding, playing, or getting attention. They are inherently attracted to action in any form.
  4. Valence. They discriminate between things they like and things they don’t like, seeking the former and avoiding the latter, as witnessed by their eating and their expressions of mood.
  5. Uncertainty. When uncertain, they hesitate and respond tentatively until they can resolve their uncertainty.

My claim is that these five concepts map directly to the fundamental syntax of every one of the six thousand or so symbolic languages currently in use. Agents and objects both convert to nouns and noun-like entities that serve as subjects and predicate objects in declarative statements. Similarly, actions convert to verbs and verb-like phrases. When we combine nouns with actions, we get predications, or what I like to term claims, which are the fundamental units of symbolic discourse. Valences foreshadow the use of adjectives, adverbs, and other modifiers that add nuances to our claims, and uncertainty is represented by modal verbs expressing possibility, probability, or necessity.

As much ground as all this covers, it is important to understand what the language of thought does not entail. Take the sentence “John is tall.” That thought would never occur to either a baby or a dog. It is inherently symbolic in nature, and until you have a symbolic language, it cannot exist. In The Infinite Staircase, it belongs to the stairstep of analytics, whereas the language of thought can reach no higher than the stairstep of narrative.

It is on the stairstep of narrative that the language of thought passes the baton to symbolic language. We cannot tell stories without symbolic language, but it is clear from the behavior of both toddlers and long-term pets that we want to. The connection that binds the two at this point is a realization of cause and effect. Narrative is how we process cause and effect. The breakthrough of symbolic language is that we can not only be a lot more precise in our communication, increasing its efficacy, but also that we can abstract from one narrative concepts and patterns that can be applied elsewhere. This is the miracle of analytics, and it only comes with symbolic language.

To close, let’s revisit our first question—where exactly do our (symbolic-language-expressed) thoughts originate from? This is not a brain-processing question—that landscape is still under investigation—but rather a question of lived experience. Where does it feel like they come from?

My answer is that they are chemically generated responses that represent fluctuations in our homeostatic balance. Like all organisms, we are compelled to seek this balance all the time. The more we get out of balance, the stronger the chemical signal to respond, the more intense the resultant stream of thoughts will be. This applies to dreams as well as to when we are awake. We are continually processing a stream of thoughts that emerge into consciousness and finding their linguistic expression as they do. We register these thoughts through listening to ourselves and shape them further through talking to ourselves. It is only when we get to the talking that we are fully immersed in symbolic language.

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

— Image credit: Pixabay

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Unleashing Your Innovation Potential

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Unleashing Your Innovation Potential

GUEST POST from Janet Sernack

It is not unusual, especially in the corporate world, to label someone who disrupts and challenges the status quo, or what others say, as argumentative and “oppositional”. According to Human Synergistics, the Oppositional Style, in their circumplex, when measured as a dominant leadership style, is summarized in their 360-degree Leadership Styles Inventory (LSI) by two items: “usually against things” and “opposes new ideas.” It labels the person, or leader as being aggressively defensive and causes them to disengage by avoiding engaging in any kind of conflict, dissent and disagreement. This inhibits and prevents them from unleashing their creative thinking and their innovation potential.

In my many years as a corporate trainer presenting high-performance cultures and transformational leadership programs, I learned to apply my imagination, curiosity and inquiry skills to be attentively present, listen deeply and ask generative questions. This helped me develop strategies to unleash a person’s innovation potential by encouraging and enabling thoughtful dissent and disagreement.  I learned to uncover and recognize a leader’s energy and positive intent behind many of the scary, argumentative, hostile, contrary, critical, and aggressive behaviors directed at me, especially in my years upfront as a female corporate trainer in many toxic organizational cultures.

I often found that they were compromised in some way by their personal and family needs and values, their assumptions and beliefs about themselves and their performance at work, poor physical and mental health, and/or a lack of emotional well-being. Any one of these factors made them self-protective, leading to either overt aggression toward others, passive avoidance of conflict, or an unconscious refusal to engage in thoughtful dissent and disagreement because they did not want to be perceived as hostile and argumentative.

All of these unconscious reactive responses inhibited them from unleashing their creative thinking and innovative potential. 

This blog explores the power of unleashing creative thinking and innovation potential through supporting people to thoughtfully dissent and disagree – by using conflict as a catalyst for better decision-making, problem-solving, and strengthened collaboration and innovation – not as a barrier.

Unconscious reactive responses

This manifests as a neurologically challenging reactive response, as people’s brains are wired to defend and protect them to ensure their survival. These defensive responses are composed of fight/flight/freeze/fawn reactions and arise when people face what their neurology (the limbic system) perceives as a threat to their security, safety, or survival.

These reactions stem from past experiences and traumas that are often stored in people’s somatic memories. They become neurologically wired and embedded in people’s habitual ways of being unless they are noticed, labelled, accepted, acknowledged and owned. Until there is a safe holding space for this to happen, it will be impossible to unleash their creative thinking and innovation potential.

Safe holding spaces

Once a safe holding space is established, an oppositional person can be carefully and empathetically challenged, disputed, deviated from, and redirected towards more self-regulated, resourceful, and emotionally healthy states and new approaches. This involves bravely engaging them in thoughtful dissent and disagreement, despite being encased in a toxic organizational culture. Its about building permission, safety and trust to encourage creative thinking that unleashes a persons innovation potential.

Fight-flight-freeze and fawn responses

The amygdala is designed to detect threats and trigger the fight-flight-freeze response to help people survive

  •  A fight response involves standing our ground when we feel threatened, driven by anger, fear, and anxiety.
  •  A flight response entails moving away from or avoiding a situation to reduce painful feelings.
  •  A freeze response involves shutting down, feeling numb, or experiencing paralysis to reduce painful feelings, resulting in immobility.
  • A fawn response involves appeasing and placating others or seeking approval while neglecting the need to feel safe.  

Role of smart conflict, thoughtful dissent and disagreement

This is particularly evident in political and organizational contexts, where people are suffering from change fatigue and overwork. As a result, they unconsciously disengage from their work, families, and daily lives through a flight-or-freeze response, driven by burnout, the pursuit of external validation (a fawn response), or frustration and anger (usually a fight response). A combination of any or all of these largely unconscious but fully present reactive responses creates toxic organizational cultures, in which leaders’ behaviors are either passively or aggressively defensive in their attempts to meet people’s core security, safety, and survival needs. Leaders avoid encouraging or engaging in thoughtful dissent and disagreement that mobilizes people’s creative and critical thinking and unleashes their innovation potential.

The constraints and challenges of the pandemic, coupled with threats to people’s stability and the desire for certainty, also led many people in organizations to fear that their needs for security, safety, and survival would not, and could not, be met. These fears unconsciously intensified people’s defensiveness and reactivity, leading to immobilization through passivity, helplessness, hopelessness, powerlessness, disengagement, and detachment. This indicates a lack of emotional intelligence, largely due to the absence of initial self-regulation and self-leadership strategies.  It is easier and sometimes safer to be a victim and blame others for any negative, pessimistic, or painful feelings of shame, guilt, and embarrassment, resulting from competing commitments, value violations, thought distortions, and emotional dissociation.

These emotionally overwhelming and cognitively overloading factors are also accepted inhibitors to unleashing a person’s innovative potential, especially when they are unable to engage in thoughtful dissent and disagreement under the influence of a toxic organizational culture.

Making the shift

To support people to effectively shift this way of being and safely unleash their creative thinking and innovation potential:

It is crucial to develop and apply the generative discovery skillset to welcome dissent and thoughtful disagreement:

  • Notice: by being aware and attentively present to what is happening to, and within the person, neurologically and physiologically, emotionally, cognitively and physically.
  • Disrupt: by being curious and safely asking open, explorative discovery questions, and by listening carefully to hear and notice what is really going on for them.
  • Dispute: by safely summarizing and challenging their assumptions, perceptions and perspectives, asking evocative and provocative questions that encourage contrary thinking, diversity of thought, differences and constructive disagreement.
  • Deviate: by safely summarizing and eliciting a mindset flip or an agility shift in the oppositional person, directing their creative energy towards constructive behaviors that deliver a positive outcome.

This enables people to redirect their emotional energy and move away from unresourceful internal thought patterns and distortions. It also encourages them to open their minds to thoughtful dissent and disagreement, allowing them to think differently and enter creative and innovative realms. 

This is impossible when toxic organizational cultures force people to hide behind conventional, rigid, and closed minds that won’t allow them to rock the boat and be, think and act differently by intentionally using conflict constructively by embracing dissent and thoughtful disagreement 

At the same time, it’s crucial to safely, empathically and compassionately evoke and provoke an opening of people’s hearts by purposefully and meaningfully aligning their needs and values, so that the change motivates them to change meaningfully and purposefully. This creates the safe holding space that allows them to let go of the need to be in control and be open-willed, unleashing their creative thinking and innovation potential to make the shift to the creative and innovative realms.

Empowering people and teams to redirect their emotional energy towards opening their minds to thoughtful dissent and disagreement allows them to handle hard conversations with constructive and creative intent.

Welcoming dissent and thoughtful disagreement involves daring yourself and others to be and think differently. Being able to think creatively maximize a person or a teams innovation potential, unleashes their human ingenuity in the age of AI, and mobilizes their collective intelligence to lead, manage, or implement constructive and sustainable change.

Leveraging constructive conflict, dissent and thoughtful disagreement unleashes people’s creative thinking and innovation potential and is a necessary part of enabling AI, digital transformation and innovation initiatives to succeed in uncertain and disruptive times.

Find out more about our work at ImagineNation™ and The Start-Up Game.™ Discover our collective learning products and tools that can be customized as playful bespoke corporate learning programs. Our blended and transformational change and learning programs provide a deep understanding of the language, principles, and applications of an ecosystem-focused, human-centric approach and emergent structure (Theory U) to innovation and entrepreneurship. It will also upskill people and teams, developing their future fitness within your unique digital transformation and innovation initiatives. Please find out more about our products and tools.

Image Credit: Gemini

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AI Will Create a More Human Future, Not a Less Human One

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An AI Soft Landing Scenario

AI Soft Landing Scenario
by Braden Kelley and Art Inteligencia

What If the Future Gets More Human?

We spend a remarkable amount of time rehearsing the wrong ending.

In one popular story, artificial intelligence hollows out work, flattens craft, and leaves people performing the emotional leftovers of automation. That is a hard landing: humans demoted by systems that do more of everything, including the parts of work that used to make us feel useful.

There is another future available to us, what I call an AI soft landing. In that future, organizations and societies deliberately design AI to absorb fragmentation, acceleration, and low-judgment transaction. What returns to humans is not emptiness. What returns is depth: larger blocks of time for insight, empathy, decision making, direction setting, problem definition, creativity, and collaboration. The future becomes more human, not less, because human attention is finally reserved for human work.

This is not a naive techno-optimism. Soft landings are designed. Hard landings arrive when efficiency is the only value on the dashboard.

The Hidden Enemy Was Never “Work.” It Was Fragmentation.

Most knowledge work did not become less meaningful because people stopped caring. It became less meaningful because attention was diced into tickets, pings, updates, status rituals, and micro-approvals. We mistook motion for progress and responsiveness for value.

Task switching is expensive. Every context shift asks the brain to unload one problem and reload another. Multiply that by a day of chats, forms, triage, and administrative glue work, and you get a workforce that is always “on” and rarely deep. Strategic thinking does not fail only for lack of talent. It fails for lack of contiguous time.

AI’s first gift, if we use it well, is not genius on demand. It is fewer interrupted minutes. When drafting, scheduling, summarizing, searching, classifying, routing, and first-pass analysis get accelerated or handled, the calendar can stop looking like confetti. Bigger time blocks reappear. And bigger blocks are the raw material of original insight.

AI Future of Work

What Humans Should Own in a Soft Landing

A soft landing is not humans “using AI better.” It is a clear division of cognitive labor, one that protects the uniquely human contribution instead of competing with the machine on volume.

In a more human future, people spend more of their capacity on:

  • Insight development — connecting weak signals into meaning, not merely producing more output
  • Empathy — understanding stakes, dignity, and lived context that no dashboard fully captures
  • Decision making — choosing under uncertainty with values, tradeoffs, and accountability
  • Direction setting — naming where we are going and why it is worth the journey
  • Problem definition — asking better questions before rushing to automated answers
  • Creativity — combining perspectives in ways that are novel, useful, and humanly resonant
  • Collaboration — building trust, resolving conflict, and making progress together

Notice what is missing from that list: being the fastest typist in the room. Soft landing excellence is not measured in tokens per minute. It is measured in clarity per hour — and in whether people leave interactions more capable, more trusted, and more oriented than before.

From Transactional Lives to Strategic Ones

When small tasks expand to fill the day, even senior roles become transactional. Leaders spend their best hours approving instead of directing, reacting instead of sensing, facilitating meetings about work rather than doing the work of judgment.

AI can reverse that inversion, but only if organizations stop using every efficiency gain to stuff more micro-tasks into the same damaged attention budget. Saving ten minutes and immediately filling them with ten more interruptions is not transformation. It is denser exhaustion.

The soft landing asks a different operating question: What human capability do we want more of, now that machines can carry more of the glue?

If the answer is “more throughput at any cost,” you will automate people into thinner slices of busyness. If the answer is “more strategic quality, better problem framing, deeper customer and employee understanding,” AI becomes a scaffold for human depth. Less task switching. More deliberate thinking. Fewer performative updates. More real collaboration around decisions that matter.

AI Human Endeavors

How Leaders Design a Soft Landing (Instead of Hoping for One)

Human-centered change makes soft landings practical. A few design moves matter more than tool catalogs:

  1. Automate the glue, not the judgment. Route AI toward fragmentation: search, draft, summarize, schedule, classify, prepare. Keep humans responsible for choices with ethical, relational, or strategic consequence.
  2. Protect deep-work blocks as policy, not privilege. If AI creates capacity, calendar culture must not immediately reclaim it for more meetings.
  3. Redefine roles around human endeavors. Job descriptions should emphasize insight, empathy, problem definition, and direction — not inbox velocity as a proxy for value.
  4. Measure success in human outcomes. Track decision quality, customer trust, employee agency, and innovation usefulness — not only cost per interaction.
  5. Teach the craft of better questions. In an AI-rich world, problem definition becomes a core leadership skill. Bad prompts and bad frames still produce confident nonsense.
  6. Build collaboration for synthesis, not status. Use reclaimed time for cross-functional sense-making, not another dashboard review theater.

This is experience design for the future of work: design the system so people can be fully human on purpose.

The Choice Ahead

Futurology is not prediction cosplay. It is responsibility with a longer horizon.

We can use AI to compress people into ever-faster transaction machines. Or we can use it to return something modern work has been quietly stealing: the ability to think, feel, decide, and create with integrity.

The soft landing is the second path, a future where machines handle more of the small so humans can do more of the meaningful. Where strategy is less of a slide ritual and more of a practiced habit. Where customer and employee experience improve not only because algorithms personalize, but because people finally have the attention required for empathy and judgment.

A more human future will not arrive by accident. It will be designed by leaders who refuse to confuse automation with progress, and who insist that the best use of artificial intelligence is the expansion of human capacity where it still matters most.

Frequently Asked Questions

What is an AI soft landing?

An AI soft landing is a future in which artificial intelligence absorbs fragmented, transactional tasks so humans can spend more time on deeper endeavors — insight, empathy, decision making, direction setting, problem definition, creativity, and collaboration — making work more human rather than less.

How does AI reduce task switching at work?

AI can handle or accelerate small tasks such as drafting, summarizing, searching, scheduling, classifying, and routing. When organizations protect the time this frees, instead of immediately filling it with more interruptions, people gain larger blocks for strategic thinking and higher-quality collaboration.

What should leaders do to make the future more human with AI?

Leaders should automate glue work rather than human judgment, protect deep-work capacity as policy, redesign roles around human endeavors, measure human outcomes as well as efficiency, invest in better problem definition, and use reclaimed time for real collaboration and decision quality — not denser busyness.

Image Credits: Cursor

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

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10 Ways to Build Customer Trust in Customer Experience

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10 Ways to Build Customer Trust in Customer Experience

GUEST POST from Shep Hyken

This article answers the question: Are organizations not only paying attention to the feedback customers give but also to the feedback they unintentionally withhold?

In the past few months, I’ve been writing and speaking about how trust fits into the customer experience. Trust is earned, and once earned, it results in a customer who has confidence to keep doing business with you. I created a metric, the Customer Confidence Score (CCS), to measure how much a customer trusts you. So, let’s say the customer gives you a 10 on a scale of 1-10. Why do they give you that perfect score? Here are ten reasons why:

  1. You Keep Your Promise: This is simple. You do what you say you will do, and always when you say you will.
  2. Fixing and Owning Mistakes: You don’t make excuses and blame others. You simply focus on fixing whatever needs fixing.
  3. Transparency: There are no surprises, such as hidden fees or rules hidden in small print.
  4. You Protect Your Customer’s Data: Your customer’s privacy and security aren’t negotiable. How the customer’s information and data are protected and how breaches are handled will add to your customer’s trust. Customers must know you guard their information.
  5. You Show Respect: Treat your customers with dignity, respect, and appreciation. This builds trust.
  6. You Embrace Feedback: Your customers know their voice matters. You listen and act on their feedback, and, just as important, you acknowledge them for sharing it.
  7. You Give Back: A company that has a social cause or gives back to the community enjoys more trust than companies that don’t.
  8. You Don’t Take Advantage of Customers: Your customers never feel manipulated by sales tactics, small print, or anything that makes them feel uncomfortable or taken advantage of.
  9. Consistency: When customers do business with you, they know what to expect.
  10. Ethics: This is non-negotiable. There should never be any question about your ethics.

Customer Trust Formula Cartoon

Bonus: Give the customer a great customer service experience. Our annual customer service and CX research found that 83% of customers said that a good experience increases their trust in the person or company they are doing business with.

Trust is more than a business strategy. It’s a promise you keep every day. It is part of your company’s DNA. When customers trust you, they believe in you. They become your fans, your evangelists, and your best source of growth. Earning trust isn’t about one big moment. It’s built over a period of time when your customers know their experience is consistent, you’ll keep your promise, and you’ll do what’s right. Do that and your customers will say, “I’ll be back!”

Special Bonus: If you want a copy of a short eBook I created on the Customer Confidence Score, go to www.Hyken.com/customer-confidence-score.

Image Credits: Gemini

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A Tale of Two Narratives on Polarization

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A Tale of Two Narratives on Polarization

GUEST POST from Geoffrey Moore

In a time of increasing polarization, amplified by social media and exacerbated by malicious actors, we all need to deepen our understanding of just what we are into. Polarization, as I described in a previous blog on this subject, is best understood as an artifact of people binding their identities to explanatory narratives that validate their experience of the world, especially those experiences that activate their deepest fears. Binding to narrative per se is fundamental to both psychological and social stability, and in that context, it is natural and healthy. But when the narrative is being deliberately corrupted in order to manipulate public opinion, it fosters increasingly antagonistic relationships, dehumanizing the antagonists and inflaming the protagonists, both of which encourage us to treat fellow human beings as targets for marginalization, incarceration, or elimination.

In contemporary culture, there are two framing narratives that are driving this kind of polarization (and let me give shout out to Tangle for calling them to my attention):

  1. Civilization vs the Barbarians. In this narrative, “we” are the defenders of what is good, noble, and sacred in human culture, and “they” are agents of evil, degradation, and blasphemy. Thus, “we” can consider ourselves exempt from ethical accountability in our actions against them because “they” are threatening the very foundation of ethics itself.
  2. Oppressed vs the Oppressors. In this narrative, “we” are the victims of political, social, and economic exploitation by “them,” an overclass that has acquired a disproportionate share of power, wealth, and entitlements illegitimately at our expense. Thus, “we” can consider ourselves exempt from ethical accountability in our actions against them because “they” have unethically disenfranchised us.

Both narratives can be legitimate under extreme conditions, but each also lends itself to inflammatory purposes as well. Historically, the role of news reporting has been to help us distinguish between these two states. What is disgraceful about today’s media is that major broadcast networks, as well as previously highly respected publications, have not just abandoned this role but are actively engaged in subverting it. Let’s look a little more closely at what they are up to.

Civilization vs the Barbarians

This is the narrative framework that underlies Israel’s stance about its war with Hamas. It is also the one the US used to justify its post-9/11 actions against both Iraq and Isis. In both instances, provoked by starkly violent surprise attacks against purely civilian targets, outrage and righteous indignation fueled a demand for massive retaliation. There was simply no room for acknowledging any mitigating circumstances, any possible responsibility for creating the conditions that might have led to the terrorist attacks, or any accountability for subsequent acts of retributive retaliation regardless of how appalling they, in turn, might have been.

Now, given the extremity of the provocations, it is hard to see how any of this could have been avoided. But the civilization-vs-barbarians narrative is being used much more broadly in contemporary political discourse to address concerns that are much less extreme, including the following:

  • Right-wing outrage over illegal immigration
  • Left-wing outrage over anti-abortion legislation
  • Right-wing outrage over students demonstrating over the war in Gaza
  • Left-wing outrage over climate change deriders
  • Right-wing outrage over DEI initiatives
  • Left-wing outrage over 2020 election deniers.
  • Right-wing outrage over atheism
  • Left-wing outrage over book-banning

The key term here, in case you missed it, is outrage. Outrage uses righteousness to legitimize an explosion of anger against a community-sanctioned target. But the roots of that anger are not in the object of its attention. They are in the subject that has been carrying that burden around internally and who has now found a socially acceptable way to release it. And don’t think this applies just to “other people.” No one (except maybe a saint) is exempt here. You and I are as subject to the power of narratives as anyone else—it is only the trigger narratives themselves that separate us.

Look back over the bullet points above. Each of them is encased in a narrative, be it based on fact or urban legend. We should not be naïve about the power of these narratives to shape public opinion and influence elections. Psychologically, they play upon some of our deepest fears and then offer us a protective shield that is both internally coherent and externally impenetrable. That’s what makes the civilization-vs-barbarians narrative such a powerful political tool.

Oppressed vs the Oppressors

This is the narrative framework that underlies US college student protests in support of the Palestinians and against Israel’s sustained offensive in the Gaza Strip, as well as NATO support for the Ukraine and US support for Taiwan. Inside the US, it underpins support for the homeless, defunding of the police, and decriminalization of drug use. In each case, in order to relieve the debilitating conditions these communities are living under, the narrative calls for a radical change in the status quo, including a willingness to deprioritize legal justice in order to achieve social justice.

There are two separate audiences this narrative seeks to engage. Ostensibly, it is the oppressed themselves, but this can be misleading. Under exceptional circumstances, it is true that such narratives can trigger a revolution of the oppressed, but more commonly, these folks are in no position to take action on their own behalf. The far more frequent audience is people of means who have the power to take action and who empathize with the cause. This results in two kinds of calls to action—a revolutionary path, led by the oppressed, which seeks to overthrow the oppressors through violent means, and a liberal path, led by the empathizers, which seeks reform by working within the system.

Although we associate the oppressed-vs-the-oppressors narrative primarily with the left, we should note that the far right is leveraging it as well, as witnessed by the following widely held claims:

  • The woke liberal establishment is imposing socialist agendas around climate change and DEI on the oppressed white middle class.
  • Parental rights are under attack, threatened by liberal ideologies that have taken over public schools.
  • The 2020 election was rigged by Democrats, and Republicans, therefore, need not accept the results of the 2024 election because it also could be rigged.
  • Donald Trump did not get a fair trial because it, too, was rigged.
  • (And at the far right) the tyranny of the Deep State is so oppressive it warrants patriotic citizens taking up arms and shedding blood.

The Implications

To sum up, both political parties are using both narratives, but in very different contexts.

  • US Right: “Oppressors are the woke liberal establishment imposing socialist agendas around climate change and DEI on the oppressed white middle class.”
  • US Right: “Barbarians are the illegal immigrants seeking to invade our country and take over our democracy by outnumbering the civilized native white citizenry.”
  • US Left: “Oppressors are the conservative capitalist establishment imposing unjust requirements on disadvantaged populations, including illegal immigrants, the homeless, and the addicted.”
  • US Left: “Barbarians are the far-right politicians and pundits undermining the rule of law with fake news and demagogic rhetoric to block reproductive rights, equal opportunity programs, and climate change initiatives.”

Any attempt to argue people off of any of these positions is almost certain to fail, not because the arguments that support them are especially persuasive, but because people have bound their identities to them so tightly that they cannot break with them. As part of this binding, society self-segregates into “Us” and “Them,” each with its own amplifying media sources, its own signals of solidarity, its own righteous indignation, its own contempt for the other side.

Given all that, what could anyone seeking a better way possibly do? That is a question for a future blog post, one that is still very much in the works. For now, we should just note when these narratives are being used in corrupt ways to legitimize illegitimate claims and do our best to detach ourselves from them.

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

— Image credit: Pixabay

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Surveys Are Collapsing

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Conversational and Agentic VoC is How Loyalty Gets Heard

Conversational and Agentic VoC is How Loyalty Gets Heard

by Braden Kelley and Art Inteligencia

The Quiet Collapse of the Survey Layer

Something uncomfortable is happening inside customer experience programs that still treat the survey as the source of truth. Response rates are falling — sometimes sharply — even when the questionnaire itself barely changes. The invitations still go out. The dashboards still refresh. The air getting thinner is the percentage of customers willing to talk to a form.

This is not the death of listening. It is the collapse of a layer: the assumption that loyalty, satisfaction, and experience quality can be reliably extracted on demand through static instruments. Net Promoter Score is not vanishing overnight. Forms are not obsolete tomorrow morning. But both are being demoted — from verdict to signal, from system of record to starting point.

Organizations that built governance, bonuses, and “voice of the customer” theater almost entirely on survey completion are discovering a hard truth of human-centered change: when the method stops matching how people communicate, the method stops producing wisdom. You can still report a number. You just cannot pretend it represents the relationship.

The urgent question for innovators is not how to squeeze three more points of response rate out of a dying habit. It is how to hear customers in the ways they already speak — and how to turn that listening into action before loyalty quietly leaves.

Why People Stopped Talking to Forms

People did not become less opinionated. They became less willing to perform unpaid labor for brands that ask without reciprocating.

Survey fatigue is real, but it is only the surface. Timing is often wrong — a form arrives after the emotional moment has passed, or in the middle of a busy day when the only honest answer is delete. Reciprocity is weak: customers complete the ritual and see no change, so the next invitation feels like noise. Channel mismatch is growing: people already live in chat, voice, messaging, and short conversational bursts, while VoC programs still insist on a clipboard with radio buttons.

Underneath the mechanics sits an emotional job. Feedback, at its best, is a bid to feel heard. A form rarely delivers that feeling. It flattens story into score, urgency into scale, and dignity into “additional comments (optional).” When the experience of giving feedback is itself a poor experience, silence becomes rational.

Human-centered leaders should treat declining response as diagnostic data. Customers are telling you — by not answering — that your listening design is out of date.

From Scorekeeping to Sense-Making

Traditional VoC optimized for scorekeeping: capture a metric, trend it, threshold it, celebrate or panic. Sense-making asks a different question: What is changing in the lived experience, and why?

In a post-survey-dominant world, unstructured signal matters more — conversations, call notes, chat transcripts, reviews, social fragments, support themes, behavioral break points. AI makes synthesis of that mess newly practical. That does not make the score useless. It makes idolatry of the score dangerous.

The “why” can no longer be an afterthought parked in an open text field that nobody has time to read. The why is the product of modern listening. Scores become navigation lights. Narratives, patterns, and emotions become the map.

This shift also changes operating rhythm. Quarterly report theater gives way to continuous closed loops: hear, understand, act, confirm. Loyalty intelligence is less a research project and more an always-on sense-making system — still human-governed, still ethically bounded, but finally matched to the speed at which experience actually breaks.

Conversational VoC: Feedback as Dialogue

Conversational VoC replaces the clipboard with a dialogue. Instead of forcing every customer through the same static path, listening adapts — in the moment, in the channel, and in response to what the person just said.

That can look like a short adaptive chat after a key journey step, a voice interview that follows curiosity instead of a rigid script, a messaging thread that asks one good question and then the next logical one, or a human interview amplified by better prompts and synthesis. The common design principle is simple: treat feedback as conversation, not compliance.

Dialogue earns what forms forfeit. It can hold emotion without collapsing it into a single digit. It can clarify ambiguity in real time. It can meet people where they already are speaking. And it can make reciprocity visible — “we heard you, here is what happens next” — which is how listening becomes trust rather than extraction.

Done poorly, conversational VoC is just a survey wearing a chatbot costume. Done well, it is experience design applied to insight itself: respectful of time, responsive to context, and worthy of the story a customer is willing to share.

Agentic Listening: When Insight Can Act

The next leap is agentic listening: systems that do not only collect and classify, but can route, summarize, prioritize, trigger recovery, and help close the loop across teams. Insight stops dying in a dashboard and starts moving work.

This is powerful — and easy to get wrong. An agent that escalates a frustrated customer to a human with full context is care at scale. An agent that silently profiles, nudges, or “manages” sentiment without consent is surveillance with a CX badge. Human-centered innovation draws that line in the architecture, not in the press release.

Design stakes for agentic VoC

  • Consent and clarity — people should understand when listening is active and how their words will be used.
  • Privacy and minimization — collect what you need for learning and recovery, not everything you can.
  • Escalation with dignity — automation should accelerate help, not trap emotion in a loop.
  • Action accountability — if the system can trigger work, someone must own whether that work actually improved the experience.

Agentic VoC is not a replacement for human judgment. It is orchestration for listening: machines handle volume and routing; people handle meaning, ethics, and relationship repair. The brands that win will be the ones whose listening systems can act — and whose customers still feel respected while they do.

A Human-Centered Playbook for the Post-Survey Era

You do not need to burn the survey. You need to dethrone it. Here is a practical path.

  • Keep scores as signals, not idols. Use them to notice change; use conversations and behavior to explain it.
  • Build conversational intake at moments that matter. Short, adaptive, channel-native dialogues beat long retrospective forms.
  • Unify experience data. Connect feedback, journeys, and operational reality so insight is not stranded in a research silo.
  • Close loops where customers can feel them. Private recovery for individuals; visible improvement for patterns. Reciprocity is the antidote to silence.
  • Measure whether people feel heard — and whether action followed. Listening quality is an experience metric, not only a research metric.
  • Govern agentic listening for care. Decision rights, consent, escalation, and audit trails before autonomy scales.

Futurology in customer experience is often sold as more instrumentation. The deeper shift is more humane instrumentation: listening that fits human communication, sense-making that honors story, and systems that can act without making people feel managed.

Surveys are collapsing as the center of gravity. Conversational and agentic VoC are how loyalty gets heard again — not as a quarterly score, but as a living relationship that organizations are finally designed to understand.

Frequently Asked Questions

Why are customer survey response rates declining?

Response rates are falling because of survey fatigue, poor timing, weak reciprocity when feedback leads to no visible change, and a mismatch with how people already communicate through chat, voice, and messaging. Many customers still have opinions — they are less willing to share them through static forms.

What is conversational VoC?

Conversational voice of the customer (VoC) gathers feedback through adaptive dialogue — such as chat, voice, or messaging — rather than fixed questionnaires. It follows context and emotion in the moment, making customers more likely to feel heard and producing richer insight into the why behind experience scores.

What is agentic VoC and how does it differ from surveys?

Agentic VoC uses AI systems that can not only collect and analyze feedback but also route issues, trigger recovery, summarize themes, and help close the loop. Unlike surveys that mainly capture scores after the fact, agentic listening turns insight into action — when governed with consent, privacy, and human escalation.

Image credits: Cursor

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

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Why So Much Bullshit?

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Why So Much Bullshit?

GUEST POST from Greg Satell

Pretty much everywhere you look, you’ll find bullshit. We are constantly bombarded with politicians and “experts “on TV, at conferences and on social media, spouting bullshit. An economist would tell you that it is simply impossible for so much bullshit to exist, because the market values truth, but of course that’s bullshit.

One possible reason that there is so much bullshit in the world is that there are so many bullshitters. Yet that explanation has a critical flaw. People spouting bullshit are, in most cases, completely sincere. They believe that they are truth tellers, uncovering and sharing critical wisdoms that add value and meaning to our lives.

In his famous essay, On Bullshit, philosopher Harry Frankfurt makes the case that “bullshit is a greater enemy of the truth than lies are,” because liars need to actually ascertain the truth to misrepresent it. Bullshitters, on the other hand, show complete disregard for facts. I would argue, however, that’s only half the story. We bullshit because it serves a crucial purpose.

What Do We Really Think?

In February 2015, Cecilia Bleasdale, took a photograph of a black and blue dress she intended to wear at her daughter Grace’s wedding. Yet when she sent a photo of it, her daughter told her that the dress was white and gold. Unable to come to an agreement, Grace posted the dress on Facebook and it became an Internet sensation. The world split into two camps: black & blue vs. white & gold. Each side sure the other side was crazy!

We like to think that we see things how they really are, but that’s not really true. Our senses react to stimuli, such as light refracting off of objects like a computer screen, and our brains augment those perceptions to form full images, based on our past experiences. As we accumulate more experiences, pathways in our brains, called synapses, begin to form.

As we add new experiences, our synaptic pathways strengthen and shape our perceptions. A painter, for example, will perceive a flower very differently than a botanist and both will notice things that most of us would not. A recent study found that even for a concept as simple as a penguin, we all have very different ideas in our heads.

On rare occasions, like the explosion of the dress meme, we become alerted to the fact that we are all walking around with very different ideas in our heads. Most of the time, however, we just go about our business and assume that everybody else sees what we see and hears what we hear. It is possible to have entire conversations with people we know well and then walk away with completely different notions of what was said, without ever realizing it.

Cogito Ergo Sum

As an accomplished mathematician, René Descartes had a hard time accepting the fact that our perceptions are so malleable. He pointed out that when you see a stick half submerged in a glass of water, it appears to be bent, but outside it becomes clear that it is not. So which is really true? Maddening!

That’s what set Descartes on his rationalist project to build a base of knowledge purely on logic, without need to rely on perceptions. The first principle he came up with was cogito ergo sum, or “I think, therefore I am.” He intended that to be the foundation of a much more elaborate structure, but was never actually able to establish anything of importance without some reference to perceptions, which we know are faulty.

Still, the basic notion that our identity is wrapped up in our ideas gets to the core of who we are as humans. That’s why when we first meet people they are likely to tell us things they think, because they want us to know who they are. It is also why the dress became such a huge Internet sensation. Black & blue vs. white & gold became more than our perceptions of a photo, but part of our identities. You were either on one team or the other.

Once we understand the link between identity and ideas, we can begin to see where all the bullshit starts. Given how big, messy and confusing the world is, we know comparatively little about most subjects. Yet we we need to think something in order to project an identity. So we grab explanations where we can, often developed from past perceptions whether those are relevant and valid or not.

Group Identity, Polarization And Purity Spirals

In The Righteous Mind, social psychologist Jonathan Haidt describes our rational mind as kind of an internal PR department. Once our brains pick up bullshit, we feel compelled to build a narrative around it, telling ourselves that we arrived at our conclusions by an objective weighing of the evidence. We also look to others to confirm our beliefs.

So we go out in search of people who believe the same bullshit that we do. We read the same stuff, attend the same conferences and socialize in the same places, making sure our internal PR departments are coordinating and updating the story so that it stays coherent. We begin to identify not only with the views, but also with the fellow travelers that also hold them.

Decades of research has shown that we will conform to the opinions of those around us and that the effect extends to three degrees of social distance. So it is not only those we know well, but even the friends of our friend’s friends—people we don’t even know—have a deep and pervasive effect on the bullshit we believe.

More recent research at MIT looked into how we share our bullshit with others. What they found was that when we’re surrounded by people who think like us, we share bullshit more freely because we don’t expect to be rebuked. We’re also less likely to check our facts, because we know that those we are sharing with will be less likely to inspect it themselves.

In How Minds Change, science reporter David McRaney explains that when people leave of a religious cult or conspiracy theory group, it is usually preceded by a change in social networks. As it turns out, to free ourselves from a particular brand of bullshit, we need to break free of that particular brand of bullshitters.

What Do You Think You Know And Why Do You Think You Know It?

We all bullshit. And not just occasionally, either, but constantly. The simple fact is that it takes enormous time, energy and focus to attain a significant level of expertise in even a narrow field. So most of the things we encounter we know relatively little about. We either abstain from participating in the discussion or bullshit our way through it.

We’re willing to accept a certain amount of bullshit in our lives. Scientific frameworks like The elaboration likelihood model (ELM) and the heuristic-systematic model (HSM) explain that for low involvement areas, we actually prefer low information arguments with emotive content over more detailed explanations.

Most of all though, we bullshit to protect our identities, both individual and collective. It is through our beliefs that we connect with others, build communities and engage in shared purpose. It’s an equation that, for the most part, works very well. We engage in bullshit, so that we can do things together that matter, that make a difference in our lives and in others’.

Yet every once in a while we need to take a more disciplined approach. A natural disaster occurs, a pandemic arises or a crisis erupts in a far off place that we know little about and we need to show more humility about what we think we know and why we think we know it.

David McRaney suggests we can do this by giving a level of certainty—from 1-10—to ideas that we believe and ask ourselves why that level isn’t higher or lower. It’s an effective practice. Try it.

Because sometimes we get to a point where all the bullshit just has to stop.

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

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Thinking From No to Yes for Top Line Growth

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Top line growth strategies and product applicability frameworks

GUEST POST from Mike Shipulski

Bottom line growth is good, but top line growth is better. But if you want to grow the bottom line, ignore labor costs and reduce material costs. Labor cost is only 5-10% of product cost. Stop chasing it, and, instead, teach your design community to simplify the product so it uses fewer parts and design out the highest cost elements.

Where the factory creates bottom line growth, top line growth is generated in the market/customer domain. The best way I know to grow the top line is to broaden the applicability of your products and services. But, before you can broaden applicability, you’ve got to define applicability as it is. Define the limits of what your product can do – how much it can lift, how fast it can run a calculation and where it can be used. And for your service, define who can use it, where it can be used and what elements without customer involvement. And with the limits defined, you know where top line growth won’t come from.

Radical top line growth comes only when your products and services can be used in new applications. Sure, you can train your sales force to sell more of what you already have, but that runs out of gas soon enough. But, real top line growth comes when your services serve new customers in new ways. By definition, if you’re not trying to make your product work in new ways, you’re not going to achieve meaningful top line growth. And by definition, if you’re not creating new functionality for your services, you might as well be focusing on bottom line growth.

If your product couldn’t do it and now it can, you’re doing it right. If your service couldn’t be used by people that speak Chinese and now it can, you’re on your way. If your product couldn’t be used in applications without electricity and now it can, you’re on to something. If your service couldn’t run on a smartphone and now it can, well, you get the idea.

For the acid test, think no-to-yes.

If your product can’t work in application A, you can’t sell it to people who do that work. If your service can’t be used by visually impaired people, you’re not delivering value to them and they won’t buy it. Turning can’t into can is a big deal. But you’ve got to define can’t before you can turn it into can. If you want top line growth, take the time to define the limits of applicability.

No-to-yes is powerful because it creates clarity. It’s easy to know when a project will create no-to-yes functionality and when it won’t. And that makes it easy to stop projects that don’t deliver no-to-yes value and start projects that do.

No-to-yes is the key element of a compete-with-no-one approach to business.

Image credits: Pixabay

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Crossing the Chasm of Fear

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AI Soft Landing scenario — Leading People Through the Anxiety of Transformation and AI

LAST UPDATED: June 14, 2026 at 5:48 PM

Crossing the Chasm of Fear

by Braden Kelley and Art Inteligencia

The Hidden Friction in Modern Transformation

Change doesn’t fail because the technology is broken or the strategy is fundamentally flawed; it fails because organizations consistently underestimate the immense gravity of human fear.

We are living in an era of unprecedented, continuous disruption where the rapid, omnipresent rise of Artificial Intelligence (AI) has magnified workplace anxiety to an all-time high. This paradigm shift has fundamentally altered the conversation from standard operational “inertia” to a deep-seated, existential dread regarding professional relevance, personal autonomy, and long-term job security.

To build an agile, future-ready organization, leaders must stop merely trying to “manage” resistance and start actively dismantling fear. True transformation requires moving past rigid, top-down mandates to embrace genuine co-creation, psychological safety, and a commitment to human-centered design.

I. Mapping the Topography of Fear in the AI Era

To successfully guide an organization through a significant shift, leaders must first understand that the friction they encounter is rarely intellectual; it is emotional. In the wake of the generative AI revolution, traditional change management frameworks are proving insufficient precisely because they treat resistance as a logistical hurdle rather than a psychological defense mechanism.

The Shift from Traditional Resistance to Existential Anxiety

Standard change models were built for linear transitions — such as upgrading an ERP system or relocating an office — where the destination is clear and the skill gap is manageable. AI, however, introduces non-linear disruption. Employees are not just resisting a new tool; they are experiencing existential anxiety. The underlying fear is no longer “How do I use this software?” but rather “Does my expertise still matter?”

The Core Drivers of Workplace Fear

This widespread anxiety is fueled by three distinct, interconnected human dynamics:

  • Loss of Competence & Relevance: Professionals who have spent decades perfecting their craft suddenly face systems that can replicate aspects of their output in seconds. The fear of being rendered obsolete overnight leads to defensive behaviors and a reluctance to engage with new platforms.
  • Loss of Autonomy: Employees worry about losing the human element of decision-making. There is a deep-seated anxiety that their daily workflows will be dictated by black-box algorithms, reducing human agency to mere data entry and validation.
  • The “Black Box” Effect: Because advanced AI models operate behind complex neural layers, the lack of transparency breeds immediate distrust. When people do not understand how a technology arrives at a conclusion, they naturally default to worst-case scenario thinking regarding its intent and accuracy.

The Real Cost of Inaction

When leadership fails to recognize and mitigate these fears, the organization pays a heavy cultural tax. This friction rarely manifests as open defiance. Instead, it operations below the surface as:

  • Quiet Quitting: Disengagement driven by the belief that effort is futile in an automated future.
  • Malicious Compliance: Following instructions to the letter while ignoring obvious system errors, effectively letting the new technology fail to prove a point.
  • Organizational Paralysis: A total stall in innovation, as teams become too risk-averse to experiment with new digital capabilities.

II. Redefining the Approach: Moving from Mandates to Co-Creation

The traditional corporate playbook for technology deployment relies heavily on top-down enforcement. Executives select a platform, managers set a deployment date, and training sessions are scheduled to push the workforce into compliance. While this rigid approach might work for static software updates, it completely fractures when applied to cognitive, disruptive technologies like Artificial Intelligence. To cross the chasm of fear, leadership must fundamentally redefine how change is initiated.

The Failure of Top-Down Dictates

When an disruptive technology is thrust upon an organization from above, it triggers the corporate equivalent of an immune system response. Employees perceive the uninvited change as an existential threat to their routines and livelihoods. Pushing mandates down the organizational chart only hardens resistance, forcing anxiety underground and transforming potential advocates into silent saboteurs.

The Power of Participatory Innovation

The alternative to top-down friction is Participatory Innovation — the deliberate practice of shifting the narrative from “This is being done to you” to “You are building this with us.” True ecosystem agility requires flattening the hierarchy of contribution and inviting the entire workforce into the design process. Rather than treating front-line employees as passive recipients of change, organizations must treat them as active co-creators of their own future workflows.

This approach transforms the deployment strategy by:

  • Engaging front-line staff at the inception stage to identify real, daily friction points that AI can genuinely alleviate, rather than forcing technology where it doesn’t fit.
  • Utilizing cross-functional design sessions that break down legacy silos, allowing technical developers and domain experts to build tools in tandem.
  • Establishing iterative feedback loops that give employees a direct hand in shaping, tweaking, and refining the automated systems they are expected to use.

Lowering Resistance Through Shared Ownership

Human beings rarely destroy what they help build. When an employee looks at a newly integrated AI assistant or a redesigned digital workflow and recognizes their own insights, feedback, and domain expertise baked into the final product, the underlying psychological dynamic shifts instantly. The fear of the unknown is replaced by a powerful sense of pride of authorship, transforming potential resistance into proactive, self-sustaining adoption.

III. The Strategic Blueprint: Crossing the Chasm of Fear

Dismantling fear and establishing a culture of participatory innovation requires more than good intentions; it demands an operationalized, human-centered strategy. To successfully cross the chasm of anxiety and achieve meaningful adoption, leaders must execute a deliberate, multi-layered blueprint that prioritizes human experience alongside technical milestone delivery.

Step 1: Cultivate Psychological Safety First

Before introducing a single algorithmic tool, leadership must anchor the organizational culture in psychological safety. If employees believe that experimenting with AI or voicing skepticism will jeopardize their standing, they will retreat into defensive compliance.

  • Create dedicated, judgment-free forums where teams can openly discuss their anxieties, ask “naive” technical questions, and challenge assumptions without fear of retribution.
  • Frame the early stages of AI adoption as an iterative experiment rather than a high-stakes, zero-fault mandate. Normalize failure as a natural, necessary component of learning to collaborate with intelligent systems.

Step 2: Demystify the “Black Box”

Fear thrives in obscurity. When technology is shrouded in complex, dense jargon, employees default to worst-case scenario thinking. Crossing the chasm requires pulling back the curtain on how automated tools function.

  • Provide transparent, accessible education tailored to non-technical users. Demystify the data sources, logic, and operational boundaries of the AI models being deployed.
  • Shift the corporate narrative away from “automation as a replacement” and explicitly reframe it as “augmentation as a partner.” Clearly demonstrate how these tools can absorb repetitive cognitive drudgery, freeing individuals to focus on high-value, uniquely human tasks.

Step 3: Define New “Experience Level Measures” (XLMs)

Traditional change management focuses almost exclusively on cold Operational Measures—tracking system uptime, deployment timelines, software licenses, and output volume. To manage the human friction of transformation, organizations must measure what actually matters: the human experience of the transition.

  • Implement Experience Level Measures (XLMs) to actively track sentiment, cognitive friction, and confidence levels across the workforce during the rollout.
  • Establish an Experience Management Office (XMO). This cross-functional entity acts as the empathetic heartbeat of the transformation, monitoring XLMs in real time and intervening with support, tailored training, or process redesign when emotional friction spikes.

Step 4: Re-skilling with Dignity and Equity

True fairness in transformation means ensuring that the rewards of technological advancement are relative to the effort invested by the people keeping the organization running. If employees feel that upskilling only leads to their own displacement or unfair workloads, adoption will fail.

  • Demonstrate a visible, legally backed commitment to the long-term value of your human capital through robust, funded re-skilling pathways that dignify the worker’s career trajectory.
  • Align future organizational recognition, bonuses, and growth opportunities with equitable outcomes: ensure that the harder working individuals who lean into the challenge of adapting and mastering new tools receive the tangible rewards of that shared success.

IV. Activating the Ecosystem: Leveraging Multi-Dimensional Roles

Successfully steering an organization away from anxiety and toward sustainable innovation requires a diverse network of human capabilities. Relying solely on technical project managers or traditional IT leaders to drive adoption is a structural mistake; these roles are designed to optimize systems, not to heal a fractured human culture. To operationalize empathy and scale change, leadership must activate a multi-dimensional ecosystem of specialized roles.

Beyond the Project Manager

While project managers excel at tracking timelines, budgets, and deployment milestones, they rarely possess the specialized tools or bandwidth required to navigate deep-seated psychological friction. Orchestrating a human-centered transformation requires shifting the focus from managing tasks to nurturing human relationships. Organizations must look beyond standard job titles and intentionally cultivate specific archetypes designed to bridge the gap between human anxiety and technological capability.

The Right People in the Right Seats

To dismantle fear at every layer of the enterprise, leaders should identify, empower, and deploy three distinct operational archetypes across the transformation ecosystem:

  • The Evangelist: This role is responsible for crafting the overarching human narrative of the transformation. The Evangelist does not merely pitch the features of a new AI tool; they communicate the authentic “Why” behind the change. By generating real, unforced energy and painting a vivid picture of a more fulfilling, augmented future, they inspire teams to lift their heads above immediate anxieties and look toward the long-term horizon.
  • The Connector: Change rarely scales effectively through top-down mandates; it spreads horizontally through social proof and trusted networks. Connectors are the cross-functional linchpins who span legacy departmental boundaries. They excel at identifying grassroots wins in one pocket of the organization, translating those successes for other teams, and ensuring that insights, feedback, and shared resources flow seamlessly across the entire ecosystem.
  • The Coach: While Evangelists inspire groups and Connectors build bridges, the Coach works on the front lines of human emotion. Operating with high emotional intelligence, Coaches provide one-on-one empathy and guidance to individuals experiencing severe friction. They help employees navigate personal technical skill gaps, address specific career anxieties, and safely transition into new ways of working without losing their professional dignity.

Conclusion: The Ultimate Reward of a Human-Centered Future

Technology provides the raw capability, but human adoption provides the actual organizational value. As we navigate the complex, non-linear disruptions of the Artificial Intelligence era, it is becoming increasingly clear that the true competitive advantage does not belong to the enterprise with the largest budget or the most advanced algorithms. The future belongs to the organizations that can move their people past anxiety and into a state of shared purpose.

Crossing the chasm of fear requires leaders to abandon the outdated illusion of top-down control. By anchoring your transformation strategy in radical transparency, psychological safety, and participatory innovation, you transform a potentially threatening disruption into a collective opportunity. Measuring the journey through human-centric lenses like Experience Level Measures (XLMs) and deploying empathetic archetypes ensures that no one is left behind in the wake of progress.

Ultimately, when you design fear out of your corporate culture, you unlock the ultimate reward: an agile, resilient, and infinitely innovative workforce. By treating employees as respected co-creators of their digital future, you don’t just achieve a successful technology rollout — you build a human-centered ecosystem capable of thriving through any disruption the future brings.

Frequently Asked Questions

Why do traditional change management frameworks fail when introducing AI?
Traditional frameworks treat change as a linear, logistical hurdle focused on training and compliance. AI introduces non-linear disruption that triggers deep psychological and existential anxiety regarding job security, relevance, and loss of human autonomy. Overcoming this requires an empathy-driven, human-centered approach rather than top-down mandates.
What is Participatory Innovation and how does it reduce resistance?
Participatory Innovation is the practice of actively involving front-line employees in co-creating and designing their future workflows instead of pushing changes down from the executive level. Because human beings rarely destroy what they help build, this shared ownership transforms fear of the unknown into pride of authorship.
What are Experience Level Measures (XLMs) and why are they necessary?
While traditional operational measures track cold metrics like system uptime or deployment timelines, Experience Level Measures (XLMs) actively quantify human sentiment, cognitive friction, and adoption confidence. They are critical because technology only provides capability; human adoption is what actually unlocks organizational value.


Operationalize Organizational Empathy

Ready to Bridge the Gap Between Technology and Human Experience?

Technology only provides capability; human adoption creates the value. If you want to move past cold operational metrics and design fear out of your transformation, let’s connect. Get expert guidance on architecting impactful Experience Level Measures (XLMs) or establishing a dedicated Experience Management Office (XMO) tailored to your culture.

EDITOR’S NOTE: This is a visualization of but one possible future. I will be publishing other possible futures as they crystallize in my mind (or as you suggest them for me to explore).

Image credits: Google Gemini

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

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