Humans Don’t Have to Perform Every Task

Humans Don't Have to Perform Every Task

GUEST POST from Shep Hyken

There seems to be a lot of controversy and questions surrounding artificial intelligence (AI) being used to support customers. The customer experience can be enhanced with AI, but it can also derail and cause customers to head to the competition.

Last week, I wrote an article titled Just Because You Can Use AI, Doesn’t Mean You Should. The gist of the article was that while AI has impressive capabilities, there are situations in which human-to-human interaction is still preferred, even necessary, especially for complex, sensitive or emotionally charged customer issues.

However, there is a flip side. Sometimes AI is the smart thing to use, and eliminating human-to-human interaction actually creates a better customer experience. The point is that just because a human could handle a task doesn’t mean they should. 

Before we go further, keep in mind that even if AI should handle an issue, my customer service and customer experience (CX) research finds almost seven out of 10 customers (68%) prefer the phone. So, there are some customers who, regardless of how good AI is, will only talk to a live human being.

Here’s a reality: When a customer simply wants to check their account balance, reset a password, track a package or any other routine, simple task or request, they don’t need to talk to someone. What they really want, even if they don’t realize it, is fast, accurate information and a convenient experience.

The key is recognizing when customers value efficiency over engagement. Even with 68% of customers preferring the phone, they also want convenience and speed. And sometimes, the most convenient experience is one that eliminates unnecessary human interaction.

Smart companies are learning to use both strategically. They are finding a balance. They’re using AI for routine, transactional interactions while making live agents available for situations requiring judgement, creativity or empathy.

The goal isn’t to replace humans with AI. It’s to use each where they excel most. That sometimes means letting technology do what it can do best, even if a human could technically do the job. The customer experience improves when you match the right resource to the customers’ specific need.

That’s why I advocate pushing the digital, AI-infused experience for the right reasons but always – and I emphasize the word always – giving the customer an easy way to connect to a human and continue the conversation.

In the end, most customers don’t care whether their problem is solved by a human or AI. They just want it solved well.

Image credits: Google Gemini, Shep Hyken

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A New Era of Economic Warfare Arrives

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Is Your Company Prepared?

LAST UPDATED: January 9, 2026 at 3:55PM

A New Era of Economic Warfare Arrives

GUEST POST from Art Inteligencia

Economic warfare rarely announces itself. It embeds quietly into systems designed for trust, openness, and speed. By the time damage becomes visible, advantage has already shifted.

This new era of conflict is not defined by tanks or tariffs alone, but by the strategic exploitation of interdependence — where innovation ecosystems, supply chains, data flows, and cultural platforms become contested terrain.

The most effective economic attacks do not destroy systems outright. They drain them slowly enough to avoid response.

Weaponizing Openness

For decades, the United States has benefited from a research and innovation model grounded in openness, collaboration, and academic freedom. Those same qualities, however, have been repeatedly exploited.

Publicly documented prosecutions, investigations, and corporate disclosures describe coordinated efforts to extract intellectual property from American universities, national laboratories, and private companies through undisclosed affiliations, parallel research pipelines, and cyber-enabled theft.

This is not opportunistic theft. It is strategic harvesting.

When innovation can be copied faster than it can be created, openness becomes a liability instead of a strength.

Cyber Persistence as Economic Strategy

Cyber operations today prioritize persistence over spectacle. Continuous access to sensitive systems allows competitors to shortcut development cycles, underprice rivals, and anticipate strategic moves.

The goal is not disruption — it is advantage.

Skydio and Supply Chain Chokepoints

The experience of American drone manufacturer Skydio illustrates how economic pressure can be applied without direct confrontation.

After achieving leadership through autonomy and software-driven innovation rather than low-cost manufacturing, Skydio encountered pressure through access constraints tied to upstream supply chains.

This was a calculated attack on a successful American business. It serves as a stark reminder: if you depend on a potential adversary for your components, your success is only permitted as long as it doesn’t challenge their dominance. We must decouple our innovation from external control, or we will remain permanently vulnerable.

When supply chains are weaponized, markets no longer reward the best ideas — only the most protected ones.

Agricultural and Biological Vulnerabilities

Incidents involving the unauthorized movement of biological materials related to agriculture and bioscience highlight a critical blind spot. Food systems are economic infrastructure.

Crop blight, livestock disease, and agricultural disruption do not need to be dramatic to be devastating. They only need to be targeted, deniable, and difficult to attribute.

Pandemics and Systemic Shock

The origins of COVID-19 remain contested, with investigations examining both natural spillover and laboratory-associated scenarios. From an economic warfare perspective, attribution matters less than exposure.

The pandemic revealed how research opacity, delayed disclosure, and global interdependence can cascade into economic devastation on a scale rivaling major wars.

Resilience must be designed for uncertainty, not certainty.

The Attention Economy as Strategic Terrain and Algorithmic Narcotic

Platforms such as TikTok represent a new form of economic influence: large-scale behavioral shaping.

Regulatory and academic concerns focus on data governance, algorithmic amplification, and the psychological impact on youth attention, agency, and civic engagement.

TikTok is not just a social media app; it is a cognitive weapon. In China, the algorithm pushes “Douyin” users toward educational content, engineering, and national achievement. In America, the algorithm pushes our youth toward mindless consumption, social fragmentation, and addictive cycles that weaken the mental resilience of the next generation. This is an intentional weakening of our human capital. By controlling the narrative and the attention of 170 million Americans, American children are part of a massive experiment in psychological warfare, designed to ensure that the next generation of Americans is too distracted to lead and too divided to innovate.

Whether intentional or emergent, influence over attention increasingly translates into long-term economic leverage.

The Human Cost of Invisible Conflict

Economic warfare succeeds because its consequences unfold slowly: hollowed industries, lost startups, diminished trust, and weakened social cohesion.

True resilience is not built by reacting to attacks, but by redesigning systems so exploitation becomes expensive and contribution becomes the easiest path forward.

Conclusion

This is not a call for isolation or paranoia. It is a call for strategic maturity.

Openness without safeguards is not virtue — it is exposure. Innovation without resilience is not leadership — it is extraction.

The era of complacency must end. We must treat economic security as national security. This means securing our universities, diversifying our supply chains, and demanding transparency in our digital and biological interactions. We have the power to stoke our own innovation bonfire, but only if we are willing to protect it from those who wish to extinguish it.

The next era of competition will reward nations and companies that design systems where trust is earned, reciprocity is enforced, and long-term value creation is protected.

Frequently Asked Questions

What is economic warfare?

Economic warfare refers to the use of non-military tools — such as intellectual property extraction, cyber operations, supply chain control, and influence platforms — to weaken a rival’s economic position and long-term competitiveness.

Is China the only country using these tactics?

No. Many nations engage in forms of economic competition that blur into coercion. The concern highlighted here is about scale, coordination, and the systematic exploitation of open systems.

How should the United States respond?

By strengthening resilience rather than retreating from openness — protecting critical research, diversifying supply chains, aligning innovation policy with national strategy, and designing systems that reward contribution over extraction.

How should your company protect itself?

Companies should identify their critical knowledge assets, limit unnecessary exposure, diversify suppliers, strengthen cybersecurity, enforce disclosure and governance standards, and design partnerships that balance collaboration with protection. Resilience should be treated as a strategic capability, not a compliance exercise.

Image credits: Google Gemini

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Rearchitecting the Landscape of Knowledge Work

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Rearchitecting the Landscape of Knowledge Work

GUEST POST from Geoffrey A. Moore

One thing the pandemic made clear to everyone involved with the knowledge-work profession is that daily commuting was a ludicrously excessive tax on their time. The amount of work they were able to get done remotely clearly exceeded what they were getting done previously, and the reduction in stress was both welcome and productive. So, let’s be clear, there is no “going back to the office.” What is possible, on the other hand, is going forward to the office, and that is what we are going to discuss in this blog post.

The point is, we need to rethink the landscape of knowledge work—what work is best done where, and why. Let’s start with remote. Routine task work of the sort that a professional is expected to complete on their own is ideally suited to remote working. It requires no supervision to speak of and little engagement with others except at assigned checkpoints. Those checkpoints can be managed easily through video conferencing combined with collaboration-enabling software like Slack or Teams. Productivity commitments are monitored in terms of the quality and quantity of received work. This is game-changing for everyone involved, and we would be crazy to forsake these gains simply to comply with a return-to-the-office mandate.

That said, there are many good reasons still to want a return. Before we dig into them, however, let’s spend a moment on the bad reasons first. First among them is what we might call “boomer executive control needs”—a carry-over from the days of hierarchical management structures that to this day still run most of our bureaucracies. Implicit in this model is the notion that everyone needs supervision all the time. Let me just say that if that is the case in your knowledge-work organization, you are in big trouble, and mandating everyone to come back to the office is not going to fix it. The fix needed is workforce engagement, and that requires personal intervention, not systemic enforcement. Yes, you want to do this in person, and yes, the office is typically the right place to do so, but no, you don’t need everyone to be there all the time to do it.

This same caveat applies to other reasons why enterprises are mandating a return. Knowledge work benefits from social interactions with colleagues. You get to float ideas, hear about new developments, learn from observing others, and the like. It is all good, and you do need to be collocated to do it—just not every day. What is required instead is a new cadence. People need an established routine to know when they are expected to show up, one they can plan around far in advance. In short, we need the discipline of office attendance, we just want it to be more respectful of our remote work. In that light, a good place to start is a 60/40 split—your call as to which is which. But for the days that are in office, attendance is expected, not optional. To do anything else is to disrespect your colleagues and to put your personal convenience above the best interests of the enterprise that is funding you.

So much for coping with some of the bad reasons. Now let’s look into five good ones.

Customer-facing challenges. This includes sales, account management, and customer success (but not customer support or tech support). The point is, whenever things are up for grabs on the customer side, it takes a team to wrestle them down to earth, and the members of that team need to be in close communication to detect the signals, strategize the responses, and leverage each other’s relationships and expertise. You don’t get to say when this happens, so you have to show up every day ready to play (meaning 80/20 is probably a more effective in-office/out-of-office ratio).
Onboarding, team building, and M&A integration. Things can also be up for grabs inside your own organization, particularly when you are adding new people, building a new team (or turning around an old one), or integrating an acquisition. In these kinds of fluid situations, there is a ton of non-verbal communication, both to detect and to project, and there is simply no substitute for collocation. By contrast, career development, mentoring, and performance reviews are best conducted one-on-one, and here modern video conferencing with its high-definition visuals and zero-latency audio can actually induce a more focused conversation.
Mission-critical systems operations. This is just common sense—if the wheels start to come off, you do not want to lose time assembling the team. Cybersecurity attacks would be one good example. On the other hand, with proper IT infrastructure, routine system monitoring, and maintenance as well as standard end-user support can readily leverage remote expertise.
In-house incubations. It is possible to do a remote-only start-up if you have most of the team in place from the beginning, leveraging time in collocation at a prior company, especially if the talent you need is super-scarce and geographically dispersed.
But for public enterprises leveraging the Incubation Zone, as well as lines of business conducting nested incubation inside their own organizations, a cadence surrounding collocation is critical. The reason is that incubations call for agile decision-making, coordinated course corrections, fast failures, and even faster responses to them. You don’t have to be together every day—there is still plenty of individual knowledge work to be done, but you do need to keep in close formation, and that requires frequent unscripted connections.
Cross-functional programs and projects. These are simply impossible to do on a remote basis. There are too many new relationships that must be established, too many informal negotiations to get resources assigned, too many group sessions to get people aligned, and too much lobbying to get the additional support you need. This is especially true when the team is led by a middle manager who has no direct authority over the team members, only their managers’ commitment and their own good will.

So, what’s the best in-office/remote ratio for your organization?

You might try doing a high-level inventory of all the work you do, calling out for each workload which mode of working is preferable, and totaling it up to get a first cut. You can be sure that whatever you come up with will be wrong, but that’s OK because your next step will be to socialize it. Once you get enough fingerprints on it, you will go live with it, only to confirm it is still wrong, but now with a coalition of the willing to make it right, if only to make themselves look better.

Ain’t management fun?

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

Image Credit: Google Gemini

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The Keys to Changing Someone’s Mind

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The Keys to Changing Someone's Mind

GUEST POST from Greg Satell

When is the last time you changed your mind about anything substantial? Was it another person that convinced you or an unexpected experience that changed your perspective? What led you to stop seeing something one way and start seeing it in another? I will bet it does not happen often. We rarely change our minds.

Now think about how much time we spend trying to change other people’s minds. From sales pitches and political discussions, to what we are going to have for dinner and when the kids should go to bed, we put a lot of time and effort into shaping the opinions of others. Most of that is probably wasted.

The truth is that we cannot really change anyone’s mind. Only they can do that. Yet as David McRaney explains in his new book, How Minds Change, there are new techniques that can help us be more persuasive, but they don’t require brilliant sophistry or snappy rhetoric. They involve more listening than speaking, and understanding the context in which beliefs arise.

Why We Fail To Adapt

We don’t experience the world as it is, but through the context of earlier experiences. What we think of as knowledge is really connections in our brains called synapses which develop over time. These pathways strengthen as we use them and degrade when we do not. Or, as scientists who study these things like to put it, the neurons that fire together, wire together.

It’s not just our own experiences that shape us either. In fact, a series of famous experiments done at Swarthmore College in the 1950’s showed that we will conform to the opinions of those around us even if they are obviously wrong. More recent research suggests that this effect extends out to three degrees of influence, so it’s not just people we know personally, but the friends of our friends’ friends that shape how we see things.

Finally, there are often switching costs to changing our minds. Our opinions are rarely isolated thoughts, but form a basis for decisions. Once we change our minds, we need to change our actions and that can have consequences. We may need to change how we do our jobs, what we choose to buy, how we act towards others and, sometimes, who we choose to associate ourselves with.

In The Righteous Mind, social psychologist Jonathan Haidt makes the point that our beliefs become closely intertwined with our identity. They signal our inclusion in a particular “team.” That’s why contrary views can often feel like an attack. Rather than taking in new information we often feel the urge to lash out and silence the opposing voice.

Meeting The Mind Changing Threshold

As closely as we cling to our beliefs, sometimes we do change our minds. In one study that analyzed voting behavior, it was found that when up to 20% of the information that people were exposed to contradicted their beliefs, they dug in their heels and grew more certain. Beyond that, however, their resolve tended to weaken. The informational environment can deeply influence what people believe.

Their relationship to the subject matter is also important. The elaboration likelihood model (ELM) and the heuristic-systematic model (HSM) developed in the 1980s both suggest that we treat different topics in different ways. Some topics, such as those that are important to us professionally, we’re willing to invest time in exploring systematically. Others are more marginal to us and we will tend to look for shortcuts.

For example, if we are researching a business investment, we’ll want to gather facts from a variety of different sources and study them closely. On the other hand, if we’re trying to decide which craft beer to select from a large selection at a bar, we’ll rely on subtle cues such as packaging, how the beer is described or what we see others drinking.

If we want to change someone’s mind about something we need to understand their relationship to the subject matter. If they are heavily invested in it, they are unlikely to be swayed by superficial arguments. In fact, weak or purely emotive arguments may suggest to them that the opposite is true. At the same time, if someone is not very knowledgeable or motivated to learn about a topic, bogging them down with a lot of facts is likely to bore them.

Two Strategies For Persuasion

If you want to change somebody’s mind, you can follow two different kinds of approaches. The first, which can be called “topic denial”, argues the facts. The second, called “technique denial,” exposes flaws in reasoning. For example, if you want to convince a vaccine skeptic you can either cite scientific evidence or refute the form of the argument, such as pointing out that while there may be a minimal risk to taking a vaccine, the same could be said of aspirin.

While research shows that both approaches can be effective, we need to keep context in mind. If you are in a trustful environment, such as a professional or scientific setting, a fact-based topic rebuttal can often be effective. However, if you’re trying to talk your crazy uncle out of a conspiracy theory at Thanksgiving dinner, you may want to try a technique rebuttal.

In recent years a variety of methods, such as Deep Canvassing, Street Epistemology and the Change Conversation Pyramid have emerged as effective technique rebuttal methods. Interestingly, they don’t rely on any elaborate rhetorical flourishes, but rather listening empathetically, restating the opposing position in a way that shows we understand it, identifying common ground and exploring how they came to their conclusion.

The truth is that we can never truly change somebody’s mind. Only they can do that. All too often, we treat opinions as if they were artillery in a battle. Yet attacking someone’s beliefs is more likely to raise their defenses than to convince them that they are in error. Before we can convince anyone of anything, we need to first build an environment of safety and trust.

Let Empathy Be You Secret Weapon

When we want to change somebody’s minds, our first instinct is to confront their beliefs. We want to be warriors and fight for our position. Yet because people’s opinions are often a result of their experiences and social networks, countering their beliefs won’t feel to them like merely offering a different perspective, but as an attack on their identity and dignity.

That’s why we’re much better off listening and building rapport. That’s not always easy to do, because staying silent while somebody is voicing an opinion we don’t agree with can feel like a surrender. But it doesn’t have to be. In fact, if we can identify a shared value and a shared language in an opposing viewpoint, we have a powerful tool to argue our position.

The truth is that empathy isn’t absolution. In fact, it can be our secret weapon. We don’t have to agree with someone’s belief to internalize it. We all have a need to be recognized and when we take the time to hear someone out, we honor their dignity. That makes them much more willing to hear us out. Lasting change is always built on common ground.

At some point, we all need to decide if we want to make a point or make a difference. If we really care about change, we need to hold ourselves accountable to be effective messengers and express ourselves in terms that others are willing to accept. That doesn’t in any way mean we have to compromise. It simply means that we need to advocate effectively.

To do that, we need to care more about building shared purpose than we do about winning points.

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

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Why Meeting Icebreakers Matter

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Why Meeting Icebreakers Matter

GUEST POST from David Burkus

Icebreakers are not just games or frivolous activities. Many people have memories of cringeworthy and awkward games played under the pretense of “team building.” I was one of them. But the research on icebreakers is pretty clear. Icebreakers are powerful tools that can help teams find uncommon commonalities and build strong connections.

Icebreakers can be the key to unlocking a more collaborative, understanding, and high-performing team. However, the effectiveness of an icebreaker hinges on its relevance and comfort level. They should be personally meaningful and not make team members uncomfortable.

In this article, we’ll cover four such icebreakers for team meetings. They’re quick, and not cringe. Each of these icebreakers is designed to help teams connect, understand each other better, and perform at a higher level.

1. Energy Check

The Energy Check is an icebreaker that encourages team members to rate their energy level and discuss ways the team can support each other. This is done by having each team member rate their energy level on a scale of 1 to 5—with 1 being dead tired and 5 being energy to spare. Whatever the answer, the team can follow up with question about what they can do to support the person speaking. This opens up a conversation about ways the team can support each other and learn about each other’s challenges and weaknesses.

By encouraging open discussion about energy levels and support needs, this icebreaker fosters a culture of empathy and understanding within the team. It helps team members to understand that they are not alone in their struggles and that they can rely on their team for support. This can significantly improve team cohesion and performance.

2. Triple H

Triple H is an icebreaker that allows team members to share a hero, highlight, and hardship in their life or career. Each team member is asked to share a hero who inspires them, a highlight from their life or career, and a hardship they have faced. This not only allows team members to disclose personal preferences, values, and experiences, but also creates the opportunity to find uncommon commonalities and build bonds through shared experiences.

By sharing their heroes, highlights, and hardships, team members can gain a deeper understanding of each other’s motivations, achievements, and challenges. This can lead to increased empathy, respect, and cooperation within the team.

3. Defining Moment

Defining Moment is an icebreaker where team members share a defining moment that shaped who they are today. Think of it as a faster version of Triple H—one that just focuses on the highlight. Each team member is asked to share a significant event or experience in their life or career that has had a profound impact on them. This encourages team members to share something personally meaningful and helps find uncommon commonalities that are deeper and more personally meaningful.

By sharing their defining moments, team members can reveal aspects of their personality and values that may not be apparent in a professional setting. This can lead to increased understanding and respect among team members, fostering a more harmonious and productive team environment.

4. Three Snaps

Three Snaps is an icebreaker where team members share three meaningful photos from their camera roll. Each team member is asked to share three photos that are meaningful to them. This allows team members to share about themselves to the level they’re comfortable with and helps find commonalities and build connections through shared experiences and interests.

By sharing their photos, team members can give others a glimpse into their personal lives, interests, and experiences. This can lead to increased understanding and connection among team members, fostering a more cohesive and collaborative team environment.

These icebreakers, when used effectively, can be powerful tools for building a more connected, understanding, and high-performing team. They can help teams find uncommon commonalities, build strong connections, and understand each other better. In other words, these short, non-cringe icebreakers can help any team do its best work ever.

This article originally appeared on DavidBurkus.com

Image credit: Pexels

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Solving the AI Trust Imperative with Provenance

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The Digital Fingerprint

LAST UPDATED: January 5, 2026 at 3:33 PM

The Digital Fingerprint - Solving the Trust Imperative with Provenance

GUEST POST from Art Inteligencia

We are currently living in the artificial future of 2026, a world where the distinction between human-authored and AI-generated content has become practically invisible to the naked eye. In this era of agentic AI and high-fidelity synthetic media, we have moved past the initial awe of creation and into a far more complex phase: the Trust Imperative. As my friend Braden Kelley has frequently shared in his keynotes, innovation is change with impact, but if the impact is an erosion of truth, we are not innovating — we are disintegrating.

The flood of AI-generated content has created a massive Corporate Antibody response within our social and economic systems. To survive, organizations must adopt Generative Watermarking and Provenance technologies. These aren’t just technical safeguards; they are the new infrastructure of reality. We are shifting from a culture of blind faith in what we see to a culture of verifiable origin.

“Transparency is the only antidote to the erosion of trust; we must build systems that don’t just generate, but testify. If an idea is a useful seed of invention, its origin must be its pedigree.” — Braden Kelley

Why Provenance is the Key to Human-Centered Innovation™

Human-Centered Innovation™ requires psychological safety. In 2026, psychological safety is under threat by “hallucinated” news, deepfake corporate communiques, and the potential for industrial-scale intellectual property theft. When people cannot trust the data in their dashboards or the video of their CEO, the organizational “nervous system” begins to shut down. This is the Efficiency Trap in its most dangerous form: we’ve optimized for speed of content production, but lost the efficiency of shared truth.

Provenance tech — specifically the C2PA (Coalition for Content Provenance and Authenticity) standards — allows us to attach a permanent, tamper-evident digital “ledger” to every piece of media. This tells us who created it, what AI tools were used to modify it, and when it was last verified. It restores the human to the center of the story by providing the context necessary for informed agency.

Case Study 1: Protecting the Frontline of Journalism

The Challenge: In early 2025, a global news agency faced a crisis when a series of high-fidelity deepfake videos depicting a political coup began circulating in a volatile region. Traditional fact-checking was too slow to stop the viral spread, leading to actual civil unrest.

The Innovation: The agency implemented a camera-to-cloud provenance system. Every image captured by their journalists was cryptographically signed at the moment of capture. Using a public verification tool, viewers could instantly see the “chain of custody” for every frame.

The Impact: By 2026, the agency saw a 50% increase in subscriber trust scores. More importantly, they effectively “immunized” their audience against deepfakes by making the absence of a provenance badge a clear signal of potential misinformation. They turned the Trust Imperative into a competitive advantage.

Case Study 2: Securing Enterprise IP in the Age of Co-Pilots

The Challenge: A Fortune 500 manufacturing firm found that its proprietary design schematics were being leaked through “Shadow AI” — employees using unauthorized generative tools to optimize parts. The company couldn’t tell which designs were protected “useful seeds of invention” and which were tainted by external AI data sets.

The Innovation: They deployed an internal Generative Watermarking system. Every output from authorized corporate AI agents was embedded with an invisible, robust watermark. This watermark tracked the specific human prompter, the model version, and the internal data sources used.

The Impact: The company successfully reclaimed its IP posture. By making the origin of every design verifiable, they reduced legal risk and empowered their engineers to use AI safely, fostering a culture of Human-AI Teaming rather than fear-based restriction.

Leading Companies and Startups to Watch

As we navigate 2026, the landscape of provenance is being defined by a few key players. Adobe remains a titan in this space with their Content Authenticity Initiative, which has successfully pushed the C2PA standard into the mainstream. Digimarc has emerged as a leader in “stealth” watermarking that survives compression and cropping. In the startup ecosystem, Steg.AI is doing revolutionary work with deep-learning-based watermarks that are invisible to the eye but indestructible to algorithms. Truepic is the one to watch for “controlled capture,” ensuring the veracity of photos from the moment the shutter clicks. Lastly, Microsoft and Google have integrated these “digital nutrition labels” across their enterprise suites, making provenance a default setting rather than an optional add-on.

Conclusion: The Architecture of Truth

To lead innovation in 2026, you must be more than a creator; you must be a verifier. We cannot allow the “useful seeds of invention” to be choked out by the weeds of synthetic deception. By embracing generative watermarking and provenance, we aren’t just protecting data; we are protecting the human connection that makes change with impact possible.

If you are looking for an innovation speaker to help your organization solve the Trust Imperative and navigate Human-Centered Innovation™, I suggest you look no further than Braden Kelley. The future belongs to those who can prove they are part of it.

Frequently Asked Questions

What is the difference between watermarking and provenance?

Watermarking is a technique to embed information (visible or invisible) directly into content to identify its source. Provenance is the broader history or “chain of custody” of a piece of media, often recorded in metadata or a ledger, showing every change made from creation to consumption.

Can AI-generated watermarks be removed?

While no system is 100% foolproof, modern watermarking from companies like Steg.AI or Digimarc is designed to be highly “robust,” meaning it survives editing, screenshots, and even re-recording. Provenance standards like C2PA use cryptography to ensure that if the data is tampered with, the “broken seal” is immediately apparent.

Why does Braden Kelley call trust a “competitive advantage”?

In a market flooded with low-quality or deceptive content, “Trust” becomes a premium. Organizations that can prove their content is authentic and their AI is transparent will attract higher-quality talent and more loyal customers, effectively bypassing the friction of skepticism that slows down their competitors.

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 credits: Google Gemini

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Three Mandates for Better Decisions

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Three Mandates for Better Decisions

GUEST POST from Mike Shipulski

The primary responsibility of management is to allocate resources in the way that best achieves business objectives. If there are three or four options to allocate resources, which is the best choice? What is the time horizon for the decision? Is it best to hire more people? Why not partner with a contract resource company? Build a new facility or add to the existing one? No right answers, but all require a decision.

Rule 1 – Make decisions overtly. All too often, decisions happen slowly over time without knowledge the decision was actually made. A year down the road, we wake up from our daze and realize we’re all aligned with a decision we didn’t know we made. That’s bad for business. Make them overtly and document them.

Rule 2 – Define the decision criteria before it’s time to decide. We all have biases and left to our own, we’ll make the decision that fits with our biases. For example, if we think the project is a good idea, we’ll interpret the project’s achievements through our biased lenses and fund the next phase. To battle this, define the decision criteria months before the funding decision will be made. Think if-then. If the project demonstrates A, then we’ll allocate $50,000 for the next phase; if the project demonstrates A, B and C, then we’ll allocate $100,000; if the project fails to demonstrate A, B or C, then we’ll scrap the project and start a new one. If the decision criteria aren’t predefined, you’ll define them on-the-spot to justify the decision you already wanted to make.

Rule 3 – Define who will decide before it’s time to decide. Will the decision be made by anonymous vote or by a show of hands? Is a simple majority sufficient, or does it require a two-thirds majority? Does it require a consensus? If so, does it have to be unanimous or can there be some disagreement? If there can be disagreement, how many people can disagree? Does the loudest voice decide? Or does the most senior person declare their position and everyone else falls in line like sheep?

Think back to the last time your company made a big decision. Were the decision criteria defined beforehand? Can you go back to the meeting minutes and find how the project performed against the decision criteria? Were the if-then rules defined upfront? If so, did you follow them? And now that you remember how it went last time, do you think you would have made a better decision if the decision criteria and IF-THENs were in place before the decision? Now, decide how it will go next time.

And for that last big decision, is there a record of how the decision was made? If there was a vote, who voted up and who voted down? If a consensus was reached, who overtly said they agreed to the decision and who dissented? Or did the most senior person declare a consensus when in fact it was a consensus of one? If you can find a record of the decision, what does the record show? And if you can’t find the record, how do you feel about that? Now that you reflected on last time, decide how it will go next time.

It’s scary to think about how we make decisions. But it’s scarier to decide we will make them the same way going forward. It’s time to decide we will put more rigor into our decision making.

Image credit: Pexels

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Just Because You Can Use AI Doesn’t Mean You Should

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Just Because You Can Use AI Doesn't Mean You Should

GUEST POST from Shep Hyken

I’m often asked, “What should AI be used for?” While there is much that AI can do to support businesses in general, it’s obvious that I’m being asked how it relates to customer service and customer experience (CX). The true meaning of the question is more about what tasks AI can do to support a customer, thereby potentially eliminating the need for a live agent who deals directly with customers.

First, as the title of this article implies, just because AI can do something, it doesn’t mean it should. Yes, AI can handle many customer support issues, but even if every customer were willing to accept that AI can deliver good support, there are some sensitive and complicated issues for which customers would prefer to talk to a human.

AI Shep Hyken Cartoon

Additionally, consider that, based on my annual customer experience research, 68% of customers (that’s almost seven out of 10) prefer the phone as their primary means of communication with a company or brand. However, another finding in the report is worth mentioning: 34% of customers stopped doing business with a company because self-service options were not provided. Some customers insist on the self-service option, but at the same time, they want to be transferred to a live agent when appropriate.

AI works well for simple issues, such as password resets, tracking orders, appointment scheduling and answering basic or frequently asked questions. Humans are better suited for handling complaints and issues that need empathy, complex problem-solving situations that require judgment calls and communicating bad news.

An AI-fueled chatbot can answer many questions, but when a medical patient contacts the doctor’s office about test results related to a serious issue, they will likely want to speak with a nurse or doctor, not a chatbot.

Consider These Questions Before Implementing AI For Customer Interactions

AI for addressing simple customer issues has become affordable for even the smallest businesses, and an increasing number of customers are willing to use AI-powered customer support for the right reasons. Consider these questions before implementing AI for customer interactions:

Is the customer’s question routine or fact-based?
Does it require empathy, emotion, understanding and/or judgment (emotional intelligence)?
Could the wrong answer cause a problem or frustrate the customer?
As you think about the reasons customers call, which ones would they feel comfortable having AI handle?
Do you have an easy, seamless way for the customer to be transferred to a human when needed?

The point is, regardless of how capable the technology is, it doesn’t mean it is best suited to deliver what the customer wants. Live agents can “read the customer” and know how to effectively communicate and empathize with them. AI can’t do that … yet. The key isn’t choosing between AI and humans. It’s knowing when to use each one.

Image credits: Google Gemini, Shep Hyken

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The Hidden Discipline for Transformation Success

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The Hidden Discipline for Transformation Success

GUEST POST from Geoffrey A. Moore

In Zone to Win, we lay out a playbook for transformational initiatives that focus on prioritizing a single effort across the entire enterprise for a period of no longer than two years. Core to success is the unswerving commitment of the CEO, the Executive Leadership Team, and the Board of Directors to see this through to completion come hell or high water. That means it is top of the agenda at every operational review and in between has an open-door escalation path to address any obstacles that come up in real time. It also means that the company as a whole is continually getting updates on the progress being made, the importance of the mission, the imperative that it get everyone’s support.

All necessary, all good. That said, there is a hidden discipline that makes the difference between success and failure, one that can be made visible in the annual operating plan, and thereby remove some of the mystery that surrounds transformational success. It begins with the transformation team simply calling out any dependencies it has on deliverables that come from divisions in the Performance Zone.

That list will get supplemented by additional unanticipated requests that inevitably crop up in the race to get to material scale. Taken together, these are the actions that are most subject to delay or deprioritization whenever the Performance Zone gets under performance pressure. The problem is that time is the one resource you cannot replenish, so you can never afford to delay or deprioritize any request from the Transformation Zone.

So, the discipline required for success is to call out every dependency as soon as it becomes visible, put it on a strict timeline, and then monitor it relentlessly through to completion. At every juncture, you will get pushback, not for the request per se but for the timeline on which it needs to be delivered. Capitulating to that pushback is the nice thing to do—the requests always have merit in their own right—but you cannot take that route and expect the transformation to succeed.

To make this brutally clear, if at any time during a transformational initiative, you lose momentum for any reason, that initiative will fall short of the game-changing goals you set for it. Said another way, inertia is a hugely powerful force, and the world does not naturally want to transform. Give it any other path, and it will take it. Your job is to block every other path. You don’t have to be brilliant to do this. You just have to be undistractedly vigilant.

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

Image Credit: Geoffrey Moore

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