Collaborative Culture: Deep Dive into AI

AI is Not a Tech Problem. It's a Culture Problem.

Episode Transcript

This transcript has been edited for clarity and readability. Repeated words, false starts, recording directions, and non-substantive verbal acknowledgments have been removed. The meaning of the conversation has been preserved.

MONICA M. SMITH:

Hello and welcome back to Collaborative Culture, the podcast where we get serious about the thing that actually makes or breaks everything else in business: culture. I’m Monica M. Smith, global leadership consultant and founder of Tradewinds Career Consulting.

DR. KRISTINE GENTRY:

And I’m Dr. Kristine Gentry, CEO of Culture Grove and co-founder of Podium Project. Together, Monica and I have spent decades working with leaders and teams around the world to build cultures that perform. Today, we’re diving into a topic that is absolutely everywhere right now. In fact, I’m a little tired of hearing about it, but we still have to talk about it because it matters: artificial intelligence.

MONICA M. SMITH:

This is not our first look at AI, but we wanted to return to it because the conversation is beginning to shift. We are not here to focus on the technology; we are here to focus on the humans. The research is now telling us loudly and clearly that AI is not simply a technology problem—it is a culture problem. We have been making that case since our second episode: Culture will shape whether AI is adopted successfully.

DR. KRISTINE GENTRY:

Using AI means changing behavior, and changing behavior means changing culture. This is not simply a technology problem. It is a significant behavior change, and that is where many organizations are struggling. They are treating AI as a traditional technology shift, even though technology initiatives often fail when leaders overlook the behavioral and human dimensions. Once again, culture is critically important—and too often overlooked.

MONICA M. SMITH:

This is our world, so let’s take a deeper look at some recent findings from Harvard Business Review, Fast Company, MIT, Stanford, and others—and pull out the practical lessons. Let’s begin with the uncomfortable truth: Why is AI failing? A global survey from Boston Consulting Group found that only 26% of companies had seen tangible return on investment from their AI investments. MIT’s NANDA initiative estimated that 95% of AI initiatives fail to deliver their intended value. A survey of 100 C-suite executives also found that 45% said their AI return was below expectations. By any measure, those are alarming numbers.

DR. KRISTINE GENTRY:

It is remarkable. Organizations are pouring billions into this technology, yet most are not getting the results they expected. That should stop leaders in their tracks.

MONICA M. SMITH:

It should. Across these studies, researchers found that the most significant barriers were not technical. They were organizational, human, and cultural.

DR. KRISTINE GENTRY:

That is exactly what we tell clients about every major change initiative: Technology is not the hardest part. People are.

MONICA M. SMITH:

One Harvard Business Review article described the problem as “technosolutionism”—the belief that better technology alone will solve organizational problems. When leaders fall into that trap, they treat AI adoption as an engineering exercise. They buy sophisticated software and assume the human side will take care of itself. It does not. Integrating AI requires multiple, interconnected behavior changes. It changes how people think about their work, identity, place in the organization, and value. When leaders ignore those dimensions, employees may resist or quietly work around the technology.

DR. KRISTINE GENTRY:

And we've seen this firsthand. You roll out a new system, there's a big launch, and six months later, it's barely being used. And leadership is frustrated because the technology is good, but the culture never caught up. People just didn't use it.

MONICA M. SMITH:

That is the pattern. Let’s look at what it looks like up close and, more importantly, what companies that are getting it right are doing differently.

DR. KRISTINE GENTRY:

One of the most useful frameworks I found identifies three distinct human fears that derail AI adoption. When you hear them, you will probably recognize them immediately. The first is what researchers call the uncertainty problem. Slack conducted a global survey of more than 17,000 office workers and found that 61% had spent fewer than five hours learning about AI, while 30% had received no training at all. When people do not understand a technology, they either dismiss it as hype or fear it as all-powerful. Neither extreme is useful.

MONICA M. SMITH:

That uncertainty creates paralysis rather than a sense of curiosity or experimentation. We see a similar pattern during intercultural transitions: The unknown often feels scarier than the known. The antidote is exposure, education, and practice.

DR. KRISTINE GENTRY:

Exactly. The second fear is replacement. When employees suspect they are training a system that may eventually take their jobs, they comply minimally. They drag their feet and contribute only enough to avoid getting in trouble. Researchers call this the training trap.

MONICA M. SMITH:

This is where culture becomes critical. The best companies do more than tell employees that AI will not replace them, especially when workers are seeing contrary messages in the news. They make structural commitments that demonstrate their intentions. One e-commerce company pledged to increase total labor spending by 1% every year. That is not simply a town-hall promise; it is a measurable commitment. When implemented properly, that kind of transparency can build trust. It's a real commitment you can check in on. And that kind of commitment, that's a risk to take that, to say that that can be looked at and it can build trust if implemented properly.

DR. KRISTINE GENTRY:

That is trust through transparency, which aligns closely with what we teach. The company is not simply telling people they will not lose their jobs while employees hear alarming messages elsewhere. It is taking concrete action to demonstrate continued investment in its people. Most companies are not doing that right now.

MONICA M. SMITH:

Much of the problem is uncertainty, compounded by the way some technology companies describe AI as a means to eliminate the need for people. That reflects a deeply flawed understanding of business. Business is about people, organizations, and serving customers—not simply completing transactions. When was the last time you were happy to speak with a service chatbot about a real problem? Many automated systems solve questions that would not have prompted me to call in the first place. The third fear is especially interesting from a leadership perspective: the self-image problem, or fear of status loss. So researchers found that engineers who were quietly using AI tools, but hiding it because they thought they might look lazy, less skilled, or even dishonest.

DR. KRISTINE GENTRY:

One example involved radiologists ignoring AI recommendations to protect their professional pride, even when the AI was outperforming them. That is a powerful example of ego getting in the way of outcomes.

MONICA M. SMITH:

Absolutely. They believe they are protecting their jobs or status. Some companies have flipped that dynamic. One financial services firm launched an AI Masters program that fast-tracked employees who demonstrated exceptional AI skills, regardless of title or seniority. The company made AI mastery a badge of sophistication rather than treating the technology as a threat to expertise.

DR. KRISTINE GENTRY:

I love that example. It shows how culture is shaped by what an organization celebrates. When a company recognizes people for learning and using AI, it encourages those behaviors to be repeated. The behaviors an organization rewards are the behaviors that continue.

MONICA M. SMITH:

Okay, so let's go further afield to a couple of other companies who are doing what's spectacularly right because there's a lot to learn and the common thread is culture.

DR. KRISTINE GENTRY:

Yeah, so tell me about the Kaizen connection because I thought that was one of the most elegant ideas we came across in the research.

MONICA M. SMITH:

It is and it's actually so proven. as a human cultural capability in organization. So Wilson and Daugherty and again, Harvard Business Review drew this parallel to Kaizen. I think we all know, but just to repeat the Japanese philosophy of continuous improvement that Toyota built its entire system on. The idea that transformation doesn't come from one big revolution. It comes from constant, relentless, small improvements driven by people at every level of the organization. Right, exactly. And the key insight is that AI, when implemented with the right culture, is not displacing workers. It's moving them to the center of work. It's amplifying their judgment, their creativity, their institutional knowledge. And we talked about these as key assets for human employees to use this tool, AI. And it's finally fulfilling the long-held aspiration of management theory, putting real business transformation in the hands of the employees.

DR. KRISTINE GENTRY:

Alright, so let's make this concrete. What does it actually look like in practice?

MONICA M. SMITH:

Okay, so an example of it was at Mercedes and they put in a platform called, I think it's called MO360 that connects all their passenger car plants worldwide. So the plants, the people in the, where they're putting together the machines. And because of natural language interfaces, that's a great thing, plain English, everybody has to use it in English, not technical code. A production worker on the shop floor can now ask about assembly line bottlenecks and get real-time data-rich input. So this is enabling factory floor workers to understand why things are slowed down and having these interim solutions to problems rather than shutting down the assembly line. And the CIOs there said it perfectly, our data is becoming everyone's business at Mercedes.

DR. KRISTINE GENTRY:

I love that because it's not just a technology story, that's a culture story that they democratized access to insight and then trusted their frontline workers with real information.

MONICA M. SMITH:

Mercedes also backed the platform with investment in its people. Its Turn2Learn program gives frontline employees access to more than 40,000 courses on data and AI, including prompt engineering and natural language processing—skills that once belonged primarily to the IT department.

DR. KRISTINE GENTRY:

It's amazing. Mahindra, I think it's Mahindra and Mahindra, the Indian automaker saw something similar. Their teams can now send queries to AI driven virtual assistants and get step-by-step guidance for repairing industrial robots. The head of AI there said it significantly raised shop floor morale. The people felt more capable and more valued, which I think it's just amazing. Like you said, it's people. being able to do more and having more responsibility and autonomy to solve problems, it's really great.

MONICA M. SMITH:

And think about that, not just for respecting the employee in that moment, but think about the retention boost. You can build your career, the mobility within that company, because that company trusts you and values you. That's a big step ahead in a tough economy like this. So it's truly Kaizen, human empowerment, and that's what happens when culture creates the conditions for AI. It is AI as a tool for the human Kaizen.

DR. KRISTINE GENTRY:

I want to bring in something from Fast Company that really resonated with me. The article was titled “How Company Culture Drives AI Strategy Success,” and it profiled Architech, a company recognized as one of Fast Company’s Best Workplaces for Innovators and one of only 10 companies globally recognized for excellence in AI. Its entire story was about putting culture first.

MONICA M. SMITH:

Tell us a little bit more about that.

DR. KRISTINE GENTRY:

So they launched what they called an AI Innovation Challenge, open to every single employee where people are invited to identify real workplace challenges and solve them using AI. Cross-functional teams, three months, bottom-up innovation. One team built an automated quality assurance testing system that improved consistency across the board, and they celebrated it publicly. A town hall showcase, a monthly AI Innovation Award.

MONICA M. SMITH:

You know, I love that because it's gamification. It's competition and everybody wins by creating something and then there's a best outcome. They made innovation a cultural habit, which was something you told us about in the last episode. Not a project, not an initiative, continuous innovation as a habit. Love it.

DR. KRISTINE GENTRY:

Yeah, it's so great. And their COO said something that I wrote down because I want to use it with clients. There's no app for transformation. There's something better, culture. That's what powers our AI strategy.

MONICA M. SMITH:

I want that on a T-shirt, Kristine, because it is true: “There’s no app for transformation. There’s something better—culture. That’s what powers our AI strategy.” We are finally seeing successful organizations explain what works. Contrast that with another Fast Company article we reviewed: 45% of CEOs reported active resistance or hostility toward AI initiatives, and 71% of C-suite executives admitted their workforces were not ready to leverage AI effectively. The technology may be the same, but the cultural conditions are not. Lara Shewchuk captured it clearly: “If your people aren’t part of your AI strategy, you don’t have one.”

DR. KRISTINE GENTRY:

That is perfect. It also reminds me of the Kyndryl Readiness Report, which found that only 29% of organizations believed their workforce was truly ready to leverage AI effectively, while 87% of leaders expected AI to reshape jobs significantly within a year. That is an enormous gap.

MONICA M. SMITH:

Yeah, I have to say that is a complete disconnect. That's not going to happen. And if it's a gap that only culture can close, training, trust, psychological safety, inclusion, they're all culture levels. But I'll tell you that turning everything around in one year, culture takes time, takes real engagement.

DR. KRISTINE GENTRY:

Unless organizations begin investing immediately in the practices we have discussed, that gap will remain. Unfortunately, the companies doing this well still appear to be the minority. Many others are fumbling through adoption, unsure what to do while hoping AI will somehow reshape work on its own.

MONICA M. SMITH:

Well, if they're publicly traded companies, think the analyst calls could get a little heated about this particular topic. But let's talk about the behavioral science part of it. I wanted to bring up some behavioral science because the third piece of research we dug into was one of the more nuanced takes I've read on why AI adoption fails. And it comes down to how humans actually process change.

DR. KRISTINE GENTRY:

Yes. That comes from research by David De Cremer and colleagues at Northeastern and Stanford.

MONICA M. SMITH:

The central finding is important: Humans are not always rational. We know from decades of behavioral research that when people face change, they fear losses more than they value equivalent gains. They cling to familiar ways of working even when those methods are less efficient, and they may make sweeping judgments after seeing a tool make one highly visible mistake—even when the tool outperforms people over time. of the thing doesn't work. It's just useless. Even when the tool outperforms them over time.

DR. KRISTINE GENTRY:

Yeah, that's the algorithm abandonment problem. You see the AI make one error and suddenly the whole thing is untrustworthy, even if its overall accuracy is far better than a human's.

MONICA M. SMITH:

Exactly. The researchers call the solution behavioral human-centered AI. Successful adoption depends not only on the sophistication of the technology, but on leadership decisions informed by how people’s biases, habits, and needs affect the entire change cycle. That is culture.

DR. KRISTINE GENTRY:

Yeah, again, design, adoption, and ongoing management, all three stages.

MONICA M. SMITH:

In the design stage, the researchers recommend co-designing AI with diverse end users. It is also less expensive to involve users before a system is built rather than surveying them after the organization has purchased a tool. At that point, engagement can become a marketing exercise designed to persuade people rather than genuine co-creation. When employees help shape a solution, they are more likely to feel real ownership.

DR. KRISTINE GENTRY:

In the adoption stage, the three priorities are to frame AI as an augmenter rather than a replacement, make its mistakes relatable so it feels like a learning partner, and explain how it reaches decisions so that mystery and anxiety are reduced.

MONICA M. SMITH:

Yeah, and we also found another example, really good example in the healthcare, and I know you have some healthcare clients that you've worked with. When the providers proactively disclosed an AI's limitations and safeguards that are there to watch those limitations, rather than offering an explanation of their minimal errors ever made with the AI, the trust and willingness to use it increased significantly. Being upfront with the employees about imperfections made people more willing to adopt it, that that vulnerability leadership to employee builds trust of using this AI tool. I thought that was pretty great.

DR. KRISTINE GENTRY:

That is really great and we know with Brene Brown's research supports that as well.

MONICA M. SMITH:

In the management stage, the researchers ask leaders to hold themselves accountable for their own biases, including overconfidence, overpromising, escalation of commitment, and doubling down on failing projects because they do not want to admit something is not working. Measurement matters—not only technical performance, but employee trust, perceived fairness, and genuine adoption.

DR. KRISTINE GENTRY:

That makes sense. Yeah. And I want to spend a moment on one of the most compelling corporate examples we saw in the research because it shows exactly what culture driven AI adoption can produce. That's the DBS Bank in Singapore.

MONICA M. SMITH:

Pure fame, right?

DR. KRISTINE GENTRY:

In 2018, DBS introduced a simple four-question framework for evaluating every AI use case in the organization. PURE stands for purposeful, unsurprising, respectful, and explainable. Instead of a 40-page policy document that nobody reads, DBS gave employees four human questions: Is this purposeful and meaningful? Will the results surprise our customers? Does it respect people and their data? Can we explain the outputs? I love it. Yeah, it's really great. And they backed it up with a responsible data use committee to review anything that didn't meet the PURE standard. So they really created some good guardrails.

MONICA M. SMITH:

What results did that produce? By 2023, AI at DBS had generated $274 million in value—not despite the organization’s cultural and governance investment, but because of it.

DR. KRISTINE GENTRY:

That demonstrates that culture is not soft. Culture is the strategy that helps a business succeed. That is what the DBS story shows.

MONICA M. SMITH:

Absolutely. I'm going to read a lot more about that because there is a lot to learn. Okay, so let's talk about something that was rarely discussed in the AI conversation, but the research calls out very directly, organizational politics.

DR. KRISTINE GENTRY:

Yep. The power dynamics, the territory protection, the quiet sabotage.

MONICA M. SMITH:

Yep. So more Harvard research identified three political patterns that derail AI even when the technology and the people are ready. The first is resource hoarding. At a large tech firm, researchers found that programmers were 16 to 18 percent less likely to recommend AI access to their own teammates because knowledge was their competitive edge. Sharing it felt like weakening their position.

DR. KRISTINE GENTRY:

Man, you can totally get that when everyone's afraid that AI is going to cost jobs, you hoard on to your knowledge of AI. So you're the more employable one. And this continues to scale up across business units. The departments with the most sophisticated data and AI models have the least incentive to share with smaller units that actually need it the most.

MONICA M. SMITH:

Yeah, where the outcomes could be super beneficial. The second pattern is hierarchy disruption. AI is leveling the playing fields in ways that threaten traditional power structures. So in one software firm, programmers with two years of experience were outperforming colleagues with five years of tenure because they knew how to use the AI tools to get to the same finish line. And that's exciting if you're a junior. That's terrifying if you're senior and you've built your career on that experience.

DR. KRISTINE GENTRY:

That is especially interesting for managers whose authority is tied to headcount. When AI makes a team more efficient, it may reduce the number of people required—and with it, a manager’s budget, bonus, or prestige.

MONICA M. SMITH:

The smartphone company OPPO developed an effective response to that problem. It staged an AI tournament in which every employee had equal access to the tools and results were ranked publicly by department. Managers suddenly had a reason to champion AI adoption or risk their teams lagging behind. The competition reframed status from “How large is your team?” to “How much can your team achieve?”

DR. KRISTINE GENTRY:

And again, that's using culture, creating an incentive structure. If you reward what matters, then you get what matters. It's brilliant. So as we bring this together, what's the through line? What do we want our listeners to walk away with today?

MONICA M. SMITH:

Well, I really want leaders and all of our listeners to hear this clearly. The companies winning with AI are not winning because they have the best technology. They're winning because they have the best culture. Cultures of trust, cultures of continuous learning and therefore ability to do continuous transformation, and cultures where every employee has a voice and a stake in the positive outcome in the transition.

DR. KRISTINE GENTRY:

And culture is the amplifier. AI is the accelerant. But if the culture isn't there, the accelerant just creates a fire, not momentum.

MONICA M. SMITH:

No fires, please. And for the leaders in our audience who are doing this work every day, the practitioners, the consultants, the chief human resource officers and the CEOs who care deeply about their people, here's your checklist. Are your people informed? Do they have genuine training, not just a town hall announcement, just see what you can do about it? Are your promises credible? And I would say is your communication consistent because that makes the credibility. Have you created structural commitments that prove you're investing in people, not just the technology? Are you co-designing or are just deploying?

DR. KRISTINE GENTRY:

And are you celebrating the humans who are leading this well? Because what gets recognized gets repeated.

MONICA M. SMITH:

The research is unambiguous: Culture is not the soft side of AI adoption. Culture is the strategy. When organizations get it right, the results can be extraordinary. At DBS Bank, AI generated $274 million in value. Other examples included productivity increasing by 22%, profitability increasing by 3%, professional services firms entering new markets, and Merck reducing false rejection rates by more than 50%. These are meaningful business outcomes.

DR. KRISTINE GENTRY:

These are real results produced by people who chose to lead AI transformation differently. The data repeatedly shows that strong cultures help organizations achieve stronger outcomes, but leaders must devote meaningful time and attention to cultivating that culture.

MONICA M. SMITH:

That is the work Kristine and I both do, and we are happy to share our workshops and perspectives with organizations navigating this change. Thanks for spending time with us on Collaborative Culture. If something resonated today, share this episode with a colleague who is navigating the AI conversation. We will link all the research in the show notes.

DR. KRISTINE GENTRY:

If you want to go deeper on building the kind of culture that makes transformation possible, reach out. This is the work Monica and I do. AI may be a new technology, but adopting it is still a culture change.

MONICA M. SMITH:

I want to return once more to Lara Shewchuk’s quote because it captures the message so well: “If your people aren’t part of your AI strategy, you don’t have one.” Until next time, keep building cultures that make humans better, because that is what this is always about. You can reach me on LinkedIn as Monica M. Smith or through my website at TradeWindsCareerConsulting.com.

DR. KRISTINE GENTRY:

And I’m Dr. Kristine Gentry. You can find me on LinkedIn as Kristine McKenzie Gentry or through my website at CultureGrove.com. Thanks for listening, and check back in two weeks for our next episode.