News

By Tammy Hawkins - Client Partner, Head of Western United States, and Head of Technology & Digital – North America

August 2026

Why AI transformation has become a leadership challenge more than a technology challenge

Over the past several months, nearly every executive conversation I've had has included AI. Going into those meetings, I expected to hear discussions about large language models, copilots, agentic frameworks, and the latest technology platforms. I assumed the conversation would revolve around which tools organizations were adopting and how quickly they could deploy them. That's not what happened.

Instead, I found myself having conversations about leadership, organizational design, governance, workforce capability, business processes, and operating models. AI was present in every discussion, but it was rarely the center of the conversation, and that
surprised me. 

After speaking with executives leading AI initiatives across enterprise software, industrial organizations, construction, and digital infrastructure, several clear themes began to emerge. While every organization is approaching AI differently, the leaders making meaningful progress seem to be thinking about the challenge in remarkably similar ways. What they're building isn't simply AI. They're building organizations designed to operate differently.

AI is becoming an operating model, not a technology project

One executive shared that nearly 80 percent of his focus over the past year has been dedicated to AI, but when he described the work, he barely mentioned models or software. Instead, he talked about redesigning workflows, evaluating business processes, and helping the organization determine which activities were transactional, which required human judgment, and which demanded leadership. Only after that work was completed did AI become part of the solution.

That conversation fundamentally changed how I think about AI transformation. The organizations making meaningful progress aren't starting with technology, they're starting with work itself. Rather than asking "Where can we apply AI?", they're asking "How should work be performed going forward?" That's a very different question, and one that has much broader implications for the business, because AI becomes part of a larger operating model rather than a standalone initiative owned by IT.

Adoption is harder than implementation

Another theme surfaced repeatedly: technology isn't proving to be the hardest part, people are. Several executives described significant investments in helping employees understand not only how to use AI, but how to work differently because of it. The objective wasn't simply increasing AI usage, it was developing new organizational capabilities. Building the technology wasn't the difficult part. Changing how people work was.

"Organizations often view AI implementation as a technology project, they are not seeing the entire picture and value AI presents in their business ." — Technology Executive, Enterprise Software

The executives leading successful transformations see it as a change management initiative supported by technology. Deployment is only the beginning, and real transformation begins once people start thinking differently about how work gets done.

The executive resume has quietly changed

One of the unexpected advantages of executive search is that I get to watch leadership profiles evolve in real time, not through analyst reports or surveys, but through executive conversations and the resumes of leaders building these transformations.

Only a few years ago, the strongest engineering resumes emphasized cloud migration, distributed systems, DevOps, Kubernetes, platform modernization, and microservices. Today, I'm increasingly seeing accomplishments centered on AI-enabled products, intelligent workflows, recommendation engines, agentic systems, AI governance, human-in-the-loop design, and measurable business outcomes created through AI.

The language has changed because the expectations have changed. Organizations are no longer looking only for leaders who understand modern technology, they're looking for leaders who understand how technology transforms the business itself. 

The best AI leaders rarely call themselves AI experts

Perhaps the most interesting observation from these conversations is how few of these executives actually describe themselves as AI experts. Instead, they introduce themselves as transformation leaders: architects, operators, product builders, business leaders. They spend as much time talking about governance, organizational alignment, customer outcomes, and business processes as they do about technology, because while technology matters, context matters even more.

The conversation about people has changed

Public discussion around AI often focuses on workforce reduction. Interestingly, that wasn't the dominant theme emerging from these conversations. Every executive acknowledged that efficiency matters, but very few started by talking about reducing headcount. Instead, they talked about redesigning work, improving decision-making, helping employees move into higher-value activities, creating new management capabilities, and building organizations that can continuously adapt.

"We're no longer asking how many people AI replaces. We're asking which work actually creates value." — Transformation Executive, Industrial Construction

Rather than viewing AI as a replacement for people, these leaders are increasingly viewing it as a catalyst for redefining how people contribute.

Final thoughts

Every major technology cycle introduces new tools, new terminology, and new predictions about how business will change. What feels different about AI is that the conversation has moved beyond technology much faster than many expected. 

The executives I'm speaking with are no longer debating whether AI will transform their organizations, they've already accepted that it will.

The questions they're asking now are much harder :

• How should work be redesigned?
• How do we prepare our people?
• How do we build organizations capable of continuously adapting?
• How do we ensure AI becomes part of the business rather than simply another technology initiative?

Those aren't technology questions. They're leadership questions.

And if the conversations I've had over the past several months are any indication, the organizations that will separate themselves over the next five years won't necessarily be those that adopted AI first. They'll be the ones that learned how to build organizations capable of evolving alongside it.