As AI becomes a core part of organizational operations, senior leaders are navigating large-scale change and pressure to demonstrate tangible impact. AI is no longer limited to pilots; it now influences daily decisions, workflows, and client delivery.

Despite growing investment, many organizations struggle to turn experimentation into measurable value. According to a 2026 survey of global AI and data leaders, 93% said human factors are the main barrier to adoption. Yet, executives remain confident about AI’s potential.

The Positive Group conducted interviews and focus groups with 35 executives—including CEOs, CHROs, chief innovation officers, and functional leaders—across sectors such as professional services, financial services, consumer brands, aviation, and life sciences. Their research examined how leaders experience AI adoption in real time, including challenges in direction, adaptability, and sustaining progress.

One senior leader said, “The target’s always moving,” highlighting the difficulty of maintaining credibility when organizational goals continuously shift. Leaders also noted that AI brings ongoing disruption, unlike episodic transformations such as new systems or restructures.

“The target’s always moving. I know what we said six months ago, but actually the target’s moved. That’s hard, because credibility starts to wobble when direction keeps changing, even if the change is justified,” a professional services executive explained.

The pace of change also affects perceptions of progress. A head of learning and development commented, “Change rarely happens gradually; it’s more like climate change. Nothing seems to shift, and then suddenly the world looks completely different. Leading through that kind of sudden disruption is one of the hardest challenges.”

Defining AI Value Remains Complex

Leaders emphasized that different stakeholders have varying expectations for AI initiatives. Shareholders often collapse AI into a single label, asking only, “What are you doing in AI?” Meanwhile, executive committees may rush into AI without considering early-stage risks.

Employees, by contrast, tend to have a clearer understanding of AI’s capabilities. A chief technology officer said, “Employees have actually been the most positive. That’s where we’ve been clearer about what AI can and can’t do, and where it genuinely helps.”

Boards often demand visible progress even when the problem is unclear. A senior executive in global retail noted, “The biggest challenge isn’t resistance, it’s leadership FOMO. Everyone wants an update on AI before they understand the problem.”

Many AI applications do not produce immediate returns, but small improvements can accumulate over time. A senior vice president in financial services explained, “A lot of AI applications won’t have a neat, immediate return. A tool that helps people write clearer emails or reduces reconciliation time might save 10 or 30 minutes a day. That doesn’t cut a role, but it compounds.”

Leaders emphasized that focusing only on short-term ROI can discourage experimentation. A head of human-centered AI noted, “Leaders need to be mindful of how AI helps humans flourish, not just chase short-term gains. That means broadening the definition of return on investment beyond time and cost savings to include strategic impacts like employer value proposition, brand strength, and talent retention.”

Human Factors Remain the Biggest Barrier

Executives highlighted that human concerns, rather than technology, often slow AI adoption. Experienced professionals may feel anxiety over how AI affects their roles.

“What tends to get in the way isn’t the technology itself. A lot of it is about people worrying what this means for their role, saying things like, ‘That’s my job, you can automate that bit, but not this,’” said a senior executive in global consulting.

Introducing AI with fear can backfire. A senior digital leader in aviation explained, “When AI is introduced with fear, it fuels resistance to change, lowers engagement, and limits adoption. But when people are prepared, included in the journey, and know their voices are part of the design process, they are far more likely to engage.”

How Leaders Are Driving AI Transformation

Leaders are responding by adjusting communication, demonstrating their own learning, and creating conditions for progress amid uncertainty.

Many are simplifying AI language to make it accessible. A senior leader in the consumer sector said, “Storytelling and simplicity are powerful drivers of adoption. We need to explain AI in plain language, simple enough that even my six-year-old could understand it, because accessibility builds curiosity and trust.”

Leaders are also giving non-technical functions direct access to AI tools. A senior technology leader in financial services noted, “The people closest to the work are often best placed to see where AI can help. When routine tasks are taken care of, those teams have more time to focus on what really matters. This more federated approach has been one of the most meaningful shifts we’ve made.”

Executives emphasized that AI adoption is not just about tools but about rethinking how work itself evolves. A senior AI and people leader in global technology said, “One of the hardest day-to-day challenges is getting people to step back and think about how work itself is going to change. We’ve spent years rewarding efficiency and productivity, and that mindset naturally pushes people to layer AI on top of existing processes. But that won’t get us where we need to be.”

Building Trust Through Transparency

Leaders are modeling AI use publicly to shape organizational norms. A senior vice president in insurance said, “I made a point of using the tools myself in visible ways. I’d take a 100-plus-page board paper and show how I used ChatGPT to summarize it. Not because it was perfect, but to show that you don’t need to be technical to get value. It’s about asking the right questions.”

Executives stressed that early AI work does not need to be perfect. A chief innovation officer in a global law firm said, “We had to move very quickly [on an AI initiative], and from the start we were clear it wasn’t going to be perfect. We said, ‘We’ll put it out, we’ll iterate, we’ll take feedback.’ It’s an 80–20 approach, not 100%.”

Leaders emphasized that building trust requires transparency, consistency, and acknowledging risks. A senior digital leader in aviation explained, “When AI is introduced with fear, it fuels resistance to change, lowers engagement, and limits adoption. But when employees are prepared, included in the journey, and know their voices and perspectives are part of the design process, they are far more likely to embrace innovation.”

By demonstrating curiosity, judgment, and adaptability, leaders are helping teams engage with AI in their own work and feel safe experimenting.

PHOTO: FREEPIK

This article was created with AI assistance.

We make every effort to ensure the accuracy of our content, some information may be incorrect or outdated. Please let us know of any corrections at [email protected].