"To get an AI transformation right, 70% of the focus should be on people and processes.” (BCG, “Where’s the Value in AI?”, October 2024)
AI success depends on more than just powerful tools—it hinges on how well leaders guide their people through change. According to BCG, 70% of AI transformation outcomes hinge on people and process. Money, tools, and training are flowing toward the technology. Now is the time to invest just as intentionally in the leaders guiding their teams through the change.
In my work coaching senior leaders responsible for driving change, AI has moved to the center of the conversation. Clients speak candidly about the bold targets they've been handed and the very human challenges slowing progress. What follows are the four pressure points I’m hearing most often, and how, through a coaching partnership, leaders are work through them in real time. In many ways these are basic challenges; but they are significant contributing factors to why 74% of companies haven’t moved past the pilot stage. Addressing these leadership gaps is where momentum either builds—or breaks down.
Time and Strategic Priorities
Executive calendars are famously packed—from board meetings to operational crises— leaving almost no room for ‘big-picture’ AI thinking. Yet real AI impact demands not just time, but a mindset shift: treating AI as mission critical. Leaders must heed the CEO and Board’s mandate by carving out recurring time blocks—protected strategic blocks for working on how AI will reshape their function and drive value. This requires deliberate rituals and ongoing commitment that reinforce both the priority and the mindset of AI leadership.
AI Fluency & Confidence
Many leaders are subject matter experts in their field. The rapid evolution of AI leaves even the most seasoned executives feeling out of their depth and uncertain about how to acquire new knowledge and gain confidence to make decisions related to AI. Overcoming this starts by reframing AI learning as an integral part of leadership responsibility (and something others are doing too). Diagnosing knowledge gaps and tapping into internal experts and external resources enables the building of a learning plan. In this approach, you model the curiosity and resilience you expect from your team and give yourself the credibility and confidence to make informed, timely decisions about AI in your organization.
Team Motivation
When teams view AI as a threat rather than an opportunity, resistance can stall even the most promising initiatives. Leaders can begin by listening with empathy, and communicating with transparency, and consistency in individual conversations and group settings. Then, actively reframe the narrative by positioning AI as the growth opportunity it is: a chance to build skills that will be essential in the years ahead. Partnering with team members on their learning plan and spotlighting even small wins and learning moments helps to normalize the uncertainty that comes with change. When team members believe they have agency in shaping the future, motivation rises—even in the face of disruption.
Communicating with Clarity
Implementing AI is a transformation that shuffles workflows, roles, and professional identities. Leaders must engage teams directly in co-designing new workflows, setting clear expectations about what’s changing and why, and maintaining consistent two-way communication. Establishing simple rhythms—such as weekly check-ins, milestone reviews, and lessons-learned sessions—helps anchor new ways of working. When people are invited to shape the process and have channels to raise concerns or share insights, AI adoption becomes something they’re invested in—not something being done to them. This kind of leadership is what turns early momentum into business value.
AI success demands mastery of both technology and people. It isn’t just another tech rollout. The leaders who succeed fastest will be those who tackle the people challenges head-on —with clarity, courage, and the right support along the way.
Sheryl Kurtis is a WJM Coach who’s led multi-million- dollar tech and people-change programs at UBS, Barclays, and Wells Fargo. She now helps leaders bridge the gap between AI’s promise and everyday practice.
