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The Future of Leadership Development: AI-Driven Manager Enablement
“If we play our cards right, this might be the golden age of coaching. It just might be delivered in a very different way.”
Matthew Breitfelder, global head of human capital at Apollo Global Management, made that proclamation at the 2026 NYU Coaching and Tech Summit, but he definitely wasn’t alone in the sentiment.
For decades, coaching has been a perk reserved for the select few, limited to senior executives or promising employees. The “golden age” Breitfelder envisions is one where coaching becomes accessible to everyone, regardless of title or position. The “delivered in a very different way” is — you guessed it — with AI.
This golden age doesn’t cut humans out of the picture. Rather it works on what was called “hybrid intelligence,” a blend of the best human capabilities with the scaling capabilities of AI.
It is those scaling capabilities that Dr. Anna Tavis, host of the event and department chair of Human Capital Management Department at NYU's School of Professional Studies, flagged during a conversation following the summit.
“We are now questioning what coaching is. The human to human and empathy piece is the top of the pyramid. However, the mission of coaching right now is not to continue to circle the top of the pyramid, but to expand the foundation,” Tavis told Reworked.
The conversation throughout the event marked a notable shift from the last few years, a change from “What is our AI strategy” to “What is our business strategy, and how can AI support it?”
Note: Read Tavis's full interview.
AGCO Corporation: A Case Study in Scaling Coaching to All
Colleen Sugrue, head of global learning and organizational capability at AGCO Corporation shared a case study of what coaching at scale can look like.
AGCO is a multinational corporation that manufactures agricultural machinery. The company has 230 locations around the world and its employees speak 25 languages. A belief of the possibilities coaching can create when offered to employees drove Sugrue to explore vendors who would help her scale access to coaching across the company.
Sugrue chose Valence, a provider of on-demand AI coaching through a chatbot-style assistant named “Nadia” that includes translation capabilities. When asked directly how she went about rolling the platform out, she replied: “We just tried it.”
Sugrue identified 25 stakeholders across IT, HR and business globally and asked if they would partner with her to test out the platform. She intentionally included people who she felt might be skeptics. The feedback was overwhelmingly positive, which gave Sugrue a cross-organizational team of champions to make the business case for her. A big selling point was that global partners had a coach speaking to them in their native language.
Before the broader rollout, Sugrue moved to get the company’s HR business partners on her side. Again, she intentionally chose people who she felt would be champions and who would be skeptics. She defined strict boundaries between the tool’s role and the part HR business partners would play and framed Nadia as a personal assistant that would free them to focus on complex issues.
“We don’t want the AI coach to ever overstep the boundaries where a real HR person needs to be involved,” Sugrue said.
A company-wide rollout followed, bringing Nadia to 22,000 employees globally at the same time. Sugrue embedded Nadia directly in work platforms like Microsoft Teams to help coach people through “moments that matter” — an employee about to ask for a raise or a manager who needed to have a sensitive conversation. Sugrue said the platform removed barriers of time, language and accessibility as a result.
A Formula to Remember
The software isn’t why case studies like AGCO’s succeed. It’s the prioritization of the human side of adoption that set them apart.
“Technology is the easiest to overcome. The human behavior side of [AI adoption] is where you get the magic or where you get the biggest detractors depending on how you play this,” said IBM CHRO Nickle LaMoreaux.
“AI transformation is about strategy, technology and change,” said Breitfelder. His advice for the audience was to spend $5 on change management initiatives for every $1 spent on technology. His firm, Apollo Global Management, used a $1 to $1 ratio the previous year before switching to the 5:1 ratio.
That kind of budget may sound extravagant. But speakers were quick to differentiate AI adoption from previous technology waves. Where an intranet is a passive tool, the learning and feedback cycle AI operates on creates a cognitive loop with people that demands constant adjustments. People also fear its effects on their jobs and futures — and this is on top of the already prevalent change weariness. Without the kind of investment in the change management, behavioral adoption and coaching employees Breitfelder advocates for, AI investments will result in sunken costs and just as importantly, loss of potential.
Words of Caution: Threats to Mastery and AI Brain Fry
Breitfelder notably included a caveat in his vision for coaching’s “golden age” — if we play our cards right. A big part of that comes in the design of the tools and in thoughtful implementation.
The fear of AI short-circuiting learning came up in multiple contexts with the warning: AI cannot do our thinking for us.
AI acts as an intensity and volume multiplier, resulting in AI brain fry. AI adds to our mental loads by increasing our capacity to take on more work. Adding to this is the work we do to clarify and clean up AI outputs. Hogan Assessments’ Josh Rich likened agents to having colleagues sprinting in and out of your office all day with updates, PowerPoints, questions and demands.
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Left unchecked, AI can also end up extending our work days. Alex Haitoglou, founder and CEO of AI skills-training and coaching platform Ovida, called his own experience getting lost in a super productive moment with AI an “AI Vampire,” acknowledging that he catches himself so fully immersed that he loses time.
AI’s design, specifically in the learning and development capacity, is another area of concern.
Cognitive psychologist Robert Bjork coined the term “desirable difficulties” in 1994. Rich used the analogy of a tree to explain the concept: trees need wind to grow stronger. In the same way, people need what Rich called productive struggle — the effort, persistence, critical thinking, even getting “painfully stuck,” it takes to engage with challenging tasks — to develop deeper understanding and mastery. Any AI tool used in learning and development therefore must be designed to challenge users, not default to supplying answers and affirming existing positions.
“You don’t want something to just hand you answers. There’s definitely choice when to give information and when to ask a really good coaching question,” agreed Haitoglou. While he maintains that it’s up to humans not to offload all cognitive effort to AI, he also acknowledges platforms should be designed to support them in that effort.
One of the hallmarks of this crop of AI tools — not specific to coaching tools — is that they optimize for effortless convenience. If vendors design AI coaching to eliminate friction, the risk is employees become passive consumers of answers rather than active, critical thinkers, with downstream effects on professional growth and productivity.
The Ultimate ROI Isn’t Productivity
The ultimate result of this golden age of coaching, should it come to fruition, isn’t that more people have access to coaching. It’s the results that coaching can produce.
“I hope we’re not talking about productivity gains only, but about a more healthy workforce, emotionally and physically. A workforce with more whitespace where the next big idea comes from. And better relationships between people,” said Prudential Financial’s Chief People and Experience Officer, Vicki Walia.
At a time when companies struggle to identify strong measurements for AI effectiveness, Walia’s comment points to a potential solution that extends to AI use beyond coaching: how deeply we cultivate human capability.
The best coaches specialize in doing exactly this. If AI coaching succeeds in expanding the foundation, as Tavis envisions, the result will be a workforce that will indeed be more productive. But more to the point, they will be more effective — provided we play our cards right.
Editor's Note: How else is learning and development adapting?
- Learning and Development Needs a Reset — We need to evolve L&D from telling and teaching, to activating new skills, capabilities, habits and behaviors.
- Why Your Development Investment Isn't Becoming Capability — Access to training doesn't equal adoption. Three conditions can change whether a development investment will deliver results.
- AI Can Democratize Coaching and Improve Outcomes. But There's a Catch — AI can democratize access to coaching and support L&D at scale. But it also lacks empathy and connection. The solution may be a blended approach.