Where Is AI Good Enough? What Senior HR Leaders Are Really Saying About AI and Executive Coaching

Berman Leadership Development hosted a roundtable of senior HR leaders in Boston on May 28, 2026 — exploring where AI executive coaching delivers real value, and where human coaches remain essential.

The conversation about AI and executive coaching is everywhere. But most of it stays superficial — centered on demos, press releases, and predictions.

What’s been harder to find is an honest, peer-to-peer conversation among senior HR leaders about what’s actually happening inside their organizations.

That’s exactly what Berman Leadership Development set out to create.

On May 28, 2026, we hosted a roundtable lunch at Del Frisco’s in Boston’s Seaport District. The question we brought to the table: Where is AI coaching actually good enough — and where does the human still matter most? What followed was one of the richest, most grounded conversations we’ve had on this topic. Here’s what we took away.

The Market Is Earlier Than You Think

If you’ve been feeling behind on AI, you’re in good company. One of the most consistent themes across the table was that the gap between interest and actual implementation is larger than most people admit publicly.

Most organizations represented in the room were still in early exploration mode — anchored to familiar tools like Microsoft Copilot rather than dedicated coaching solutions. The business case for AI coaching is often being driven by cost pressure and scale needs, sometimes before organizations have fully mapped what AI can and can’t do well.

The leaders who are doing this well aren’t rushing to deploy — they’re asking better questions first. What problem are we really solving? What does quality look like at scale? Where does AI add genuine value, and where would it be a shortcut we’d regret?

Naming the gap honestly — between the hype and the reality — is where good strategy starts.

Where AI Is Genuinely Strong: Scale, Practice, and Access

When the conversation turned to where AI coaching is delivering real value, there was strong consensus. AI shines when the goal is scale, structure, and repetition — and it’s opening doors that were previously closed.

Some of the strongest use cases discussed:

Skill-Building and Practice

AI tools that allow leaders to role-play difficult conversations, get real-time feedback, and iterate quickly are genuinely valuable. The ability to practice a hard conversation ten times before having it in real life — without burning out your coach — is something that simply wasn’t possible before.

Performance and Career Coaching at Scale

For mid-level leaders and managers, AI coaching tools can provide consistent, accessible support that many organizations simply couldn’t afford to offer broadly before. The cost-to-access equation is compelling.

Democratizing Coaching Access

Coaching has been reserved for senior leaders. AI is changing that. Organizations can now extend meaningful developmental support to a much wider population.

The excitement around using AI wasn’t theoretical. People in the room had used AI to roleplay difficult conversations and were genuinely impressed by the quality of feedback — things like where they could have shown more empathy, asked better questions, or given clearer guidance. “You can do that all day long,” one attendee noted. That kind of repetition and feedback loop? You can only get that from AI.

Where the Human Edge Wins: Executive Coaching Is Different

Here’s where the conversation got nuanced — and important.

The group was equally clear that the executive coaching context is different in kind, not just in degree. At the most senior levels of an organization, the work of coaching isn’t primarily about skill-building. It’s about navigating complexity, trust, relationships, and judgment in high-stakes environments where the right answer is rarely obvious.

The areas where senior leaders still need human coaches:

Organizational Politics and Interpersonal Dynamics

The web of stakeholder relationships, history, and context at the executive level requires a coach who knows the landscape — not just a tool processing inputs.

Emotional Complexity and Genuine Trust Over Time

Processing the emotional weight of senior leadership — the isolation, the pressure, the hard decisions — requires a relationship built on real trust and confidentiality. That doesn’t happen with an algorithm.

Nuanced Business Judgment

Collaborative thinking that draws on years of pattern recognition, context-sensitivity, and the lived experience of navigating organizations is still deeply human work.

There are emerging AI tools that listen across company communications and surface patterns — tools that can give coaches richer inputs than they’ve ever had before. But the relationships in which that insight gets applied? That remains human work.

The frame the group kept returning to was augmentation, not replacement. AI can make great coaches better by freeing them to focus on the relationship and the insights — not the note-taking or the between-session check-ins.

Trust, Privacy, and Governance: The Real Adoption Question

If there was one theme that cut across every level of the conversation, it was trust — and how fragile it can be.

Several practical realities surfaced that any organization thinking about AI coaching needs to take seriously:

Group-Level Data, Not Individual Tracking

Leaders are far more comfortable with aggregate insights — what patterns are we seeing across our leadership population? — than with the idea that individual coaching conversations are being analyzed and reported up the chain. The line between insight and surveillance matters enormously.

Knowing the Source Changes How We Receive the Message

Here’s a human reality worth naming: research suggests that people can receive a piece of feedback, find it useful and well-put — and then feel differently about it the moment they learn it came from AI rather than a person. It’s not that the feedback changed. It’s that trust is relational, and we’re wired to weight human judgment differently than machine output. This isn’t a reason to hide AI’s role — in fact, transparency is essential. But it is a reason to be thoughtful about how AI-generated insights are introduced, framed, and contextualized. Done well, that transparency builds confidence. Done poorly, it quietly undermines the very feedback you worked to deliver.

Regulated Industries Have Extra Complexity

Organizations in financial services, pharma, and biotech face compliance and regulatory layers that make AI adoption especially careful territory.

The Governance Question Is Still Live

Who owns AI coaching in your organization? Is it HR? IT? Legal? The C-suite? In most organizations right now, the answer is: it’s complicated. And that ambiguity slows adoption — sometimes for good reason.

New Directions: Hybrid Models and Change Leadership

If there was a headline from the room, this was it: the conversation has moved from “AI vs. human” to “what’s the right architecture?”

The organizations getting this right aren’t choosing between AI and human coaching — they’re designing hybrid models that put AI where it’s strong (scale, practice, consistency, access) and protect human coaching where it’s irreplaceable (executive-level complexity, trust, judgment, and relationship).

And critically — the leaders in the room agreed that implementing this well is fundamentally a change management challenge, not a technology challenge. The organizations that are struggling aren’t struggling because they picked the wrong tool. They’re struggling because they didn’t bring the right people along — didn’t build the internal alignment, didn’t address the fear and the uncertainty, didn’t create the governance structures that allow people to trust the process.

The organizations that do this well will be the ones that treat AI adoption as a leadership challenge — one that requires the same intentionality, communication, and human-centered thinking as any other major organizational transformation.

What’s Next: The Conversation Continues

This lunch was about getting a room of smart, experienced HR leaders together to think out loud — to peel back the hype and get honest about where things actually stand.

What struck us most was the energy. There is genuine curiosity, genuine momentum, and a real hunger for peer-level connection around these questions. The conversation is just getting started.

Here’s what we’re planning next:

• A webinar focused on leading AI adoption as a change challenge, not just a tool decision
• A dinner gathering tied to the Life Sciences East conference in October, for those who want to go deeper
• Continued thought leadership and resources at bermanleadership.com

If any of these themes sparked a question you’re wrestling with in your own organization, we’d love to hear it. Reach out anytime at scott@bermanleadership.com.

And if you’d like the AI leadership framework materials referenced at the table, just let us know — we’ll send them your way.

Berman Leadership Development partners with organizations in financial services, pharma, biotech, technology, and healthcare to develop high-stakes leaders through executive coaching, leadership development, and organizational change. We’re thinking hard about what AI executive coaching means for all of it.

Follow us on LinkedIn.