This live discussion provided a necessary strategic pause—reframing 2025, a year when AI acceleration outpaced governance and skills into a clear, action-oriented agenda for 2026, shaped by some of the brightest minds in talent leadership.
The session, which focused on turning 2025's lessons into 2026's impact, moved beyond a simple recap to identify the structural gaps holding organizations back: unclear roles, inconsistent manager readiness, and a lack of skills and governance to match the speed of AI experimentation.
The Core Narrative: Addressing Structural Crisis and Strategic Mandate
The key insight is that AI has exposed profound flaws in organizational design, making the chief priority for 2026 a fundamental overhaul of how we define and manage work itself.
"Work is evolving faster than roles, causing heartburn around antiquated job structures." -- Megan Bickle, Rothy's
This structural crisis demands that the talent function lead the charge in strategic redesign—not as a support function, but as the architect of how work, skills, and AI come together.
Key Takeaways for Senior Talent & Learning Leaders:
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The Structural Work/Role Disconnect is the New Crisis: Work is evolving faster than job architecture, creating real tension around compensation, accountability, and career paths.
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Operational AI Exposes Manager Readiness as the #1 Governance Gap: As AI moves into daily work, inconsistent manager capability—not technology—has become the primary bottleneck.
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L&D's Identity Must Pivot to 'Designer of the Blended Workflow: The talent function must intentionally design how human judgment and AI systems integrate—moving people up the value chain by design, not accident.
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The Future of Work is a Mental Health Design Challenge: The focus is shifting from reactive wellness programs to proactively redesigning work in ways that protect psychological well-being.
The Strategic Mandate: Linking AI to Business Value
The ultimate goal for 2026 is harnessing AI to maximize competitive advantage. That requires moving past technological enthusiasm to disciplined, strategic deployment. As Chris Dunford emphasized, this is the constraint talent leaders must enforce:
"Don't just follow the tech for the tech's sake; it must be linked to a business need." -- Chris Dunford, Aon
This quote serves as the central mandate for any new AI-driven capability investment.
When that constraint is applied, the value proposition becomes clear.
As Matt Donovan reinforced, this is the outcome talent leaders should design for:
"AI takes on tasks to enable humans to move up the value chain."
This is not a philosophy—it’s the benchmark against which every AI-enabled role redesign, learning investment, and manager capability should be measured.
Practical Actions for 2026 Strategic Planning (Where to Start)
To generate the necessary Talent Development Intelligence and address these strategic and human gaps, talent and learning leaders can start with the following actions:
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Launch a Cross-Functional "Deconstruction of Work" Sprint: Start by deconstructing 3–5 mission-critical roles. Map which tasks are best handled by AI versus high-value human judgment to inform Q1 job architecture and skill redesign.
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Measure Manager Readiness for AI Governance (Not Just Usage): Assess managers on their ability to govern, embed, and coach responsible AI use—not just whether tools are adopted.
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Reallocate L&D Resources to the "Three C's": Use AI to clarify role expectations, co-curate third-party content, and customize individual learning journeys—embedding learning directly into the workflow.
These actions shift talent teams from reacting to AI disruption to intentionally redesigning how work actually gets done.
ELE Outlook for 2026: Why Incremental Change Isn’t Enough for How Work Gets Done
As ELE heads into 2026, one signal is already clear: incremental improvements won’t keep pace with the human, structural, and leadership challenges created by AI at scale. The mandate for talent and learning leaders is to shape how work evolves—clarifying job architecture, building practical manager capability for AI governance, and ensuring every technology investment is explicitly tied to business value. By focusing on these priorities, talent and learning leaders can turn the disruption of 2025 into a scalable impact in the year ahead.
