ICYMI: The future of learning arrived early- 8 leaders predict what's next for 2026
ICYMI: Communicating L&D Value Through Storytelling
Challenge Accepted #7
December 10, 2025 | Hosted by The Learning Table & Juno Journey
On the brink of 2026, the Learning Table community gathered for a fast-paced, one-hour experiment:
8 speakers. 5 minutes each. One big question: “What will learning look like in 2026?”
Hosted by Klil Nevo, Head of Community at The Learning Table (powered by Juno Journey), the session blended sharp predictions, real use cases, and a very human look at AI, data, and change.
Here’s a recap you can share as a post-webinar article, with a spotlight on each speaker.
Eric Grant – Mapping Workplace DNA: L&D as the CRISPR of Behavior
Eric Grant, Learning Product Support Lead at Figma, opened with a bold prediction: 2026 will be the year workplace DNA is fully mapped – and L&D will either own it or become irrelevant.
Eric described a wave of tools (like Windmill and data-rich platforms from Microsoft, Google, Salesforce, Slack, and more) that can already:
- Pull signals from tools we use every day – email, docs, Slack, Notion, Figma, CRM
- Measure how we work: time in meetings, frequency and tone of messages, feedback given, collaboration patterns, and how often people actually use AI tools.
For the first time, this creates a behavioral “genome” of how teams work.
Eric’s core idea:
L&D needs to act like CRISPR – not rewriting the whole genome, but making targeted edits to behavior:
* How we give feedback in this company, not in theory
* How we communicate, collaborate, and structure days
* How managers lead in this culture, with this data.
Two big shifts he sees for 2026:
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Radical Contextualization
No more generic “feedback trainings.”
Instead: “Here’s how feedback works here – based on how we actually behave and how leaders want us to behave.” -
Measured, Mapped Impact
L&D will be expected to prove: “We saw X in the behavioral data.” “We designed Y interventions.”
“Here’s how we shifted the DNA over time.”
Eric’s warning and invitation were clear:
This level of data is our biggest opportunity – and maybe our last big chance to prove L&D is a strategic behavior-change lever.
Ari Paskoff – Reflection as the Cheapest Performance-Enhancing “Drug”
Ari Paskoff, Senior HR Business Partner & Learning Experience Lead at Cognitive, took the conversation inward.
Framed by Michael Jackson’s “Man in the Mirror” and Mulan’s “When will my reflection show…”, Ari argued: In 2026, the differentiator won’t be who AI has – it’ll be who has better reflection.
He told the story of a manager who almost skipped a leadership deep-dive session because she was “too busy.” After a simple “Wins, Wobbles, and Wonderings” reflection exercise, she realized:
- She had new ideas for structuring upcoming performance reviews
- Her team of four would now have sharper, more meaningful conversations
- That single hour of reflection would ripple through six months of performance.
Then he had the group do it live:
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20 seconds – Think of a recent win.
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20 seconds – Extract the key learning from that win.
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15 seconds – Turn it into one sentence and drop it in the chat.
The flood of insights that came back proved his point: AI can generate content, but it can’t make meaning for us.
Ari’s thesis:
- Reflection is not a luxury anymore – it’s a performance system.
- It’s also the cheapest “performance-enhancing drug” we have.
- L&D’s value in 2026 will lie in building: reflective habits for individuals, Reflective rituals for teams, and reflective practices at the org level.
“If we don’t teach people how to learn from their own experience, it doesn’t matter what’s in our tech stack.”
Hana Zacay – Leadership Breakthroughs Happen In Between the Programs
Hana Zacay, founder of LeaderIs Consulting and a leadership development expert for first-time managers, focused on a simple truth: Leadership doesn’t wait for your next offsite.
She contrasted classic leadership development:
- multi-day bootcamps, offsites, and workshops
- great for connection and trust
- but limited for the messy, daily moments where leadership is actually tested.
In reality, feedback moments appear and disappear quickly, difficult conversations pop up between 1:1s, and first-time managers face daily dilemmas with no one on the call.
Hana calls this space “the in-between”, and she believes 2026 will belong to the organizations that learn to support managers there.
Her prediction: We’ll see more AI-powered, personalized, in-the-flow support for managers:
- guidance on a tough conversation right before it happens
- Suggestions for action based on today’s challenge
- micro-journeys that evolve over the year.
Her challenge to the audience was beautifully practical:
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Identify your #1 leadership challenge right now.
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Ask your AI tool: “What’s one small step I can take today to get better at this?” and “Build me a simple weekly practice for the next year.”
Even 10 focused minutes a week becomes 53 meaningful moves a year toward better leadership.
In 2026, leadership development will be less about big programs and more about what happens in the in-between.
Ofer Kenig – “Enable the Enablers” and Focus Your AI Bets
Ofer Kenig, Strategic Technology Leader at AppsFlyer, zoomed in on a question CEOs will increasingly ask: “We’ve invested in AI tools, training, pilots… so where is the impact?”
He was candid about two realities:
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You can’t train hundreds or thousands of employees on tools that change every two weeks.
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Not everyone needs the same AI skills.
Instead of trying to “AI-train everyone,” AppsFlyer chose to “enable the enablers.”
Their approach:
1. Identify Strategic Partners:
>> Sales Ops, CS Ops, Enablement, Business Applications, IT
>> Train them deeply and turn them into AI Champions.
>> Form an AI Ops Committee that meets regularly and drives adoption.
2. Model the Skills That Really Matter. They built a model to define:
>> Which AI skills are critical
>> Which roles need which skills
This created clarity and focus for both leaders and L&D.
3. Launch the AI Builders Program
Using the Pareto principle (20/80), they hand-picked the ~20% of employees likely to create 80% of AI impact.
The program did not just teach tools. It taught how to analyze business processes, spot bottlenecks, and design and implement AI assistants/solutions for real use cases.
The results?
Roughly 78% of the most impactful AI solutions came from the very people selected and trained in this Builders Program.
Ofer’s three takeaways for 2026:
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Enable the enablers.
Partner with the teams that can really move AI adoption. -
Focus your efforts.
Stop training everyone at the same level; find your 20% who drive 80% of the impact. -
Measure business value, not just completions.
In an AI world, impact beats attendance.
Dor Nachshoni – From Fear to Friendship: The Rise of Hybrid Human + AI Teams
Dor Nachshoni, CEO & Co-Founder of Juno Journey, framed 2025 as: “The year of fear and experiments.”
Looking back at global data, he highlighted:
- Employees worried about job loss
- Companies are playing with AI in small, fragmented pilots
- Fewer than 10% of organizations are truly scaling AI agents.
Most employees, he said, were “Playing with AI in low-impact tasks – curious, messy, hesitant… but not yet transformative.”
His prediction for early 2026:
We’re moving from fear to friendship. Agents will take on the heavy lifting of L&D ops: creating courses, checking knowledge, summarizing reports, answering employee questions
L&D pros won’t be replaced – they’ll guide and govern these agents.
But Dor went further:
Every employee will increasingly work as a “hybrid team”: human + AI agents supporting their performance and growth.
In that world:
- Learning becomes embedded in performance, not separate from it.
- Development is continuous and contextual, not tied to annual reviews.
- “Courses” become bite-sized, in-the-moment learning nudges triggered by real work.
For Dor, the future is not just AI-powered; it’s context-powered:
“The value of AI doesn’t come from the agent itself, but from how deeply it understands the employee, the workflow, and the business.”
“AI won’t replace L&D. 2026 is the year AI finally unlocks L&D – and the people in this (virtual) room will lead that shift.”
George Boone – Building Resilience in a World of Constant Change
George Boone, Director of Organizational Effectiveness & Talent Management at Mitratech, brought the conversation back to human nature and resilience.
He drew a critical distinction: Change is situational – a new tool, a reorg, a new boss.
Transition is psychological – how people internally process and adapt.
Using William Bridges’ transitions model and Elisabeth Kübler-Ross’ change curve, George reminded everyone:
- People move through stages like shock, denial, resistance, exploration, acceptance, and commitment.
- The shape of that curve differs, but everyone rides it.
His key message: In 2026, with AI accelerating change, we must double down on our humanness.
That means:
- allowing people to struggle, question, and learn
- giving space to fail safely
- helping teams move out of the “neutral zone” – that pit between detachment and exploration – without rushing or ignoring it.
He also linked stress and performance: Too much stress → panic, burnout, chaos. Too little → boredom, disengagement.
The sweet spot is “eustress” – a productive stretch that fuels growth.
For L&D and leaders, his invitation was:
- Control what you can control.
- Take change one step at a time, not by “boiling the ocean.”
- Pay attention to your own transition curve and to your team’s.
His closing question:
“Looking back at 2025, what transitions will you choose in 2026 to tap into more of your potential?”
Melinda Stallings – The PALM Foundation: Preparing Humans for AI
Melinda Stallings, organizational effectiveness psychologist, executive coach, and founder of The Positive Consultant, tackled a hard truth:
“95% of AI implementations are failing – not because of the tech, but because of the people system it’s landing on.”
She told the story of a global company that invested millions in a new AI system, had brilliant tech and solid strategy, but unprepared people: employees didn’t understand why, managers weren’t equipped to lead the change, and there was no psychological safety to say “I don’t get this.”
Momentum collapsed, not due to AI failure, but human unreadiness.
Out of many such conversations, Melinda developed and unveiled her PALM Foundation for the first time:
P – Prepare | A – Align | L – Lift | M – Multiply
Together, these pillars form the human capability foundation AI depends on.
P – Prepare (the Translators)
Give people clarity, communication, and purpose.
Prepared people don’t fear the future – they accelerate it.
A – Align (the Balancers)
Align culture, values, ethics, and expectations so AI adoption feels human, not threatening.
L – Lift (the Builders)
Lift core human capabilities: communication, EQ, critical thinking, adaptability, conflict skills, resilience. When you lift human capability, technology rises with it.
M – Multiply (the Amplifiers)
Leaders model, teams reinforce, micro-learning spreads.
What you repeatedly multiply becomes your culture – and culture decides your AI future.
Her question to organizations:
“Juno Journey has powerful AI for L&D – but do you have the human foundation to actually use it well, the first time and every time?”
Matt Donner – Three Roads, Two Bridges, and L&D’s New Job
Finally, Matt Donner, Strategic L&D Partner at Credit Karma (and the resident musician in the lineup), closed by weaving the themes together.
He summarized the big lines he heard:
>> Data as existential opportunity for L&D (Eric)
>> Reflection as human differentiator (Ari)
>> Breakthroughs between programs (Hana)
>> Focused AI enablement (Ofer)
>> Hybrid human + AI teams (Dor)
>> Resilience through change (George)
>> Human foundations for AI (Melinda)
Then he offered a metaphor: Three roads. Two bridges.
The Three Roads – For L&D and Learners
For L&D teams:
Left road:
Keep doing everything the old way – ADDIE, long cycles, SME-heavy courses that may or may not change behavior.Middle road:
Use AI for efficiency – some prompt design, some GPT building, some automation – but stay in the crowded “everyone’s doing it” lane.Right road:
Tackle complex, integrated AI systems – agents, RAG, orchestration – the steep, stormy, “electric” road where few are yet walking.For learners:
Left road:
Stick to old methods, ignore AI, stay “safe” but fall behind.Middle road:
Basic AI adoption – the 10% of people who use the tools a bit.Right road:
Advanced enablement – deeply integrating AI into how they work and grow.The Bridges – L&D’s New Role
Matt’s argument: L&D has to walk all three roads – and then build bridges for others.
Our work shifts from building only courses and programs to designing systems, rubrics, and architectures that let people: interact with AI as a sounding board, learn through live AI-driven experiences (audio, video, conversation), and move from basic to advanced AI usage safely.
He sees early 2026 as an “AI + HI” phase:
- AI helps build content, knowledge lakes, and grounded experiences
- Humans stay in the loop to guide quality and ethics.
Later in 2026 and beyond, he expects more AI-driven, prompt-based learning experiences, with L&D professionals focusing more on defining rubrics, constructing guardrails, and architecting the systems
…while AI helps build the tools themselves.
“It’s about using the tools to build the tools – and helping learners choose which road they want to walk, with bridges ready when they’re ready to cross.”
The Big Picture: What 2026 Learning Might Actually Feel Like
Across all 8 perspectives, a clear picture emerges for 2026:
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More data, better measurement.
L&D will have unprecedented behavioral data – and will be expected to prove impact.More reflection, more meaning-making.
AI can generate, but humans must interpret, reflect, and decide.More learning in the flow of work.
The real magic happens between programs – in the in-between moments.More focused AI enablement.
Not “AI for everyone, everywhere,” but targeted enablement of enablers and builders.More hybrid human + AI teams.
Every employee is supported by AI agents that understand context, goals, and work.More emphasis on resilience.
Change is constant; how we navigate transitions will matter as much as tools.More investment in human foundations.
Culture, values, psychological safety, and leadership will make or break AI success.And a new role for L&D.
Less “course factory,” more architect, orchestrator, and bridge-builder.
If you attended, this article can help you revisit and digest the insights.
If you missed it, consider this your invitation to reflect:
What road are you on today – and which bridge do you want to start building for 2026?