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Precisely

<div style="font-family: 'Calibri', 'Candara', 'Segoe UI', 'Optima', Arial, sans-serif; color: #333; line-height: 1.6; max-width: 800px; margin: auto; font-size: 1.1rem;">
<blockquote style="border-left: 4px solid #990000; margin: 20px 0; padding: 10px 20px; background-color: #f8f9fa; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"AI doesn't need you to change who you are, but it's going to show you clearly who you've been." -- <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a></blockquote>
At the ELE Spring Conference on May 21st, keynote speaker <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a> of Precisely opened with a challenge most AI rollout plans never get to: adoption doesn't stall because of the tools. It stalls because the tools force a reckoning with professional identity — who people believe they are at work, where they hold authority, and what they're still worth when AI can do 60% of what used to define them. Until people leaders address that layer directly, no amount of tool training moves the needle.
The identity gap no one is putting on the roadmap
Most organizations are treating AI adoption as a change management problem. Marty Murrillo reframed it as an identity problem — and the distinction matters enormously for how people leaders show up.
Three things are being disrupted simultaneously: the work itself, the tools people use to do it, and the workflows that connect them. Best practices are outdating every 6–12 months. Interfaces are changing weekly. The ground keeps shifting — and employees are privately asking questions their managers haven't been invited into yet.

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"What am I here for? What do I still uniquely add? Where do I still make decisions?" -- <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a></blockquote>
These aren't engagement survey questions. They're the internal monologue of a workforce negotiating its own value in real time. People leaders who skip this conversation and go straight to tool adoption are solving the wrong problem.
Leaders in the conversation
The May 21st live discussion brought together people leaders and senior talent professionals engaging directly with Murrillo's framework for identity-driven adoption. The room wasn't debating whether AI would change work — it was grappling with the harder question of how to lead people through a shift that touches role, value, and authority all at once.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 30px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">What's actually changing — and what stays human</h3>
Murrillo was direct about where the real capability shift lands. Task-based expertise — the work AI can increasingly replicate — is no longer a stable identity anchor. What remains distinctly human is judgment, ethics, and the ability to ask whether something should be done, not just whether it can be.

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"What stays with you? Judgment, ethics — thinking about whether this is the right thing to do." -- <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a></blockquote>
This is the reframe people leaders need to be making explicitly with their teams. The goal isn't to convince employees that AI won't change their roles. It will. The goal is to help them anchor their professional identity in the work AI cannot do: reading a room, sensing what the numbers aren't showing, holding the relational and ethical weight of decisions.
That's the capability shift — from output production to strategic stewardship. And it requires leaders to model it, not just message it.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">The leader's own identity shift comes first</h3>
One of the sharpest signals from Murrillo's keynote: you cannot guide a workforce through this change if you haven't moved through it yourself.
The shift from knowing answers to asking better questions. From task expertise to judgment and ethics. From holding authority to sharing agency with AI. These are internal moves — and leaders who skip them end up communicating a roadmap they haven't personally walked.
As highlighted during the live discussion:

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"Leaders can't just talk the talk. They have to walk it too." -- <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a></blockquote>
Visible leadership behavior is the adoption signal the workforce is reading most closely. Executives who say "I don't know, let's try it" — and mean it — are doing more for adoption than any enablement program run without that cultural backing.
Psychological safety isn't a culture initiative in this context. It's an operational condition for AI adoption. Teams need permission to experiment, fail publicly, and keep moving. That permission has to come from the top — and it has to be behavioral, not just stated.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">Clarity about decision rights is the hardest thing to provide — and the most valuable</h3>
One of the most practical signals from the live discussion: ambiguity about where AI stops and humans start is feeding the authority anxiety that stalls adoption faster than any tool friction.
Employees aren't just asking what AI can do. They're asking where they still get to decide. Without explicit answers, they default to anxiety or avoidance — and people leaders read that as resistance when it's actually a reasonable response to unclear boundaries.
Defining decision rights — which calls stay with humans, which route through AI — isn't an IT governance question. It's a leadership clarity question. And it belongs on the people leader's agenda, not just the tech team's.


<hr style="border: 0; border-top: 1px solid #eee; margin: 40px 0;" />

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-bottom: 15px;">What to try next</h3>
<ol style="padding-left: 25px; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">
 	<li style="margin-bottom: 15px;">Run the Three Bucket Exercise with your team. Ask each person to sort their top 12 tasks into three buckets: AI does alone, human + AI together, and uniquely human. It moves the conversation from abstract anxiety to concrete analysis — and gives individuals agency over their own role evolution.</li>
 	<li style="margin-bottom: 15px;">Use the 50% threshold as a workforce planning signal. If more than half of someone's tasks land in the "AI does alone" bucket, that's a proactive role conversation — not a performance issue. Getting ahead of it builds trust and preserves the talent you'll need for the work that remains distinctly human.</li>
 	<li style="margin-bottom: 15px;">Make your own identity shift visible this week. Name publicly — in a team meeting, a one-on-one, or a leadership communication — which of the three shifts you're personally working through. Leaders who model the internal work build more credibility for the change than those who only communicate the strategy.</li>
</ol>
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Bring your work into the room
If this connects to real work you are trying to move forward, bring it into the ELE community. Share the challenge, compare signals with trusted peers, and leave with practical next moves you can use.
Submit My Challenge Now: <a style="color: #0056b3; font-weight: bold; text-decoration: underline;" href="https://www.ele.llc/faqs/share-top-of-mind-talent-challenges">https://www.ele.llc/faqs/share-top-of-mind-talent-challenges</a>

</div>
</div>

Identity Drives AI Adoption — or Stalls It

Engagement &amp; Culture

Digital &amp; AI

marty.murrillo

psychological safety

workforce planning

human AI collaboration

change leadership

AI Implementation

AI Adoption

leadership behavior

manager enablement

wise2026

People Leaders

insights-wise-2026

professional identity

workforce mindset shift

role redefinition

decision authority

practical next moves

ELE Spring Conference

Executive Learning Exchange (ELE)

Rothy's

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.

<h6 data-path-to-node="2">The Core Narrative: Addressing Structural Crisis and Strategic Mandate</h6>
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.

<blockquote data-path-to-node="3,0,1">
"Work is evolving faster than roles, causing heartburn around antiquated job structures." -- <a href="https://www.ele.llc/members/megan-bickle" target="_blank" rel="noopener">Megan Bickle</a>, Rothy's
</blockquote>
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.

<h6 data-path-to-node="6">Key Takeaways for Senior Talent &amp; Learning Leaders:</h6>
<ul data-path-to-node="7">
 	<li>
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.
</li>
 	<li>
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.
</li>
 	<li>
L&amp;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.
</li>
 	<li>
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.
</li>
</ul>

<hr data-path-to-node="8" />

<h6 data-path-to-node="9">The Strategic Mandate: Linking AI to Business Value</h6>
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:

<blockquote data-path-to-node="3,0,1">
"Don't just follow the tech for the tech's sake; it must be linked to a business need." -- <a href="https://www.ele.llc/members/chris-dunford" target="_blank" rel="noopener">Chris Dunford</a>, Aon
</blockquote>
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 <a style="font-size: 16px; background-color: #ffffff;" href="https://www.ele.llc/members/matt-donovan" target="_blank" rel="noopener">Matt </a><a href="https://www.ele.llc/members/matt-donovan" target="_blank" rel="noopener">Donovan </a>reinforced, this is the outcome talent leaders should design for:

<blockquote data-path-to-node="3,0,1">
"AI takes on tasks to enable humans to move up the value chain."
</blockquote>
This is not a philosophy—it’s the benchmark against which every AI-enabled role redesign, learning investment, and manager capability should be measured.


<hr data-path-to-node="15" />
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:

<ol start="1" data-path-to-node="18">
 	<li>
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.
</li>
 	<li>
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.
</li>
 	<li>
Reallocate L&amp;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.
</li>
</ol>
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.

2025 in Review, 2026 in Focus: Defining Talent Priorities for the AI Workforce

future of work

Strategy

Future of Work

dirk.tussing

tracey.wik

upskilling

azizeh.constantinescu

talent development

talent management

learning &amp; development

matt.donovan

Talent Strategy

marsha.love-morrow

employee experience

reskilling

matt.sernaker

megan.bickle

HR transformation

HR leadership

Business Alignment

sara.fitzgerald

AI &amp; Workforce

angelica.janina.stilling

4Q2025

cindy.pinkstaffmiller

L&amp;D strategy

organizational design

terresa.bubbers

ali.glaser

sam.amelio

AI governance

2026 planning

chris.dunford

dustin.brewer

manager readiness

job architecture

executive learning

2026 priorities

Froedtert ThedaCare Health

Journyz

Goal: In this 45-minute breakout, participants will experience a taste of the ELE Work/Life Blueprint and reflect on how design thinking can make reskilling personal, scalable, and business-aligned.

Every HR leader knows reskilling at scale is an enterprise priority—but traditional, one-size-fits-all approaches rarely deliver impact. The Work/Life Exchange Blueprint introduces a five-step, design-thinking framework that makes reskilling personal, practical, and scalable:

1️⃣ Discover — map where energy, skills, and growth opportunities intersect.

2️⃣ Design — generate multiple “what’s next” scenarios, short- and long-term.

3️⃣ Prototype — test small, low-risk skill applications that generate real data.

4️⃣ Exchange — share insights, borrow ideas, and refine through peer feedback.

5️⃣ Blueprint — tell your story, build your support team, and co-create a living plan (not a static PDP).

Grounded in design-thinking principles from Designing Your Work Life by Bill Burnett and Dave Evans, this ELE-built model simplifies reskilling at scale by moving from HR-led programs to frontline-owned growth — turning learning into impact.

📚 Related Reading: <a href="https://www.ele.llc/members/bookshelf/designing-your-work-life" target="_blank" rel="noopener noreferrer">Designing Your Work Life on ELE’s Bookshelf</a>

🔁 <a href="https://docs.google.com/presentation/d/1qFs__kIJsCLH6ynAeNopOsz6PHEpub9ntpAmvuJt588/edit?mc_cid=e7686c688f&amp;mc_eid=621cbc8540&amp;slide=id.p1#slide=id.p1" target="_blank" rel="noopener noreferrer">ELE Executive Innovation Sprints Proposal</a>

What’s Next: Following this initial ideation, on <a href="https://www.ele.llc/events/reskilling-128" target="_blank" rel="noopener noreferrer">November 14th we’ll host a virtual exchange to refine business requirements</a> before recruiting 4–6 members for our first Solution Sprint.

🔄 ELE Executive Innovation Sprint: Simplifying Reskilling/Upskilling to Scale | Turning Upskilling into Impact

Integrated Talent Management

talent mobility

design thinking

newton.moore

performance improvement

janice.simmons

CHIE2025

Strategic HR

deepa.kartha

integrated talent

reskilling at scale

upskilling strategy

business aligned learning

practical framework

capability gap

skills mapping

The Regis Company

The traditional L&amp;D operating model is obsolete. Simply rolling out more content won't solve the capability gaps driven by rapid technological change. In this crucial keynote, Mike Vaughan delivers critical, data-backed research on the irreversible shift from a content-first to a skills-first learning architecture, driven by AI and comprehensive talent data.

Senior leaders will move beyond generalized trends to understand the specific L&amp;D 3.0 framework necessary for enterprise transformation. You will gain actionable insights on:
<ul>
 	<li>The Skills-First Imperative: Why merely having a skills taxonomy isn't enough. Learn how to leverage AI-driven skills data for proactive talent planning, enabling true talent mobility and a responsive learning ecosystem.</li>
 	<li>From Reactive Training to Proactive Capability: Discover how high-performing L&amp;D functions are using data to anticipate skill needs before they become business-critical gaps, moving L&amp;D from a service center to a strategic capability builder.</li>
 	<li>The Power of AI-Enabled Personalization: Review compelling research that validates the exponential increase in learner engagement and performance when AI is used to deliver personalized and relevant career journeys, not just generic training paths.</li>
 	<li>Measuring Business Impact: Focus on the metrics that matter. Understand how to connect skills development directly to key business outcomes (like customer experience and innovation) to finally prove the strategic ROI of your talent investment.</li>
</ul>
This keynote provides the research and the roadmap to future-proof your L&amp;D strategy, positioning it as the indispensable engine of organizational agility and growth.

How AI is Changing L&D: Research | Skills Data

Analytics

michael.vaughan

organizational agility

skills taxonomy

HR Strategy

Data-Driven L&amp;D

capability building

Strategic L&amp;D

enterprise transformation

skills gap analysis

AI in L&amp;D

AI personalization

skills first architecture

L&amp;D 3.0

talent data

proactive talent planning

learning ecosystem

measuring business impact

ROI of talent

future proofing L&amp;D

BARYONS

By 2030, AI, automation, and data will shape every decision, workflow, and talent strategy—but as this provocative keynote demonstrated, Culture will remain the true, non-replicable driver of performance. This high-energy session, featuring a mystery co-emcee from the AI future, challenged senior HR, Talent Development, and L&amp;D leaders to rethink the organizational model they are building today.

The core message was a powerful strategic call-to-action: The winners of the next decade will be the organizations that solve the human equation behind AI integration.
<h3>The Strategic Questions Leaders Must Answer:</h3>
<ul>
 	<li>What is the New Meaning of "Flourishing"? The keynote used future "what-if" scenarios to ask a fundamental question: In a world where AI handles most cognitive tasks, how do we define and measure human flourishing? The challenge is to make the "good life" accessible to all employees, ensuring work remains a source of purpose, not just output.</li>
 	<li>Building a Culture for the "Unknown": Leaders were pushed to design cultures that thrive on ambiguity, asking: What kind of leadership is required when your most significant competitor—or even a potential new product—doesn't exist yet? The answer lies in fostering psychological safety and prioritizing curiosity over certainty.</li>
 	<li>From Skills to Strategic Conversation: The session highlighted that the future role of the executive is not just to manage people, but to orchestrate high-quality conversations and collaborative problem-solving. This means building a cultural architecture where talent development accelerates both emotional intelligence and strategic discernment.</li>
</ul>
This keynote provided a critical perspective on the organizations we must build today to ensure that by 2030, our culture is a source of sustainable competitive advantage, not a barrier to an AI-driven future.

How Will Culture Drive Performance in 2030 | A Look Ahead: Where AI, Culture, and Performance Intersect

Leadership

Change Management

leadership development

Culture Change

emotional intelligence

competitive advantage

organizational culture

AI integration

Ethical AI

michael.hruska

performance driver

human flourishing

strategic discernment

cognitive tasks

high quality conversations

collaborative problem solving

organizational model

baryons.aimentor

This live discussion with experienced talent executives, mostly ex-Accenture, made one thing clear: skills are more than a talent metric—they’re the language of business capability. When viewed as data, skills connect individual growth to enterprise agility, shifting the conversation from headcount to capability management.
<a href="https://www.ele.llc/members/craig-friedman" target="_blank" rel="noopener">Craig Friedman</a> reminded us that:

<blockquote data-start="1100" data-end="1220">
“Skills are both people data and business data. That shift takes us from counting heads to managing capabilities.”
</blockquote>
That single shift reframes how talent leaders partner with the business. Instead of defending headcount, we’re managing capabilities that drive agility, growth, and performance.
But, as Heber cautioned:

<blockquote data-start="1441" data-end="1560">
“Skills data only matters if it’s accurate. Decisions are only as strong as the confidence you have in the data.” -- <a href="https://www.ele.llc/members/heber-sambucetti" target="_blank" rel="noopener">Heber Sambucetti</a>, Skillsoft
</blockquote>
Confidence in your data determines whether leaders trust skills intelligence to shape pay, succession, and workforce planning.
And as Craig warned, complexity is the enemy:

<blockquote data-start="1740" data-end="1840">
“If your taxonomy is exploding, step back. Keep the skill the skill—and separate the context.”
</blockquote>
The conversation didn’t just redefine skills—it revealed what leaders must prioritize to make skills strategy work in practice

<h3 data-start="1972" data-end="1991">Key Takeaways:</h3>
🔹 Skills are strategic currency, bridging individual growth with enterprise capabilities. 🔹 Data quality is non-negotiable—without it, business decisions crumble. 🔹 Start where the business hurts; pilots anchored in real challenges prove value fast. 🔹 Simplicity wins—overbuilt taxonomies collapse under their own weight. 🔹 AI is an accelerant, not a replacement; governance keeps it usable.


<hr data-start="2400" data-end="2403" />

<h3 data-start="2405" data-end="2447">Practical Actions for Talent Leaders:</h3>
✅ Frame conversations with executives around capability, not headcount. ✅ Audit skills data before using it to drive staffing, comp, or workforce plans. ✅ Launch a pilot tied to a pressing business problem to win support and credibility. ✅ Establish governance guardrails early: clear definitions, owners, and refresh cycles. ✅ Use AI smartly—let it speed tagging and content, but apply governance filters.

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</div>
</div>
</div>
</div>
</div>
Skills strategy isn’t about boiling the ocean. It’s about building trust, proving value, and scaling what works—step by step.
Which of these actions feels most urgent in your organization right now? Let’s continue this conversation in the <a href="https://www.ele.llc/idea-exchange" target="_blank" rel="noopener">ELE Idea Exchange</a>.

Skills Are Data: Designing a Strategy for Agility and Growth

jean.ryan

learning and development

maryann.kennedy

talent agility

future skills

skills strategy

skills data

audrey..hackley

HR Innovation

Organizational Growth

Workforce Strategy

craig.friedman

AI in talent development

Workforce Agility

3Q2025

skills-based organization

HR data

skill mapping

talent analytics

talent development strategy

talent intelligence

heber.sambucetti

capability management

skills governance

data quality in HR

business capability

This robust discussion underscored a powerful truth: talent development leaders can no longer afford to wait for lagging indicators to reveal problems. To stay ahead, we must anticipate needs, align talent metrics with strategy, and act before gaps derail performance.
As Matt Sernaker shared:

<blockquote data-start="483" data-end="650">
"Shifting from surveys after the fact to shaping daily experiences turned our lowest-rated hotel into the top performer—and gave everyone a role in improvement."
</blockquote>
And Angelica Stilling reinforced with her systemic view:

<blockquote data-start="715" data-end="864">
"A focused talent scorecard reveals workforce patterns early—speeding time-to-fill, boosting retention, and giving leaders actionable visibility."
</blockquote>
Together, these perspectives highlight a shift in mindset and practice. It’s not just about reporting outcomes—it’s about shaping them. Predictive talent strategies bring business and HR closer together, using early signals to drive accountability, innovation, and measurable results.
When leaders integrate predictive metrics into strategy, they move from reactive firefighting to proactive value creation. And when those metrics are transparent, they don’t just inform decisions—they shape culture, empowering people at every level to own outcomes.


<hr data-start="1423" data-end="1426" />

<h3 data-start="1428" data-end="1450">🔑 5 Key Takeaways</h3>
<ol data-start="1451" data-end="1813">
 	<li data-start="1451" data-end="1519">
Lagging tells you what happened; leading tells you what’s next.
</li>
 	<li data-start="1520" data-end="1595">
Predictive metrics must align with business strategy to gain traction.
</li>
 	<li data-start="1596" data-end="1667">
Sales and DEI examples show how early signals prevent costly gaps.
</li>
 	<li data-start="1668" data-end="1732">
Transparency in data creates ownership and cultural buy-in.
</li>
 	<li data-start="1733" data-end="1813">
Don’t wait for perfect dashboards—directionally correct data drives action.
</li>
</ol>

<hr data-start="1815" data-end="1818" />

<h3 data-start="1820" data-end="1845">✅ 5 Practical Actions</h3>
<ol data-start="1846" data-end="2223">
 	<li data-start="1846" data-end="1921">
Embed predictive metrics into business reviews and strategic planning.
</li>
 	<li data-start="1922" data-end="2000">
Review leading indicators more frequently to allow for course correction.
</li>
 	<li data-start="2001" data-end="2066">
Define measures with executives upfront to secure alignment.
</li>
 	<li data-start="2067" data-end="2132">
Pilot predictive talent metrics in one function, then scale.
</li>
 	<li data-start="2133" data-end="2223">
Share results beyond leadership—use ERGs and employee forums to drive culture change.
</li>
</ol>

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🔮 Predictive talent isn’t just a measurement shift—it’s a mindset shift. By blending culture, data, and foresight, talent development leaders can deliver results that matter most to the business.
📣 How is your organization shifting from lagging to leading indicators? Let’s continue this conversation in the <a href="https://www.ele.llc/idea-exchange" target="_blank" rel="noopener">ELE Idea Exchange</a>.

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