Repsol, EY, and Amazon Are Ready for AI Agents. Is Your Workforce?

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REPSOL, EY, AND AMAZON ARE READY FOR AI AGENTS. IS YOUR WORKFORCE?

AI is entering your workplace — not just as a tool, but as a teammate.

While most HR teams are still focused on rolling out copilots and productivity tools, a bigger transformation is already unfolding: AI agents are redesigning workflows, collapsing traditional hierarchies, and blurring the line between roles, systems, and people.

According to McKinsey:
🔹 Only 1% of companies feel confident in their GenAI maturity
🔹 92% are investing more in 2025
🔹 And employees? They’re using GenAI 3x more than leaders think

The rollout isn’t the challenge.

The real question is: Who’s designing the AI experience? 

Inside this edition

• What employees think about GenAI — and why most feel unsupported

• A six-part framework to redesign AI-powered work from the inside out

• How USAA, Amazon, and Repsol are rethinking L&D for GenAI fluency

• How EY and Waste Management are scaling trust-first AI systems

• A one-page scorecard to assess your AI and learning readiness

• What CHROs must do to move beyond pilots and lead transformation

🗞️ In case you missed it: Shopify tightens AI hiring rules, a judge blocks Trump’s DEI ban (for now), California backs skills over degrees, and Oracle settles a $15.5M labor case.

Read on to discover what’s stalling AI transformation and how HR can unlock the momentum hiding in plain sight.

SPREAD FOR YOU
📢 SIX SIGNALS YOUR AI STRATEGY MIGHT BE STUCK

HR leaders are rolling out pilots, pushing adoption, and juggling change fatigue. But strategy?

Still stuck in draft mode.

Here are six signs your organization’s AI momentum may be slowing down — and what they mean for HR.

 1. No Scale Plan

66% of HR teams use GenAI, mostly in small pilots, such as job descriptions or candidate screening.

✅ The real challenge: Define where GenAI creates value or how it connects to business outcomes.

2. Skills Visibility Gap

47% of C-suite leaders say talent gaps are slowing GenAI adoption — but most haven’t mapped what skills already exist.

✅ Millennial and Gen X managers are already leading adoption from the middle, but leadership hasn’t caught up.

3. Training and Access Missing

Half of employees say formal training is the best way to boost AI adoption — but 20% report receiving almost none.

✅ Employees want tool access, learning incentives, and recognition, not just policies.

4. Employees Not Heard

Employees know how AI is changing their work, but few organizations are listening.

✅ At Repsol, frontline teams work directly with AI systems, identifying what’s working, where human judgment is needed, and how models should evolve.

5. Transformation on Hold

Only 1 in 4 companies has a roadmap to scale GenAI. Just 12% have identified revenue-generating use cases.

 ✅ The issue isn’t hype. It is lack of alignment, ownership, and a clear plan beyond “test and learn.”

6. No Agent Readiness

AI agents are already running operations, not just providing suggestions.

 ✅ Salesforce uses Agentforce, a new layer that enables people to easily build and deploy autonomous AI agents to handle complex workflow tasks, from simulating product launches to orchestrating marketing campaigns.

Here’s where CHROs can focus to start shifting momentum.

HR FRAMEWORKS

DESIGNING THE AI EXPERIENCE: A STRATEGIC FRAMEWORK FOR CHROS

For AI to deliver lasting impact, HR leaders must help design how it fits into the work, not just how it’s introduced. This framework outlines six strategic domains where CHROs can lead and how to move each forward with clarity and intent.

1. Strategic Alignment

Many AI initiatives launch without a clear connection to business strategy or workforce priorities. Without alignment, investments remain isolated, and although they are helpful, they are not transformative.

• Co-lead a GenAI business integration map: Start with 3–5 core business priorities (e.g., customer growth, retention, margin improvement) and identify where AI could augment decision-making or workflows. Work with IT, Sales, and Finance to align these to value.

• Review existing GenAI pilots for business relevance: Ask: Which pilots support a priority outcome? Which are tools in search of a use case? Prioritize scaling those that create measurable results.

• Create a GenAI + People Systems briefing for your CEO: Use simple language to show how GenAI impacts hiring, onboarding, learning, and leadership. Position HR as a co-designer of how AI changes work.

2. Skills & Capability Mapping

Most executives say “talent” is a top barrier to AI adoption, but few know where readiness already exists. Many employees, especially middle managers, are using AI tools on their own.

• Run a GenAI skills discovery survey: Ask three simple questions: What GenAI tools do you use today? How confident are you? Where do you see opportunities? Segment results by role, generation, and region.

• Spot internal leaders of adoption: Millennials (especially ages 35–44) are often already helping peers explore GenAI. Gen Xers bring a system-wide perspective. Highlight both as potential scale champions.

• Build a dynamic GenAI capability tracker: Use pulse surveys, L&D data, and pilot feedback to build a living map of where adoption is happening and where support is needed.

3. Workforce Experience and Trust

Employees want clarity, training, and support. Without it, even great tools fail. Many don’t know what’s allowed, or what safe or “good” looks like.

• Design onboarding into GenAI tools: Don’t just grant access — offer micro-tutorials, usage policies, and real task-based examples. Help people start with confidence.

• Create recognition pathways for GenAI adoption: Publicly acknowledge early users. Offer small incentives for sharing use cases. Build social proof and trust.

• Ensure explainability in HR-led GenAI tools: Explainability means showing how an AI tool makes recommendations (e.g., in hiring, feedback, or internal mobility). Work with vendors to provide clear documentation and usage logic for employees.

4. Organizational and Workflow Redesign

As AI agents take on tasks, organizations must rethink roles, workflows, and how work flows across teams. HR must help shape this transition.

• Run a role-task-agent audit: Select a few roles. Break down key tasks. Identify which could be enhanced or fully executed by AI agents. Engage managers in redesign conversations.

• Create cross-functional AI redesign pods: Pair HR, Ops, and IT leaders to reimagine a workflow (e.g., onboarding, client setup, knowledge management) using GenAI. Focus on real friction points.

• Prototype redesigned roles and measure impact: Test one new role or workflow in a pilot group. Collect data on efficiency, clarity, and satisfaction. Refine before scaling.

5. Governance and Ethics

Compliance concerns, unclear boundaries, and a lack of communication often slow AI adoption. But this doesn’t mean solutions are delayed; it’s responsible design..

• Join your organization’s AI governance group: If one doesn’t exist, propose it. Include HR, Legal, IT, and Risk. Define responsibilities and decision rights for AI adoption.

• Develop a clear policy on AI use in people processes: Set guardrails for use in hiring, promotion, performance, and development. Communicate these in onboarding and manager training.

• Create a safe channel for employee feedback: Let people report when AI recommendations seem off, biased, or unclear. This will protect trust and improve system design.

6. Activation and Momentum

Most organizations are running pilots, but few are scaling. Real progress happens when leaders spot what’s working and build from there.

• Use a diagnostic to assess AI readiness by team or function: Our one-page AI Readiness Scorecard can help identify where to invest next. Look for usage + appetite + trust.

• Appoint GenAI champions at the team level: By GenAI champions, we do not mean formal roles, but just people empowered to test tools, collect peer questions, and flag wins and risks.

• Celebrate small wins, not just launches: Share stories where GenAI saved time, helped a customer, or clarified a process. Don’t wait for a big success to scale momentum.

Take a moment to pressure-test your own AI strategy.

POLL

EXPERT INSIGHTS
DESIGNING FOR SCALE WITHOUT LOSING THE HUMAN

🎙️ Interview with Melina Gillies, Chief People Officer, FlexNetworks

DJ: What moment made you realize the power of technology in transforming the employee experience?

Melina Gillies: 

A client was struggling to get buy-in (and budget) to fix recurring employee pain points. We linked employee feedback with customer data and uncovered shared frustrations. That connection flipped the narrative—suddenly, solving internal issues was a customer solution. The result? 35% lift in eNPS, 20% jump in customer NPS. Tech made the invisible visible.

DJ: How have you used automation or personalization to create a more engaging candidate experience in your hiring process?

Melina Gillies: 

We start with real notes—personal details from screening calls or applications—and feed those into automation tools. So when a candidate gets an update, it’s not generic. It sounds like, “Your experience with X really stood out,” not “Thank you for applying.” It’s personalization at scale, making each candidate feel remembered—not processed.

DJ: What’s been the biggest barrier in embedding tech-led personalization without making the experience feel robotic?

Melina Gillies:

It’s tempting to over-automate. The key? Branching paths based on actual candidate or employee input. Real personalization happens when you let them steer the journey, and tech follows suit—not the other way around.

DJ: What strategies or tools have helped you scale personalization across the employee lifecycle without overburdening your HR teams?

Melina Gillies:

We use interest-based segmentation (think beyond roles—music, sports, pets!) for onboarding and “job crafting.” Intake forms guide welcome kits, while automation handles the admin—freeing HR to focus where tech can’t go: real conversations, coaching, and connection.

Read on to learn how EY, Repsol, Amazon, Waste Management, and USAA are redesigning work with AI.

SUCCESS STORIES
FROM PILOTS TO PERFORMANCE: HOW EY, REPSOL, AND AMAZON ARE REDESIGNING WORK WITH AI

Here, we explore how five organizations show what it takes to move beyond experimentation. Each example highlights a different way HR and business teams can work together to scale AI with clarity, structure, and trust.

🟨 EY | Scaling AI Agents Across the Enterprise

Impact:
🤖 Deployed 150+ AI agents across tax, risk, and operations
📊 Enabled 80,000 professionals to complete 30M+ tasks per year
🔁 Integrated agents directly into workflows — not just apps

The Challenge:

EY’s teams faced increasing demands for efficiency and compliance in high-volume, high-risk domains. Traditional tooling couldn’t keep up with the complexity of workflows and the pace of business change

What They Did:

EY partnered with NVIDIA to embed AI agents into day-to-day operations — automating tasks, guiding decisions, and enabling expert focus where it mattered most. The rollout was paired with HR-led change management and training to ensure usability and adoption.

🟩 Repsol | Designing AI Around Human Expertise

Impact:

📣 Frontline workers empowered to retrain AI systems based on judgment
📈 Improved decision quality through employee-informed AI corrections
🧠 Scaled trust by integrating human feedback into model design

The Challenge:

Repsol wanted to scale AI without removing expert oversight — especially in operational environments where human judgment still drives safety and performance.

What they did:

Instead of building GenAI systems in isolation, Repsol created a loop where employees could directly adjust AI models and shape their evolution. This created a workforce-led feedback mechanism — blending trust, relevance, and innovation.

🟦 Amazon | Coaching GenAI from the Ground Up

Impact:

📚 AI Coach launched to support day-to-day learning
💬 Personalized prompts based on role, function, and workflow
🔍 Reduced training time and increased on-the-job fluency

The Challenge:

Amazon needed a way to train a massive frontline workforce on GenAI tools — without pulling people out of the flow of work.

What they did:

They introduced an internal AI Coach: a tool embedded into daily workflows that delivers task-specific, contextual GenAI support. It helps employees learn by doing, with prompts tailored to their current systems and responsibilities.

🟫 Waste Management | Rebuilding Skills and Trust at Scale

Impact:

🛠️ Drivers empowered to override and improve AI-powered routing
💰 Bonuses offered to employees who outperform automated recommendations
🤝 Strengthened trust through human discretion, not just compliance

The Challenge:

Waste Management wanted to scale intelligent routing, but without reducing driver autonomy or trust in the system.

What they did:

Instead of mandating AI-generated routes, the company let drivers challenge the bot. If they improved on it, they got rewarded. The result? Better performance, stronger adoption, and a culture that sees AI as a collaborator — not a controller.

🟪 USAA | Rebuilding the EVP for an AI-Ready Culture

Impact:

📘 AI training strategy mapped to all 37,000 employees
🎓 Senior leaders trained in-person by industry experts
🚀 55+ use cases generated from cross-functional hackathons

The Challenge:

USAA needed to build GenAI fluency across a massive, highly regulated workforce, without compromising governance, trust, or momentum.

What they did:

Led by CIO Amala Duggirala, USAA designed a three-part training strategy:

• Governance and risk as the entry point

• Executive education through in-person sessions

• Role-based training tailored to tech, compliance, and business users

To promote hands-on experience, they hosted company-wide hackathons with record participation, surfacing 55+ use cases and sparking grassroots enthusiasm.

Use this one-pager to check your organization’s readiness.

YOUR DOWNLOADABLE RESOURCE
AI & LEARNING READINESS SCORECARD

Where does your team stand on GenAI?

This one-page diagnostic helps you assess readiness across five essential areas.

🔍 Score yourself (from not ready to fully ready) and use the results to:

• Start cross-functional conversations with IT, Ops, and business leads

• Prioritize support where fluency or trust is low

• Build momentum where champions and systems are in place

• Track progress over time as GenAI capabilities grow

UPCOMING EVENT
THE AI EXPERIENCE SUMMIT

AI is no longer just a tool—it’s becoming the co-architect of strategy, leadership, and workforce transformation.

The three-day AI Experience Summit will explore how AI reshapes the employee experience, redefines leadership, and accelerates workforce potential. From talent acquisition and learning to ethics, productivity, and innovation, attendees will get frameworks, use cases, and strategies to lead in the AI era, without losing the human thread.

With expert panels, live workshops, and future-ready insights, this summit is a must-attend for HR, tech, and business leaders building the next chapter of work.

📅 When: June 3-5, 2025 (7 am–11 am Pacific Time)
💻 Event Type: Online | Free
📢 Content Format: Panel | Workshop

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