Editorial
White Paper
The Future of Leadership Development: AI-Driven Manager Enablement
Every year I write a CX trends piece about the shifts I genuinely believe will come to fruition, not the ones that make good conference slides. For several years running, EX and CX alignment has topped my list. And every year, I've had to argue past the same objection: a faction that doesn't believe there's any real causation between employee experience and customer experience — that the correlation researchers keep finding is just two metrics moving together for unrelated reasons.
I understand the skepticism. Isolating a causal arrow in organizational data is hard, and engagement scores get criticized for good reason. But I've watched enough transformations up close to believe that when culture, employee experience and customer experience move together, growth follows — and when one is missing, the whole thing stalls. This year, I don't need to win the causation argument to make my point. The economics are doing it for me.
Because here's what's different in an AI-first environment: employee resistance remains one of the biggest reasons transformations fail and resistance shows up as lower ROI, higher cost and slower, weaker transformations. That's not a new finding. What's new is that AI is making the cost of ignoring it visible in real time, on both the employee side and the customer side, instead of buried in an annual survey report.
The Signal Has Been Getting Louder for a While
Perceptyx's latest research, drawn from 20 million employee survey responses tracked over a decade, found what its own researchers call the largest shift in engagement drivers they've ever recorded. Belonging and feeling valued — the consistent top-two engagement drivers from 2016 through 2024 — dropped to the bottom of the list in 2025. Change management effectiveness and confidence in senior leadership now sit at the top.
Employees didn't suddenly stop caring about belonging. They're just telling us what matters most now, because the thing straining them the most has changed. And nowhere is that clearer than at the frontline, where the EX and CX story stops being separate stories. Perceptyx's frontline research tells a consistent story. In its February 2025 Forgotten Frontline study, 53% of customer-facing employees reported abusive or threatening interactions with customers — 61% among retail workers, 81% of whom report burnout. Separate 2025 research on retail employees found whether workers feel genuinely heard is now a stronger predictor of engagement than pay.
That's not an employee experience statistic or a customer experience statistic. It's both, generated by the same broken process, showing up on both sides of the interaction at once. Voice of the employee data has been carrying this signal for years. It just hasn't been loud enough, or convenient enough, to act on.
That same body of research points to why: retention numbers may look stable, but that stability is masking a workforce that's staying out of fear rather than conviction. Intent to stay is up. Intrinsic motivation — the strongest predictor of actual performance — is down. Employees have quietly shifted from asking “how can I grow here?” to “do I believe this company will succeed, and will I succeed with it?” That's a workforce sitting on information leadership hasn't been forced to read closely, because the metric everyone watches — retention — still looks fine.
Why Leadership Hasn't Made This a Priority
It's not that the evidence has been missing. The CHRO Association's 2026 survey of roughly 150 CHROs found that geopolitical instability, inflation and regulatory uncertainty top the list of forces shaping company decisions right now, with AI and workplace digitization the dominant operational priority layered on top. Employee experience doesn't disappear from that list — it gets “balanced” against cost management, which is a polite way of saying it competes with line items that are easier to defend in a board meeting.
That's the honest answer to why the voice of the employee (VoE) hasn't climbed the priority chain: revenue growth, cost reduction and risk mitigation have clearer, faster paths to a number executives can report. HR, and the employee experience work underneath it, is still budgeted like overhead rather than underwritten like an investment — even when the research says that's backwards. The same CHRO survey names “organizational readiness — including workforce concerns, governance risks and investment constraints” as the primary barrier to scaling AI. Read that plainly: leaders know the workforce and governance side is the bottleneck, and they're naming investment constraints as a reason not to address it. That's a cost-center mindset describing its own limitation without recognizing it as one.
McKinsey's State of Organizations 2026 report, based on a survey of more than 10,000 senior executives across 15 countries, makes that backwardness explicit. Eighty-eight percent of organizations are experimenting with AI, and fewer than one in five report meaningful bottom-line impact from it. One benchmark the report highlights: for every dollar spent on AI technology, five dollars should go to people.
Not as a values statement — as a correction to a spending ratio that isn't producing returns. That's about as direct a business case for treating employee experience as an investment, not a cost, as you're likely to get from a firm whose name shows up on the same slide decks justifying the AI spend in the first place.
Why AI Changes the Calculus
Here's where I part ways with the “AI won't fix broken processes” argument, even though it's not wrong on its own terms. AI genuinely doesn't fix anything by itself — layer it on top of a dysfunctional workflow, and it will amplify the dysfunction faster than a human ever could. But that amplification is precisely the mechanism that's about to make VoE data impossible to keep ignoring.
For years, a broken process could hide inside an annual engagement survey nobody read closely, or inside a workaround an exhausted employee quietly built to cope. AI removes both hiding places. Deploy it on top of a process employees have been flagging for years, and the failure shows up immediately — in adoption data, in customer complaints, in the abusive interactions frontline staff are already absorbing at scale, in the ROI numbers executives track.
Think about how this plays out inside a single deployment. An organization rolls out an AI tool to speed up service resolution without first fixing the escalation path frontline employees have flagged for years as broken. The tool doesn't underperform the way the old process did. It fails loudly and fast — customers notice within days, not quarters, and the same employees who've been raising the issue in engagement surveys are now the ones fielding the complaints AI helped generate faster. The broken process was always there. AI just made it visible.
Perceptyx's own research makes the same point about AI in listening: it can analyze feedback, recognize patterns and uncover insights at a scale no survey cycle ever could. But deciding what deserves attention, balancing competing priorities and building trust remain decisions. AI has taken away the option of not knowing — it hasn’t eliminated the need to lead.
That's the shift I believe is coming, and it's why I think this is the year EX and CX stop being adjacent conversations. The same governance and change-management failures that make employees resist AI are the ones showing up as friction in the customer's experience of that same organization. AI didn't create that overlap. It's just making it visible at a speed leadership can no longer outrun.
What Leaders Who Get Ahead of This Will Do Differently
The organizations that treat this moment well will be the ones that finally act on what those tools surface. That means treating VoE as continuous intelligence rather than an annual scorecard, connecting employee listening data to customer experience data instead of running them in separate departments with separate budgets, and applying something closer to McKinsey's five-to-one ratio in practice rather than in a slide.
Two specific practices matter most here, and neither is new — they're just no longer optional.
The first is giving employees a sanctioned space to build AI literacy, instead of leaving them to find their own workarounds. When training lags deployment, employees don't stop using AI — they use whatever tool solves their immediate problem, outside any governance framework leadership can see. I’ve argued that AI literacy failures are usually exclusion problems wearing a training-gap disguise: employees weren't given a seat at the table, so they built their own workaround instead. The fix is the same here. AI literacy has to be built in the open, with a mandate, the same as any other core competency — not left for people to learn quietly on their own time.
The second is including employees in tool selection and process design from the start, not after the rollout. The self-fulfilling loop that drives AI resistance starts exactly here: fear of displacement triggers pushback, pushback triggers a punitive mandate, and the punitive mandate confirms the fear was justified all along — a cycle I've traced in more detail before. Frontline and functional teams know which processes are actually broken and which fixes would work before procurement does. Treating that knowledge as a formality to collect after the tool is chosen, instead of an input to the decision itself, is the same exclusion that drives resistance and buries the VoE signal.
Both practices point to the same discipline underneath everything above: treat what employees are already telling you — through literacy gaps, exclusion or resistance — as intelligence to act on before deployment, not damage control after.
None of this requires resolving the academic debate about EX-CX causation. It requires acknowledging that the same broken process is now costing an organization on both fronts simultaneously, and that AI has removed the option of dealing with only one of them.
Engaged, But Not Convinced: What's Eroding Beneath Your Strongest Engagement Numbers
Watch Now
Retention Is a Communication Problem: New Data from 6,000+ Employees
Watch Now
Employees have been telling us what's broken for a long time. AI didn't change what they're saying. It changed how fast the rest of the organization finds out.
Editor's Note: For more reading on some of the topics Sue raised, try:
- A Blueprint That Binds: The First Principle of Digital Employee Experience — A reference architecture is foundational for DEX. This practical framework guides tech purchases and integration decisions. Here's how to build yours.
- Where AI Can Enhance Employee Experience: A Digital Workplace Perspective — AI can help build digital workplaces where employees thrive. Success lies in balancing tech innovation with an understanding of employee needs and aspirations.
- Where Employee Experience and Customer Experience Align, and Where They Diverge — Aligning EX and CX efforts pays off. But the two shouldn't be treated the same. Here's where EX requires a different approach.
Learn how you can join our contributor community.