From hype to habit: how organisations can operationalise AI in HR

Most organisations have moved past asking whether AI matters. The conversation now is whether it’s genuinely becoming part of how work gets done.

That’s where many are still getting stuck. Adoption is high, but impact is uneven. ELMO’s 2026 HR Industry Benchmark research found that HR teams see a lack of skilled people (35%) as the biggest barrier to AI adoption, followed closely by a lack of time to experiment (30%). The intent is there, and in many cases the tools are too, but translating that into meaningful, day-to-day value is proving harder.

From my seat, AI doesn’t stall because people are unwilling. It tends to stall because organisations mistake access for enablement.

At ELMO, we’ve been fortunate to be on the leading edge of adoption. We’re part of a relatively small group of organisations (around 6%) where more than 75% of the workforce is actively using AI (HRIB 2026). That level of uptake has been valuable, but it has also made something very clear: high adoption doesn’t automatically translate into high impact. What matters is how deeply and effectively people are using it.

Five shifts have made the biggest difference for us.

1. Start with a vision people can see themselves in

Early on, we found that broad narratives about AI — productivity, disruption, the future of work — didn’t land in a meaningful way.
What did land was helping people understand how AI could improve the quality of their own work. We positioned AI as part of how we operate, not something separate to it, co-creating AI-related OKRs and KPIs with the team to anchor it in day-to-day performance. That meant connecting it to better decision-making, more meaningful work, and the ability to focus on higher-value problems.

If the message centres only on efficiency or cost, people tend to disengage or comply at a surface level. When they can see how it helps them think better, solve problems differently, or progress in their role, the response shifts.

2. Treat AI as a capability, not a course

We also moved quickly away from thinking about AI as something that could be addressed through standalone training. Training plays a role, but on its own it doesn’t change behaviour. What made a difference for us was defining what good looks like.

By embedding AI into our capability framework, we shifted the focus from attendance to expectation; from who has completed a course to how people are expected to apply AI in their role. That spans everything from basic literacy and safe use through to using AI to redesign workflows and solve more complex problems.

This has helped connect AI to the broader talent lifecycle, including how we hire, develop and assess performance, rather than treating it as a separate initiative. It has also reinforced that as AI becomes more embedded, human capabilities like judgement, critical thinking and problem-solving become more important, not less.

3. Build learning into the flow of work

If AI is going to become part of how work happens, learning needs to be practical and ongoing.

We used moments like ELMO Educate D-AI to create initial momentum, combining leadership context with hands-on sessions such as custom GPT builds and tool-based workshops.
From there, we focused on embedding learning into day-to-day work, moving beyond foundational skills towards AI intuition. It’s less about knowing how to use a tool and more about how you approach complex problems, navigate ambiguity, direct the technology, and apply judgement.

The people who develop that intuition tend to integrate AI more deeply into their workflows and are often the ones rethinking how work is structured, not just how tasks are completed.

4. Make experimentation part of the job

One of the more effective shifts has been creating space for experimentation. We’ve done this through structured initiatives like hackathons and freestyle Frid-AIs, but also through recurring time for teams to explore how AI can be applied to real workflows using approved tools.

Within People & Culture, we have run AI showcases where the team shares where AI has helped solve real problems or reduced friction and allocated weekly time in our calendars to experiment in the flow of work.

5. Build social proof, champions and guardrails together

AI adoption tends to spread through people rather than through formal programs alone. We saw stronger traction when teams had access to peers who were already experimenting, sharing what worked and helping others apply AI in context. Local champions and communities have played an important role in that, particularly in translating ideas into practical application.

At the same time, none of this works without clear guardrails. Governance provides the confidence to experiment at pace. When people understand which tools are approved, how data should be handled, and where human oversight is required, they are far more willing to engage.

The human side of the shift

As AI increases the pace of work, it often increases the volume as well. You’re able to move faster, but you’re also expected to handle more, across a broader set of priorities. I’ve felt that personally, the sense that everything is accelerating at once.

There’s a term starting to emerge for this, “AI brain fry”, which captures the cognitive load that comes from constant context-switching and operating at a higher intensity.

It’s a reminder that this isn’t just a technology transformation. It’s changing how people work, how they manage their energy, and what organisations need to put in place to support them.
For organisations looking to create real impact, the focus needs to move beyond adoption and into behaviour. AI only delivers value when it is built into how work happens in practice, with clear expectations and consistent application to real problems.

HR has a central role in making that shift stick by setting standards, guiding how work is structured and supporting people to use AI with confidence. AI may be the catalyst, but outcomes depend on how deliberately it is embedded into everyday operations.

ELMO is the Complete AI Workforce Platform™. Find out more here.

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