Rushing into AI risks eroding human capability and creating uneven, error‑prone outcomes – unless HR leaders step up now to co‑own strategy, governance and skills from the start
Business leaders are rushing into AI because of “corporate FOMO”, risking weaker skills, uneven quality and clumsy workforce changes.
In discussion with HRD, Gartner’s Jonathan Tabah noted that HR leaders must now co-lead AI strategy alongside IT.
He said many executives feel they “have to move fast” on AI to avoid being left behind by competitors, even when the plan is still immature. That bias to act is understandable – but dangerous if HR is not deeply involved from the outset.
AI over-reliance and the risk of skill atrophy
While public debate often focuses on AI replacing jobs, Tabah is more concerned about what happens to the capabilities of employees who lean too heavily on these tools.
Data from Gartner revealed that by 2030, 30% of organisations are expected to see poorer decision‑making due to overreliance on AI.
“The more people rely on AI to complete tasks on their behalf, the more atrophy we see in the skill to complete that task by humans,” he said.
When workers lose hands-on familiarity with core tasks, they also become less able to “evaluate whether AI has done it properly,” increasing the risk of errors or poor decisions slipping through.
Recent high‑profile examples, such as flawed AI‑generated legal briefs, demonstrate how quickly that risk can become reputational or even legal.
Why AI decisions can’t be left to individuals
Some HR narratives frame AI as a highly individual journey – each employee experimenting in their own way. Tabah pushed back on that as a primary strategy, describing it as a recipe for inconsistency and unmanaged risk.
“Every single human has different judgment, different risk tolerances, different opinions and views,” he said. “If we expect everyone to manage that on their own, we’re going to achieve unreliable outcomes.”
Instead, he argues, organisations need a clear, top‑down strategy and governance framework that sets where AI can and should be used, where it should be restricted, and what guardrails and review processes apply.
HR leaders at the centre of AI strategy
For Tabah, AI is no longer a “tech project” – it is a workforce transformation issue, which puts HR at the centre of the conversation.
Corporate strategy teams, CIOs and CTOs are leading much of the AI agenda. But “most importantly, perhaps, are CHROs,” he said. “Chief human resource officers need to be leading and guiding that conversation. Because at the end of the day, this is about the workforce.”
Tabah said most functional leaders are thinking only about how AI affects their own department. In contrast, only the heads of IT and HR consistently worry about how AI will reshape the wider workforce as well.
Target the ‘low-hanging fruit’ –
In practical terms, Tabah said most organisations should focus AI adoption first on operational, repeatable and automatable tasks – especially at more junior levels.
Critically for HR leaders under pressure to show quick ROI, Tabah warned that the early stages of AI rollout are likely to reduce productivity before they improve it.
“Innovation itself is inefficient,” he said. As employees learn new tools by trial and error, “what they first find is an efficiency decrease” before productivity ultimately rises.
On workforce planning, he cautioned against cutting roles too early in anticipation of AI savings. A more effective approach is to implement AI, understand where genuine efficiencies emerge, and then make headcount decisions based on evidence rather than forecasts.
What ‘good’ looks like: guided use cases and shared learning
The organisations that are “getting AI right” tend to have one thing in common: they do not simply hand employees a tool and walk away.
Some employers are “being very thoughtful about, in this job or in this kind of role, these are the most immediate use cases to start with. And here’s how to do it,” Tabah said. As staff become familiar, they are encouraged to identify new use cases and share them so the organisation can “achieve scale” from those innovations.
By contrast, a purely bottom‑up approach – giving people tools and waiting to see what comes back – is likely to produce “less consistent, less reliable outcomes,” even if it occasionally uncovers breakthrough ideas.
Overall, Tabah said, the companies seeing “the most rapid uptake, the most rapid increases in productivity” are those that are deliberate about AI priorities by job family, are guiding employees to high‑impact and low‑risk use cases first, and are capturing and scaling successful experiments.
“There’s a reason we always get the low hanging fruit first… we get the most return for the least amount of effort,” he noted.
What this means for HR leaders in 2026
For HR leaders, Tanah believes you cannot afford to sit on the sidelines of AI.
He urged HR leaders to work closely with talent, L&D and workforce planning teams to pinpoint where AI will create capability gaps and where it can safely augment work – and then to partner across IT, finance, operations and strategy on an enterprise‑wide roadmap.
As AI reshapes day‑to‑day work, he also expects HR to become either more integrated with IT or more dependent on it, rather than expanding as a stand‑alone function.
“It’s hard to imagine an environment where HR doesn’t become either smaller and more dependent on IT, or at least more integrated with IT,” he said. “HR’s strategic remit is unlikely to expand as stand‑alone.”
For now, though, Tabah’s core warning for HR leaders is less about structure and more about mindset: resist the pressure to blindly keep up with AI hype, and instead own the governance, guardrails and capability-building that will determine whether AI becomes a genuine productivity accelerator – or a long‑term risk to your people and your business.
