AI transformation is reshaping work. HR leaders must help redesign it

A year after IBM's Deep Blue defeated Garry Kasparov at chess in 1997, Kasparov did something unexpected.

Rather than retreat, he invented a new form of chess that paired human players with computers to see what they could produce together. The result was striking: even moderately skilled players, armed with a standard machine, could outperform both grandmasters and computers operating alone. The combination was categorically superior to either in isolation.

That lesson carries direct relevance for organizations navigating AI today. The instinct is to frame AI as a technology story. It is not. AI reshapes jobs, redistributes decision rights, resets operating models and forces organizations to reconsider deeply embedded ways of working. It produces as many human questions as it does technical ones. And the organizations genuinely winning with it are not those with the most sophisticated technology – they are those that have most deliberately redesigned how humans and machines work together.

AI transformation is not a technology programme to be rolled out. It is a human transformation to be led.

The most effective AI transformations are driven by a tight three-way partnership: the business setting the agenda and owning outcomes, the Chief Information Officer (CIO) providing technology platforms and governance, and the Chief Human Resources Officer (CHRO) leading the human transformation that determines whether AI delivers value at scale or stalls in pilots.

Each is essential. None is sufficient alone.

The human dimension – the design of work and decision rights, the building of capability, the management of trust, the orchestration of adoption – is not downstream of the technology. It is a primary enabler of it. That’s why the CHRO must play a central and distinct role in this transformation, through four interconnected roles.

As design architect, the CHRO reimagines how work gets done. AI transformation fails far more often because of organizational design choices than because of technology limitations. When companies deploy AI without redesigning work, decision rights blur, accountability erodes and productivity gains stall. The CHRO must clarify which decisions remain human-led, which are AI-supported, and where accountability sits – and build operating model architectures that are dynamic enough to evolve as AI capabilities accelerate.

At Procter & Gamble, data scientists and AI engineers were embedded directly within business units and operational teams rather than siloed in centralized analytics functions, enabling real-time engagement with supply chain, marketing and commercial decision-making at scale and removing the information barriers that had long constrained performance.

As capability steward, the CHRO builds enterprise-wide learning systems that keep pace with AI. In the AI era, capability – not technology – is the primary constraint on value creation. Traditional episodic training is structurally unsuited to the pace of change. The CHRO must build continuous, contextual learning embedded in daily workflows, develop AI fluency across the entire workforce and maintain ongoing insight into which capabilities are emerging or declining.

During my time at Zurich Insurance, we built an enterprise-wide AI capability ecosystem that combined broad literacy with deep domain-specific learning. That focused deliberately on transferable skills, enabling rapid redeployment of people as roles shifted.

As adoption catalyst, the CHRO ensures AI value is not confined to central teams or leadership mandates. Scalable impact comes from the bottom up – from employees who understand the work and are empowered to apply AI where insight is deepest.

At Al-Futtaim, the use cases underpinning our Blue Loyalty Platform, for example, were not developed centrally. They were built by multi-disciplinary frontline retail teams, in agile action-learning groups, applying direct customer knowledge to develop personalized recommendations. AI was embedded in workflows by the people who understood them best, and the result has been measurable revenue uplift driven by use cases rooted in real interactions, not boardroom hypotheses.

As transition guardian, the CHRO ensures AI adoption is ethical, transparent and consistent with the employee value proposition. AI introduces legitimate concerns around fairness, surveillance, bias and employability that, if left unaddressed, erode the trust on which adoption depends. Today's employees need to focus less on specific target jobs and more on building transferable skill profiles that will serve them throughout a career that is certain to evolve rapidly. The CHRO must make that pathway credible through concrete reskilling and redeployment commitments, not reassurance. Trust is not a soft outcome of AI transformation. It is the hard prerequisite for scaling it.

The decisive differentiator will not be access to technology, but the ability to orchestrate human transformation around it.

The organizations that convert AI from experimentation into sustained competitive advantage are those that redesign how work is done, build capability continuously, empower employees as co-creators and protect trust throughout the transition. The CHRO who grasps this – and who acts on it with the same strategic weight as any technology investment – becomes one of the most consequential executives in the organization.

Kasparov's advanced chess experiment showed us, a quarter of a century ago, that the most powerful outcomes emerge not from humans or machines working alone, but from their deliberate and skillful combination. The CHRO's mandate is to make that combination work at enterprise scale, at pace, and without losing the trust of the people it depends on.

That is a defining role – and one organizations looking to capitalize on AI cannot ignore.