Only 4% of HR chiefs feel very prepared for AI-driven change. Here’s why deploying AI without redesigning the work is a strategy that won’t hold
Workforce design – not AI adoption – is becoming the sharpest competitive divide facing HR leaders globally. PwC's 2026 Global Workforce Hopes and Fears Survey, which gathered responses from 49,364 workers across 48 countries and regions, found that while daily AI usage rose significantly over the past year, the share of employees with access to learning and development fell from 59 to 51 per cent from 2025 to 2026. The divergence captures a design failure, not a technology failure: organisations are deploying tools without redesigning the work those tools are meant to support.
Ram Srinivasan, Managing Director at JLL in Chicago, which surveyed more than 2,200 C-suite executives worldwide in its 2026 AI research, describes this as the gap between substitution and reinvention. Most organisations are in the substitution phase – applying AI to existing processes, while the organisations generating measurable returns have moved to reinvention, questioning whether those processes should exist at all, he says. According to The Conference Board's 2026 CHRO Confidence Index for the third quarter, only four per cent of chief human resources officers (CHROs) in the U.S. say their organisations are very prepared to manage AI-driven workforce change over the next two years, with just over half saying they’re prepared at some level. That figure describes the scale of the design gap.
Pascal Gouel, Managing Director of TAG, a Sydney-based casual labour hire firm managing approximately 5,000 workers across close to 100 blue-chip clients in aviation, hospitality, fast-moving consumer goods, supply chain, and retail in Australia, says that technical AI proficiency is becoming less scarce, not more, as AI absorbs information-gathering, analysis, and routine execution. The skill rising in value is the one AI cannot replicate, he says.
"AI has just shred that to pieces," Gouel says of the traditional information-advantage model. "It's going to come back to good decision-makers that can make decisions within that governance framework – and that works at all levels of the organisation. I'm not talking about executive leadership. It's all levels."
Design the work before you deploy AI tools
The pattern is consistent across markets: AI tools are acquired, licences distributed, adoption tracked, but the underlying work is never examined. Lee-Ann Reid, Vice President of Operations and Director of HR at Vistek, a Canadian imaging and technology retailer with approximately 160 employees, says she spent six to 10 years building process maps for every workflow before asking where automation could add value. The maps identified which tasks were deterministic, which required genuine judgment, and where handoffs created friction – providing the design foundation that made AI deployment meaningful rather than cosmetic.
"An HR professional understands how to remove the emotional attachment from the role to really look at the challenge," Reid says. "The challenge is before us on the table together, and we're going to solve it together."
Transformation requires collaboration between HR and IT
Fiona Ho, the Vancouver-based CHRO at Sophos, a global cybersecurity company based in Abingdon, U.K., has articulated the same distinction from an Asia-Pacific perspective. "For HR leaders – if they're not already – I would highly encourage working closely with their IT departments when it comes to rolling out AI and going through these workforce transformations," says Ho. "This is not a technology rollout. We think about this as a workforce transformation and all of these different areas come together and we're rolling this out to the whole company collectively."
Ho believes that effective AI adoption requires building foundational human skills – critical thinking, clear communication, and accountability for AI outputs – alongside tool access. Giving employees a licence is not the same as giving them a capability, she says. The gap between the two is a design gap, not a training gap, and it requires a different kind of investment to close.
With the Canadian government releasing its own national AI strategy in 2026, it sets the tone for five workforce transformation strategies HR leaders can act on now.
The human skills organisations are building
Jason LaRue, Vice Chair of Talent and Culture at KPMG U.S. in Providence, RI, has described the challenge as a "work trifecta": the work itself is being redesigned, the workforce is shifting in terms of which capabilities are hired and rewarded, and the workplace – physical and digital – is evolving in how people collaborate. At KPMG, LaRue says investment in simulation-based learning has been aimed at developing uniquely human skills – judgment, critical thinking, and ethical reasoning – alongside the urgent HR imperative of AI fluency, on the principle that the compound capability between the two is what produces durable competitive advantage.
Katie Williams, People and Culture Leader at Sky New Zealand in Auckland, has described AI's productivity promise as largely unmet in organisations that have treated adoption as an end in itself. She argues that the people function is hybridising in response – technology, workforce strategy, and culture are increasingly managed as a single integrated domain, and organisations trying to maintain them as separate disciplines are finding the seams. The implication for workforce design is that the function being redesigned is not just individual jobs, but the architecture of how the people function itself operates, according to Williams.
Permpreet Soomal, Vice President of HR at MDA Space, a Canadian aerospace technology company based in Toronto, described the measurement shift that accompanies effective workforce redesign: moving from retrospective dashboards to predictive insights oriented around business outcomes. Soomal says MDA Space is exploring machine learning models that analyse performance trajectory, skills acquisition rates, and project complexity to identify high-potential employees — replacing subjective nomination with evidence-based talent intelligence and closing the loop between workforce design decisions and business results.
Srinivasan of JLL puts the pace challenge plainly. "HR leaders, at least the HR leaders we are working with, are already front-leading on the subject of AI adoption," he says. "Where I think there is a challenge for every functional area is keeping pace with the changes that are happening."
The organisations closing that skills gap and its implications for workforce readiness share a common discipline: they designed the work before they decided what the machine should do. Workforce design is not a step that follows AI adoption. It is the step that makes AI adoption worth doing.
