AI Is rewiring organisational design. HR must respond

Every year political leaders, CEOs, economists and academics gather in Switzerland for the annual meeting of the World Economic Forum. I watch the sessions closely because they offer something useful: a barometer of what senior leaders are genuinely prioritising.

This year there was little ambiguity: AI framed almost every serious discussion.

What struck me, though, was the shift in language. The conversation has moved on from experimentation. It now centres on structure, power and value.

Two remarks have stayed with me. Historian and author Yuval Noah Harari described AI as “the biggest and scariest psychological experiment in history”. Microsoft CEO Satya Nadella described it as “a complete inversion of how information is flowing in the organisation.” Between those two statements sits the HR agenda for 2026.

What changed in the AI conversation at Davos 2026?

The focus has shifted from pilots to operating models. Last year many sessions centred on generative AI’s efficiency potential. This year leaders were talking about information flow, decision-making and organisational architecture.

Nadella offered a practical example. Preparing for major meetings once required layered briefings travelling up through management. Today, he asks Copilot directly for a 360-degree overview. Information that previously moved through people now moves through systems.

When information flows differently, authority and accountability inevitably shift with it.

Accenture CEO Julie Sweet spoke about embedding AI value into the P&L and redesigning operating models accordingly. An Accenture survey referenced at Davos found that 78% of C-suite leaders believe AI is contributing more to growth than cost reduction. Growth language suggests integration into core strategy.

Christoph Schweizer, CEO of BCG, reinforced the behavioural dimension. He said that AI adoption delivers value when people use it consistently. Sporadic use distracts while daily use changes how work is done.

Across industries, leaders described the same pattern. AI is altering workflows. It is accelerating analysis. It is reducing friction in information exchange. The organisational consequences are becoming harder to ignore.

If information flows differently, how should organisations respond?

Hierarchy has historically managed information, decisions and risk. AI reshapes at least two of those functions. When employees at multiple levels can access contextual insight instantly information asymmetry narrows. That influences how decisions are informed and where they sit.

Uber CEO Dara Khosrowshahi described the difference between incremental efficiency gains and deeper redesign. Applying AI within legacy systems can improve performance. Rebuilding workflows around AI demands greater adjustment and produces greater change.

Royal Phillips CEO Roy Jakobs shared a healthcare example. AI-enabled ambient listening gives nurses back 10 to 15 minutes per hour. The impact depends on whether documentation processes and clinical workflows evolve alongside the technology.

The thread across these discussions was consistent. AI affects the way work moves. 

Organisational design determines whether that movement creates value.

For HR leaders this is familiar territory. Decision rights, role clarity, performance metrics and accountability frameworks sit within the people agenda. When information flow changes, those elements require review.

What happens to entry-level work when routine tasks are automated?

Another theme running through Davos was the changing nature of early career roles.

For decades repetition played a formative role in professional development. Analysts built spreadsheets, junior lawyers drafted clauses and graduates screened CVs. Through such volume and exposure young people developed judgement. 

Andrew Ng, founder of deep learning.ai, argued that most jobs consist of tasks and that AI can automate a significant proportion of them. The implication is that routine components are increasingly AI-assisted.

Kate Kallot, founder and CEO of Amini AI, highlighted the demographic dimension. Around 1.2 billion young people are expected to enter the workforce in emerging markets over the next decade, with only 400 million jobs forecast. Access to AI capability and infrastructure will shape employability.

Adecco CEO Denis Machuel cited research across 37,000 workers in more than 30 countries showing that 83% want control over their skills development. Many employees are already investing in AI literacy themselves.

The question for organisations is developmental. If repetition declines as a learning mechanism, how will judgement, context and professional confidence develop?

Graduate programmes may need to place greater emphasis on interpretation, critical thinking and cross-functional exposure. Apprenticeships may focus more on validating AI outputs than generating first drafts. Managers will require the capability to coach employees who work alongside intelligent systems from day one. It’s easy to think of this as a skills issue when in reality it is about how careers are constructed.

Who captures AI-driven value?

One of the more striking elements of Davos 2026 was the confidence with which CEOs spoke about financial returns. Aramco CEO Amin Nasser reported between three and five billion dollars in value in the previous financial year, with more than half directly attributable to AI. That value was generated by subject matter experts identifying use cases, supported by a digital company and an AI centre of excellence.

At the same time, questions about inclusion in design and value distribution surfaced in several sessions. Luc Triangle, general secretary of the International Trade Union Confederation, warned that informing workers about AI after deployment undermines trust. Participation matters.

When productivity increases expectations often increase alongside it. Work can be completed more quickly and output can expand. The link between contribution and reward becomes more visible.

For HR leaders governance and transparency are central. Performance frameworks, incentive design and communication strategies influence whether AI-driven gains strengthen engagement or create tension.

Why trust now sits at the centre of AI adoption

Trust surfaced repeatedly across sectors. Roxana Mînzatu, executive VP for social rights, skills and quality jobs and preparedness at the European Commission, spoke about the importance of social dialogue in maintaining labour market stability during AI-driven transformation. Visa CEO Ryan McInerney described the layered trust architecture required for autonomous commerce.  Jakobs reflected on the accuracy thresholds demanded of AI systems in healthcare before clinical adoption.

Trust operates at multiple levels: confidence in outputs, confidence in oversight and confidence in intent.

Inclusion was discussed in similar structural terms. Iris Bohnet, director of the women and public policy at Harvard Kennedy School, argued that embedding fairness into hiring and promotion systems is more effective than relying on awareness initiatives alone. Process design shapes perception and legitimacy.

For HR, trust is not abstract. It is embedded in policies, governance mechanisms and everyday practice.

Creative destruction is accelerating

Economists Philippe Aghion and Peter Howitt revisited their long-standing argument that technological progress drives growth, while rendering older models obsolete. Adjustment creates winners and losers.

Harari warned against underestimating AI’s capacity to act strategically. Khosrowshahi spoke about a 10 to 20 year horizon in which autonomous vehicles progressively reshape mobility.

Creative destruction is unfolding across industries. It is also unfolding within organisations. Legacy processes, incentive systems and career pathways will all feel pressure.

HR’s influence over mobility, reskilling and succession planning shapes how constructively that pressure is managed.

What HR leaders should do now

The implications are structural rather than tactical. Several priorities emerge.

Audit workflows. Map how AI changes information flow across teams and identify where hierarchy no longer adds value.

Revisit decision rights. Clarify where AI-supported insight enables redistribution of authority without increasing risk.

Redesign entry-level pathways. Build structured exposure to evaluation, interpretation and cross-functional thinking.

Align reward systems with AI-augmented output. Review pay frameworks, bonus design and workload expectations.

Embed transparent governance. Establish clear oversight mechanisms and communicate them consistently.

Invest in leadership AI fluency. Senior leaders who use AI understand its limitations and strengths. That practical familiarity supports credible guardrails.

Strengthen internal mobility. Enable talent to move into emerging areas as automation affects legacy roles.

Develop geopolitical literacy. Technological transformation unfolds within a volatile global context. Scenario-based workforce planning supports resilience.

These actions sit squarely within HR value creation. They influence productivity, engagement, legitimacy and long-term competitiveness.

At The People Space we focus on helping HR leaders stay Future Fit by critically understanding technological shifts and shaping them in human-centred ways. Davos 2026 reinforced a clear message. AI is restructuring organisations from the inside. The question is whether HR will shape that redesign or react to it.