Future of Work
Voices shaping how organisations adapt to automation, hybrid models and shifting expectations of work
Most enterprises have bought into generative AI in principle and stalled in practice. Pilots multiply, demos impress, but very few make the jump to operating on proprietary data inside real workflows. The hard question for boards is no longer whether to adopt AI, but how to make it useful at scale without losing control of accessibility, governance and the workforce alongside it.
Building a marketplace from zero is a different discipline from running marketing inside a mature business. Leaders who have only operated inside the enterprise tend to under-invest in supply-side acquisition and over-invest in demand-side spend. The question is how to apply enterprise marketing rigour to early-stage growth without losing the founder economics that make scale-up possible.
Most founders pitch the upside. Few have the discipline to talk honestly about the years between traction and exit, when capital tightens, partnerships stall, and the operating model has to be rebuilt mid-flight. Boards backing entrepreneurial leaders, and corporates trying to learn from them, need someone who has lived the full arc, not just the launch.
Most diversity programmes have stopped producing measurable change. Budgets stay flat or fall, while the political cost of running them rises. Leaders need someone who can rebuild equity as an operating practice inside talent processes, products, and AI tooling, not as a campaign that lives on the side.
Fatigue is the productivity tax most organisations refuse to measure. Sleep deprivation degrades decision quality, accelerates burnout and corrodes engagement, yet it sits outside the remit of most wellbeing programmes. Leaders need a serious treatment of recovery as an operating variable, not another mindfulness add-on.
Boards are being asked to make capital and workforce decisions on AI without a shared map of where the technology is actually heading. Internal teams default to either pilot-by-pilot caution or unchecked enthusiasm, and neither produces a defensible long-range position. What is missing is a credible read of what the next decade looks like, grounded in technology history rather than vendor marketing.
Talent scarcity is not a cycle. It is a structural condition, and most organisations are still running people strategies designed for a different labour market. The gap between what employees now expect from work and what employers are offering has widened, and compensation alone does not close it. Leaders who cannot articulate why their organisation is worth someone’s career will lose that competition consistently.
Most organisations have announced AI strategies that their non-technical employees cannot act on. Adoption stalls not because the tools are inadequate but because the majority of the workforce has no framework for integrating AI into the work they actually do. Leaders are caught between a small group of early adopters running unsupervised and a larger group that has quietly opted out, and neither is being served by communications built for engineers.
Workforces have absorbed wave after wave of restructure, system migration and AI rollout. Engagement is flat, change initiatives stall on adoption, and the people expected to deliver the next transformation are visibly tired of the last one. Leaders need a credible way to rebuild appetite for change without another corporate culture programme that lands as noise.
Most organisations have run AI pilots. Far fewer have managers who can govern AI decisions, interrogate model outputs, or redesign a process around an agentic system. The gap is not tooling. It is a workforce of decision-makers who do not yet know enough about AI to lead with it.
Most organisations have run AI pilots. Almost none have rebuilt how work actually gets done. The gap between board ambition and operational reality is where competitive position is now being lost, and senior teams are running out of room to keep treating AI as an experiment rather than an operating model.