Future of Work
Voices shaping how organisations adapt to automation, hybrid models and shifting expectations of work
Five generations now share the same office, the same Slack channel and the same expectations of their employer, and almost none of those expectations agree. Engagement scores are sliding, managers feel outnumbered by their direct reports’ demands, and the post-pandemic settlement on hybrid work has hardened into resentment on both sides. The work is no longer to defend a culture. It is to rebuild the social contract between the organisation and the people who turn up to it.
Most cultures decay quietly while leaders are busy fixing other things. Engagement scores drop, the best people leave first, and remote and hybrid setups make the drift harder to see. The work is figuring out which few cultural levers actually move performance, and pulling them with discipline rather than rituals.
Women leave technology and senior roles at every stage of the pipeline, and the reasons are now well documented: a culture that rewards perfectionism over risk, and a workplace built for workers without caregiving responsibilities. Most organisations respond with policy statements and employee resource groups. What they need is a structural account of why their female talent is stalling and a tested set of interventions that work.
AI has moved past the pilot stage and into the documents, decisions, and reasoning that organisations rely on. The problem is no longer adoption. It is what happens to institutional judgement when the conditions under which it is formed are quietly rewritten by the models in the loop.
Most planning tools were designed for a world that no longer exists. Strategy cycles built for predictable horizons break down when disruption compounds across technology, climate, and social change simultaneously – producing false confidence rather than genuine foresight. Organisations that cannot distinguish structural change from noise will always be reacting to a future someone else shaped.
Most enterprises now have an AI strategy on paper and very little of it in production. The board wants returns, the engineering organisation is still rewriting pilots, and personalisation, agents and generative AI are stuck behind unresolved questions on data, privacy and operating model. The gap between AI ambition and AI in revenue is now the defining technology problem of the cycle.
AI is raising the floor for every company at once. The same models, the same speed, the same outputs are now available to every competitor in a category. The danger is no longer falling behind on adoption. It is spending heavily to arrive at the same place as everyone else, faster but indistinguishable.
Younger consumers and workers no longer accept the trade-offs older marketing playbooks were built on. They expect brands to take a position, deliver on it, and prove it in the product, not in a campaign. Most commercial and brand teams are still reaching them with research that is one cohort behind the cultural reality.