AI transformation consultants

AI transformation is changing an organisation’s roles, processes, skills and habits so that its people apply AI to their daily work. AI automates routine tasks within jobs and amplifies the work of people with deep expertise, and what an organisation gains depends on whether its people know what to ask of it and can judge what comes back. We run the work as a change programme in four phases: Opportunity, Prepare, Deliver, and Monitor and evolve.

We look for ten conditions before an AI programme starts, including leadership communities that are confident using AI in their own roles, identified use cases that will deliver value, a culture in which experimentation is encouraged within a safe environment, and an IT function willing to let people experiment. The first phase of a programme assesses readiness and identifies the gaps before money is committed.

Technical training, whilst useful, is not enough to get people to change their ways of working. It simply reduces their apprehension and, for those who go on to use it, increases their confidence. Our AI Study Group identified five human barriers to adoption: fear of job losses, a lack of basic digital skills, a lack of trust in AI and its output, a lack of communication and transparency, and a lack of leadership support.

We expect AI to change almost every job. It automates process tasks and amplifies expert work. Roles made up mostly of process tasks are the most exposed, although of the 32 roles our AI Study Group profiled, very few looked likely to be fully automated. Where AI frees capacity, leaders have to decide whether to put it into higher-value work or to consolidate roles and reduce headcount.

AI automates tasks such as data entry, scripted calls and standard processing, so roles made up mostly of these tasks change most. In roles built on expert judgement, relationships and synthesis, AI amplifies the work. The model behind our AI Impact Report 2026 estimates that AI could free the average UK worker 10.9 hours a week.

We expect organisations to become smaller and flatter, with fewer middle managers, a larger share of knowledge workers directing AI agents, tasks consolidated into new roles and some whole functions regrouped. Their leaders will need to be experts in their field, competent with AI and good at building relationships.

We expect it to make the work that remains more demanding. AI takes on low cognitive load tasks such as data entry and leaves judgement, synthesis and difficult conversations, which draw on attention, working memory and emotional regulation. Our research with the Centre for Evidence Based Management found that mental load from different sources adds up and can compound, so unclear goals, poor relationships, noise and interruptions do more damage when the rest of the day is demanding work.

We can’t give a reliable length until phase 01, Opportunity, is complete, because it depends on the scale of the use cases, how many readiness conditions are already in place and how much of the delivery you run yourselves. Phase 01 can be commissioned on its own, has a fixed end, and produces a use-case register with ROI modelling, a readiness assessment, role-level AI profiling and a strategic roadmap.

No. We are independent: we broker nothing, resell no one’s technology and take no share of what gets built, so we are paid the same whichever tools you choose.