AI Product Management / AI Strategy

Every available report shows that AI is one of the most key areas of job growth right now, and AI product management and AI strategy roles sit at the heart of that, reflecting the fast pace with which AI has moved from experimentation to product deployment across many sectors.

When hiring for AI product management roles, managers are seeking a specific combination of technical ability and product-focused thinking. Without necessarily being engineers, strong candidates can bring an understanding of the fundamentals of machine learning system function, which means training data, model evaluation and the practical constraints of deploying AI in production. They can define clear problem statements, work with data science teams and engineering teams on feasibility, and negotiate around the challenges of probabilistic systems. In particular, strong candidates are able to communicate uncertainty and failure modes to stakeholders.

At a slightly more senior level, AI strategy roles focus on the ‘why’ behind AI use within an organisation and lead the way on how businesses identify, prioritise and operationalise AI opportunities. Roles like this often mean working at the intersection of technology, commercial strategy and change management, and need to be able to engage in a credible and meaningful way with technical teams and leadership.

Even in non-engineering roles, you will be expected to have familiarity with the current AI landscape: foundational models, LLMs, RAG architectures and the major cloud AI platforms. It’s also important for senior appointees to understand AI governance, responsible AI principles and the emerging regulatory landscape, including the EU AI Act.