[HPS Podcast: S01 E02] What Executives Need to Know Before Funding an AI Project

Invest with eyes wide open. AI can deliver tangible business impact, but only when paired with workflow redesign, strong governance, and skilled talent – not by deploying algorithms in a vacuum.

In fact, a McKinsey global survey finds companies are beginning to see bottom-line results by redesigning processes and putting senior leaders in charge of AI governance. More than three-quarters of organizations now use AI in at least one function, yet the biggest gains come when CEOs and boards oversee AI efforts and workflows are fundamentally reworked.

Think portfolio, not one-off. Treat your AI spend as a portfolio spanning build, buy, and blend options, evaluated continually. This means initially leveraging existing AI platforms or APIs for speed, then considering custom builds for strategic differentiation. Apply risk controls from day one – adopt frameworks like NIST’s AI Risk Management Framework (AI RMF) to structure governance.

The NIST AI RMF 1.0 defines four core functions for managing AI risks – Govern, Map, Measure, Manage – which provide a useful blueprint to ensure your AI investment has oversight, context understanding, performance metrics, and ongoing risk mitigation.

In short, balance ambition with accountability: secure quick wins with off-the-shelf AI where it makes sense, but put the guardrails and org structure in place early (e.g. an AI steering committee, risk assessment processes) to avoid costly surprises later.