Manage Your AI Investments Like a Portfolio | Harvard Business Review | – BRIAN HEGER

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As organizations accelerate their use of AI, many are ending up with too many disconnected pilots and too little strategic coordination. In response, this article argues that AI investments should be managed as a portfolio rather than a collection of experiments. It introduces a step-by-step approach designed to help leaders determine where to start, how quickly to progress, how to balance short-term value with long-term capability building, and when to stop or redirect initiatives. The portfolio progresses through four stages: 1) Opportunity (Outline), where ideas are surfaced and triaged; 2) Design & Partnership (Partner), where dependencies, governance, and capability needs are clarified; 3) Experimentation (Experiment), where initiatives are tested as learning journeys rather than validation exercises; and 4) Scale & Operate (Navigate), where solutions are deployed and sustained. One part of the framework that especially resonated with me was Stage 1: Opportunity, and the emphasis on making fast “no” decisions. This phase is explicitly designed to identify and eliminate weak, misaligned, or premature ideas early—before time, credibility, and political capital are wasted. Building on this, I’m resharing a one-page editable worksheet I created to help HR leaders and their teams identify which AI-enabled, HR-related use cases are most likely to generate business value by starting with business-first questions before jumping to solutions. While these are just a few sample questions and far from exhaustive, this type of structured questioning can help HR leaders and their teams guide the organization toward more disciplined AI portfolio decisions.
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