Manage Your AI Investments Like a Portfolio

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Companies should apply a step-by-step portfolio management approach when it comes to AI.

Summary. Companies should apply a step-by-step portfolio management approach when it comes to AI. They should view the connected portfolio through a dual lens: first, as an advancement pipeline with clear gates through which projects must pass; and second, as awhole-portfolio dashboard that shows balances across risk/return, time horizon, capability areas, and mission alignment. This dual perspective enables both rigorous project-level discipline and strategic portfolio-level optimization.

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Business leaders now face intense pressure to transform their organizations with AI, even though the technology, public attitudes, and the competitive landscape are all still in flux. The result is often too many pilots with too little coordinated oversight. Without a way to systematically decide where to start, how fast to move, and when to stop, AI efforts quickly become a drain on attention and resources rather than a source of advantage. A familiar pattern recurs across many companies: isolated, piecemeal deployments, limited buy-in by senior executives, and weak linkage to strategic goals.

In 2018, one of us (Tom Davenport) argued that companies pursuing AI should create portfolios of projects based on business needs rather than rolling the dice on moonshots. That article identified the need for systematic portfolio development but stopped short of detailing how to build and manage such portfolios. This article completes that picture.

Organizations need to follow a disciplined step-by-step portfolio approach that treats AI innovation as a structured pipeline of projects that is managed by applying coherent, repeatable principles. This approach enables leaders to allocate scarce resources strategically, secure and maintain executive sponsorship across multiple initiatives, and sequence the right projects at the right time rather than chasing disconnected proofs of concept.

The approach described here builds on proven portfolio management approaches, including those that members of the author team have implemented across large organizations such as Northrop Grumman, PepsiCo, and units within the U.S. Army. While AI-specific deployments are still emerging, the adaptation presented here incorporates insights from both past and present implementations.

Why Take a Step-by-Step Approach to AI Portfolio Management?

Processes for managing R&D and new product development have long employed tightly defined go/no-go gates—known as “stage gates”to increase the likelihood of worthy innovations reaching the market. Combining these tools for managing project progression with a portfolio management approach to AI innovation addresses core failure modes for AI implementations. This approach ensures that every candidate project is judged not only on its standalone merits but also in relation to competing opportunities, enterprise priorities, and cross-initiative dependencies. At the same time, because projects progress through defined gates that assess their feasibility and strategic fit, organizations are protected from the distractions caused by a flood of strategically disconnected pilots.

The portfolio approach:

  • Elevates AI from a series of departmental experiments to a board-level strategic imperative.
  • Allows executives to view all current and planned AI initiatives on a single dashboard, including their interdependencies, resource requirements, and strategic alignments.
  • Formalizes a strategic approach to time-horizons across projects, enabling leaders to select a mix of projects across:
    • near-term implementations that build confidence and capabilities
    • medium-term initiatives that require deeper integration but deliver more substantial transformation
    • longer-term projects that offer transformational potential
  • Surfaces interdependencies across projects, allowing organizations to sequence initiatives so that earlier projects build foundational capabilities required by later, more sophisticated implementations.

Portfolio management has long enabled organizations to manage innovation in a holistic manner—capturing both top-down strategic imperatives and bottom-up opportunities, while unifying efforts horizontally across departments and developing strategies that build capabilities over time. The AI-specific portfolio approach adapts time-tested portfolio principles to AI’s unique characteristics.

How the Portfolio Runs

The step-by-step portfolio management approach views the connected portfolio through a dual lens: first, as an advancement pipeline with clear gates through which projects must pass; and second, as a whole-portfolio dashboard that shows balances across risk/return, time horizon, capability areas, and mission alignment. This dual perspective enables both rigorous project-level discipline and strategic portfolio-level optimization.

[Image: Hiroshi Watanabe/Getty Images]

Full article @ Harvard Business Review

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