When abundance complicates strategy

Contrary to expectations, artificial intelligence does not simplify strategy but complicates it. This is because AI generates an "analytical abundance" that makes it possible to justify several possible futures at once. For decision makers, the challenge is no longer finding information but choosing a path and committing to it.

In the boardroom of a software company, directors flip through dashboards that lay out dozens of market scenarios, each backed by AI models promising the definitive answer. The expectation is that artificial intelligence will reduce uncertainty, but what they get is an overload of options that paralyzes decision-making.

The paper published in California Management Review, based on interviews with leadership teams and on an analysis of strategic projects where AI was applied, shows how analytical capacity has been democratized and multiplied. The authors describe an architecture of three cycles (strategic intelligence, strategic choice and strategic change) to map the whole process and detect where friction arises.

The results reveal that, far from simplifying, analytical abundance creates a condition of "multiple futures" that coexist as plausible options. Teams report that generating insight is no longer the bottleneck. The real challenge becomes defining a clear route and keeping the commitment against the temptation to keep exploring alternatives. The paradox is that more data widens the sense of control but erodes the ability to close a decision.

Adopting the three-cycle architecture means formally separating the information-gathering phase from the strategy selection phase and, finally, from its implementation. In practice, that means institutionalizing "closing" moments where a scenario is chosen and resources are aligned, and creating follow-up mechanisms that reinforce adherence to the chosen plan, so that analytical abundance does not reopen the discussion.

Conclusions

• Artificial intelligence, by generating more analysis, makes strategic decision-making more complex.
• The main obstacle for companies is no longer a lack of data but the difficulty of choosing among multiple valid options.
• Strategic success requires not only understanding the landscape but also closing options and securing the organization's commitment.
• It is essential to separate strategic intelligence from choice and from the implementation of change in order to manage this new complexity.