Leadership

Should we keep investing in AI?

The board approved the mandate on a promise. The question now is what evidence justifies continuing.

The first AI investment was approved on the promise of greater productivity, faster decision-making, and stronger business performance. Two years later, the technology has largely been deployed, budgets have been spent, and the board is asking a different question:

Should we continue investing?

It is one of the most important decisions an executive team will make, because the original business case is no longer enough. Future investment requires evidence that AI is creating measurable business value.

The wrong question, and the right one

The question most organisations ask is: “Is the technology working?”

In most cases, the answer is yes. The software is installed, accessible, and functioning as intended.

Yet business value remains difficult to demonstrate.

The better question is: “Where is business value being created, and where is it breaking down?”

Technology is only one part of the value chain. Leadership decisions shape the organisational environment. That environment influences workforce behaviour. Behaviour determines adoption, and adoption determines whether AI investment becomes measurable business value.

When business value falls short, the breakdown usually occurs somewhere along that chain, not within the technology itself.

Continuing blindly and cutting blindly are both expensive

Without evidence, organisations face two equally costly decisions.

Continue investing, and additional capital may be committed to a programme that will never deliver its intended value.

Stop investing, and funding may be withdrawn just before meaningful business value begins to emerge.

Neither decision should rely on optimism, anecdote, or assumptions.

There is also a governance responsibility. As AI investment grows, boards need evidence that capital is being allocated responsibly, risks are understood, and expected business outcomes remain achievable.

The decision this informs

The question is not simply: “Should we continue investing in AI?”

The better question is: “Where should we continue investing, where should we pause, and where should we stop?”

Those decisions require evidence.

Our LEAD™ Framework identifies where the AI value chain is succeeding and where it is breaking down. Combined with our DRIVE™ Adaptability Diagnostic, organisations can measure readiness before further investment and evaluate adoption and business value after implementation.

This enables AI investment decisions to be guided by evidence rather than assumptions.

Before approving the next phase of AI investment, identify where business value is being created, where it is breaking down, and where additional capital will generate the greatest return.