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The Executive Guide to AI ROI

Michael Deeming

Michael Deeming

Moving beyond vanity metrics to measure the real business impact of AI investments.

When boards and executive teams ask about AI ROI, they're often met with metrics that don't connect to business outcomes: model accuracy percentages, inference speeds, or user engagement statistics. While these measures have their place, they rarely answer the fundamental question: is our AI investment creating value?

The challenge is that AI value often manifests differently than traditional IT investments. The benefits can be indirect, distributed across multiple processes, or only apparent over longer time horizons.

Principles for Measuring AI ROI

Start with the Business Problem

Successful AI ROI measurement starts with clear articulation of the business problem being solved. If you can't explain how the AI initiative connects to revenue, cost, risk, or strategic capability, you're not ready to measure ROI.

Look Beyond Efficiency Metrics

While time and cost savings are important, the most valuable AI applications often enable entirely new capabilities or decisions that weren't possible before. Consider:

  • Revenue enablement — new products, services, or customer segments
  • Decision quality — better outcomes from improved insights
  • Risk reduction — avoided losses and improved compliance
  • Speed to market — faster delivery of products and services

Account for Learning Value

Even AI pilots that don't scale provide organisational learning that accelerates future initiatives. Factor this into your ROI calculations:

  1. Technical capabilities developed
  2. Data infrastructure improvements
  3. Team skills and experience
  4. Understanding of what works (and what doesn't)

Consider the Cost of Inaction

In competitive markets, the relevant comparison isn't AI versus the status quo—it's AI versus competitors who are already moving forward.

Building Measurement Into Your Process

Build measurement into your initiatives from the start. Retrofitting ROI measurement onto existing programmes is far harder than designing it in from day one.

"The organisations seeing the best returns from AI are those who treat measurement as a strategic capability, not an afterthought."

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