AI ROI: Why It Feels Hard — and How to Finally Unlock It

Artificial Intelligence (AI) promises efficiency, cost savings, and innovation. Yet for many CFOs, COOs, and analytical leaders, a blunt question hangs in the air: Where is the return on investment?

A recent study found that 74% of companies still haven’t seen tangible value from their AI investments.

Here’s the truth: The problem isn’t AI. It’s how organisations choose, measure, and manage AI initiatives.

Why ROI Feels Hard to achieve – and how to change that

Many organisations fall into the same trap: measuring activity, not impact. Success is often reported in terms of “projects launched” or “hours saved”, but these don’t tell you whether AI is improving profitability or customer outcomes.

The real question is: Is AI moving the metrics that matter to your business? Success should be measured against outcomes that drive value – cost savings, revenue growth, risk reduction, and customer experience improvements.

The Missing Piece: Choosing the Right Problems to Solve

ROI doesn’t begin at deployment. It begins at use‑case selection. At Naitive, we call this the AI Applicability Sweet Spot – the overlap between:

• a real, meaningful business need, and
• a feasible AI capability that can address it.

Most stalled AI projects fail not because the technology doesn’t work, but because they were aimed at the wrong target. If your starting point is wrong, ROI becomes almost impossible.

Three Steps to Get It Right

1. Start with the baseline: Capture the current state – cost per transaction, conversion rates, error rates – before AI enters the picture.
2. Track the delta: Measure the change AI delivers over time. If you can’t show improvement against the baseline, the ROI story falls apart.
3. Look beyond numbers: Some of AI’s biggest wins are qualitative – better decisions, faster responses, happier customers. These often lead to hard financial gains later.

Real-World Metrics That Matter

Fintech & Banking

• AI-driven personalisation can lift cross-sell rates by 10–15%, increasing revenue per customer.
• Automating compliance checks can cut processing costs by 20%, freeing teams for higher-value work.

Healthcare

• AI Transcription can be utilised to improve clinical note accuracy whilst also reducing time-per-appointment.
• Diagnostic AI can improve accuracy by 4–5%, directly impacting patient outcomes.

When you measure these kinds of results, ROI stops being a mystery – it becomes a roadmap.

The Naitive Approach: Results, Not Hype

ROI starts before implementation – it starts at the moment you choose the right problems to solve. At Naitive, we believe that AI can pay off – but only if you use the right yardsticks. Every AI project we deliver is anchored to clear, business defined outcomes. We work with clients to define what success looks like up front, set baselines, and track progress transparently. This results-oriented approach builds trust and ensures that AI investments deliver real, measurable value.

Final Thought

AI is not a magic bullet, but when measured and managed correctly, it can be transformative – reducing admin, boosting efficiency, and freeing your teams to focus on what matters most. The key is to move beyond activity and focus on business outcomes.