Certinia Report: Spreadsheet Data Sprawl Curbs AI Gains in 2026

What happened

Certinia has published its 2026 Global Service Dynamics Report, a study of professional services organisations worldwide that finds fragmented data — much of it still sitting in spreadsheets and disconnected systems — is limiting how much value these firms can extract from artificial intelligence. The research, commissioned by Certinia and reported by Diginomica, reinforces a message the industry has heard before: AI performance is only as good as the data foundation underneath it.

Rather than surfacing a new problem, the report puts fresh weight behind a familiar one. Professional services firms have been investing in AI tools and automation, but many are discovering that inconsistent, siloed or manually maintained data — particularly in spreadsheets used for planning, resourcing and reporting — is blunting the return on those investments.

Why it matters

For leaders weighing AI investment, the finding is a reminder that model quality and feature lists are not the binding constraint most organisations face — data readiness is. Professional services firms run on operational data: utilisation, project margins, resource allocation, client billing. When that information is scattered across spreadsheets and disconnected point solutions, AI tools built on top of it inherit the same gaps, producing recommendations or forecasts that staff don't fully trust.

This has implications beyond IT. Data sprawl slows decision-making, creates rework for employees who reconcile numbers across systems, and ultimately shapes the experience clients get — from the accuracy of a project estimate to the responsiveness of account teams. Digital transformation programmes that lead with AI tooling before addressing data architecture risk delivering underwhelming results and eroding internal confidence in the technology.

The Renascence take

The instinct in many organisations is to treat AI adoption as a technology purchase. This report is another data point suggesting it's actually an operating-model and data-governance exercise wearing an AI label.

Most professional services firms don't have an AI problem — they have a data-ownership problem. Spreadsheets persist not because staff love them, but because they're the fastest way to get a job done when the "official" system is slow, incomplete or untrusted. That's a behavioural signal, not a technology gap: people build workarounds when the sanctioned process fails them. Fixing this means redesigning how data is captured and governed at the point of work, not just layering AI on top of what already exists. Operators serious about AI returns should audit where and why spreadsheets are still doing the heavy lifting before they invest further in models sitting on shaky foundations.