How AI in spreadsheets offers a practical path for business leaders

Many business leaders are struggling to implement artificial intelligence due to concerns over complexity, cost, and lengthy timelines, despite widespread adoption of AI tools at an individual level.

Recent survey findings indicate that 94% of backend engineers and IT decision-makers use AI tools such as Copilot and ChatGPT. However, only 39% of organisations have built reliable internal frameworks to support AI, pointing to ongoing challenges with reliability and scalability across industries.

AI through spreadsheets

Sebastian Dewhurst, Founder of EASA, has highlighted a practical route for organisations to begin integrating AI into daily operations by leveraging the widespread use of spreadsheets in business processes.

"Spreadsheets remain the backbone of financial modelling, forecasting, and operational planning," says Sebastian Dewhurst, Founder of EASA. "What many leaders don't realise is that AI can be embedded directly into those models, delivering immediate value without a major transformation programme. AI doesn't have to be intimidating - it can start with the tools you already know."

Dewhurst notes that many organisations are delaying AI adoption, believing it to be too difficult or costly to implement. The significant gap in support frameworks means projects are often delayed before providing substantial results.

"Business leaders often overlook the fact that AI doesn't need to be applied everywhere at once," Dewhurst adds. "The fastest route to adoption is often right in front of them: the spreadsheet."

Five focus areas

EASA's approach suggests that applying AI to spreadsheets can bring measurable improvements in five main areas: forecasting accuracy, anomaly detection, pricing optimisation, risk analysis, and supply chain performance.

In manufacturing environments, spreadsheet-based AI can assist with better demand forecasting, reduce stock shortages, and facilitate pricing strategies for bespoke orders. For financial services firms, spreadsheet-driven AI can assist with compliance reporting by automating anomaly detection and strengthening risk models for improved risk assessment.

Business benefits

By taking this incremental approach, Dewhurst says organisations can achieve a faster return on investment without the need for protracted and expensive new platforms.

According to Dewhurst, starting with spreadsheets makes innovation more accessible and enables safer adoption. Spreadsheets function as a practical testbed for experimenting with AI before rolling out more comprehensive solutions.

This approach enables manufacturers to refine their demand forecasting processes while financial teams can strengthen stress-testing for portfolios. This results in greater business agility, with the potential to achieve results on a much shorter timescale.

Advice to leaders

Sebastian concludes: "Business leaders need to rethink their approach to AI adoption. Don't wait for the perfect AI project to start. Look at the spreadsheets your teams already use. With the right tools, you can elevate them with AI and see tangible benefits today."

The trend of applying AI at the spreadsheet level highlights a more accessible and immediate route for manufacturers, financial services companies, and others to begin integrating artificial intelligence into their operations using existing software and workflows.