Getting Excel Ready for Enterprise AI
Why Excel matters in the enterprise AI conversation
AI has quickly become a top priority for most organizations. Investment is accelerating, experimentation is widespread, and expectations are high. Yet, for many, meaningful business value remains elusive. One of the most overlooked reasons sits in plain sight: Excel.
Excel remains deeply embedded across finance functions and broader enterprise workflows. In many institutions, there are thousands of critical workbooks supporting finance alone—and in some cases, millions of spreadsheets across the organization. This scale is often seen as a challenge, but it also represents a significant opportunity. Not every workbook is a candidate for AI, but the sheer pervasiveness of Excel creates a large surface area for impact—if organizations can approach it in a structured and scalable way.
Part of that opportunity exists because Excel is still one of the most manual layers of enterprise infrastructure. Despite years of transformation programs, it is often the piece left behind. Many spreadsheet-driven processes remain repetitive, time-consuming, and low value in isolation, yet critical to the business. These characteristics make them well suited to AI. Unlike other enterprise systems that have already been optimized, Excel-based workflows have largely not, which means the potential for productivity gains is significant.
What makes Excel particularly compelling in the AI journey is that it can be addressed incrementally. Organizations do not need to commit to large-scale transformations upfront. They can start with a subset of high-impact workflows, demonstrate value, and expand from there. This creates a more practical and culturally aligned path to adoption, especially for organizations that are still early in their AI journey.
The real barrier, however, is not technology—it is visibility. Most organizations do not have a clear understanding of their Excel estate, which has typically evolved over decades. There is often limited awareness of what spreadsheets exist, how they are connected, and how data flows between them. Many critical workbooks were built years ago by individuals no longer in the organization, yet they continue to underpin key processes. This creates both operational risk and challenges in scaling any form of automation.
To move beyond isolated experimentation, organizations need a structured path. The first step is discovery—building a clear inventory of spreadsheets and understanding their role within business processes. This visibility enables better prioritization and lays the foundation for everything that follows.
From there, risk and governance become critical. Applying AI without understanding and control can simply accelerate existing issues. Establishing clear ownership, controls, and monitoring ensures that automation is both effective and trusted across the organization.
Only once these foundations are in place can organizations begin to scale AI in a meaningful way. Early use cases often focus on areas such as data movement across spreadsheets, reconciliation processes, and other manual workflows. While these may not always be the most visible parts of the process, they are often where the greatest efficiency gains can be realized.
The broader opportunity, however, goes beyond individual workbooks. AI enables organizations to operate across entire Excel estates—identifying patterns, mapping dependencies, and creating structured views of previously fragmented assets. Combined with contextual information such as policies, regulations, and external data, this allows workflows to be executed more efficiently while improving consistency and control.
The impact of this shift is not just operational. As manual work is reduced, finance teams can focus more on analysis, forecasting, and decision support. This creates a path for finance to move beyond traditional control functions and play a more strategic role in driving business outcomes.
For many years, Excel has been viewed as a necessary liability. That perspective is beginning to change. With the right visibility, governance, and AI capabilities, Excel can be repositioned as a strategic asset within the enterprise AI stack.
At Coherent, this is exactly the problem we focus on—helping organizations bring visibility, control, and structure to their Excel estate, and then using AI to unlock value at scale. The goal is not to replace Excel, but to make it enterprise-ready for AI.
If you’d like to explore this topic further, you can watch the full webinar on demand here:
https://hubs.la/Q047pcGd0
