Finance departments can be slow to adopt new technologies. Our most recent State of Strategic Finance report found that just over half (57%) of financial professionals are using AI for some aspect of financial operations.
But despite some measure of AI adoption, they also haven’t left their trusted tools behind: 89% are still relying on Excel for financial modeling and calculations, data analysis, budget input collection and revenue planning.
At first glance, this looks like an inherent contradiction: Why embrace the latest in technology while also clinging to a spreadsheet tool that’s in its late 30s? But as new as AI is, the need for quality financial data isn’t new, and because of that, AI and Excel aren’t at odds. They’re converging to reshape financial planning and analysis. Financial professionals really can have it all.
Why we (still) love Excel – and AI too
Spreadsheets still dominate financial professionals’ lives. A 2025 AFP FP&A report showed that 96% of respondents used spreadsheets for planning and 93% for reporting on a daily or weekly basis.
Speaking realistically, that means they’re using some form of Microsoft Excel, because there are a reported 1.2 billion users of Microsoft Office, and an estimated two-thirds of that population uses Excel, bringing us to 800 million Excel users. Some of this is due to sheer inertia, since Excel has been the platform of choice for more than 30 years, but some of it is due to the sheer amount of functionality and ease of use packed into one program.
Excel may be the foundation of financial departments around the world, but AI is emerging as a significant game-changing tool in its own right. A late 2024 survey of finance leaders from Gartner found that they had four top use cases for AI in their departments:
- Intelligent process automation (44%)
- Anomaly and error detection (39%)
- Analytics (28%)
- Operational assistance and augmentation (27%)
For example, let’s take a closer look at the second most popular use case, error detection. One small mistake in a spreadsheet can lead to cascading errors over time and hours spent searching for the root of the problem. AI, however, is much better at parsing large amounts of data to spot the error far faster than a human could.
On top of these use cases, AI models are also improving in their understanding of business and accounting concepts. For example, users can ask models about last year’s gross profits for the fiscal year in natural language and get a response without providing the formula – again, saving them time.
AI and Excel together
Microsoft itself has also been encouraging the AI and Excel relationship through the integration of Microsoft 365 Copilot. In the specific case of Excel, Microsoft’s stated goal is to help users “get more done with less effort.”
So far, Microsoft has integrated features such as the following:
- Data cleaning: Asking Copilot to find and correct errors, duplicates and formatting issues
- Complex formulas: Suggesting formulas based on the nature of the data at hand
- Smart suggestions: Better ways or shortcuts – even for creating pivot tables
Other providers in the Microsoft ecosystem have jumped in as well to provide plugins and extensions, mostly keeping users within the Excel interface. The goal isn’t to give people a new platform to master, but, as Microsoft itself puts it, to augment tools: “Even if you’re not an Excel expert, the user-friendly design of Copilot in Excel makes it straightforward to use.”
This has the added benefit of addressing a major challenge hindering AI adoption as identified by Gartner, among others. Currently, teams don’t necessarily have the technical skills or data literacy to make the most of AI; it’s simply moving that fast. This user-focused approach, however, is actively encouraging them to develop those skills without feeling forced.
Looking ahead: Both not either/or
Vena’s research quantifies what we’re seeing in customer implementations: They want Excel and more. In this model, Excel operates as the front end where users capitalize on their deep experience with the platform, and AI helps accomplish the heavy lifting without complicating matters further.
In the same way, AI augments professionals’ contextual knowledge and judgment, too: It can surface patterns or anomalies they may not see. As a result, finance teams can operate faster, more flexibly, with more agility and more strategically.
Since the second half of 2024, the ROI of AI has become increasingly apparent. According to McKinsey, strategy and corporate finance were the functions that saw the biggest ROI gains this year – from 43% in H1 2024 to 70% in H2. This suggests that adopting AI is quickly becoming a competitive advantage and that the 43% of finance leaders not using AI may want to reconsider that plan.
As adoption accelerates, solutions providers will respond by further embedding AI into the tools finance departments want. Microsoft itself will continue its direct investment; smooth integration with the Excel platform will be a major selling point for data engines, and APIs or connectors as bridges to other cloud-native AI tools will continue to emerge.
We’re quickly moving into a future where financial professionals who can blend traditional spreadsheet skills with AI literacy – without having to write code – will bring significant advantages to their organizations. It’s not one or the other. There’s room for both AI and Excel in the finance department.
