AI will make Excel even more popular, not less, and the numbers support it. For years, the prevailing narrative in finance technology has been that artificial intelligence would finally push Excel into retirement. Dedicated FP&A platforms, cloud-based planning suites, and BI dashboards were supposed to render the humble spreadsheet obsolete. Yet the opposite is happening.
A recent industry survey of more than 430 finance professionals found that 90% of respondents still use Excel. This is for at least some of their modeling and reporting, even at organizations with $1 billion or more in annual revenue. Nearly a quarter of large enterprises reported relying on Excel as their primary planning tool. Spreadsheets weren’t a legacy habit fading into the background, they were, and remain, the active, everyday reality of financial planning and analysis (FP&A).
That single data point tells a bigger story about where finance AI tools are headed. It also tells why the future of Excel in finance looks brighter, not dimmer.
Why Excel Is Still Popular Despite the Rise of Finance AI Tools
The assumption that Excel can’t scale isn’t wrong. For large, decentralized organizations, spreadsheets genuinely struggle with dynamic, connected planning across remote teams. This is because real-time updates and a single source of truth are spread across fragmented systems. That’s precisely the gap dedicated FP&A software was built to fill.
But scalability limitations don’t explain why finance teams keep returning to Excel anyway. It includes teams at companies that have already paid for enterprise planning platforms. The same survey found that 61% of respondents still use spreadsheets as a primary budgeting and forecasting tool, even when FP&A software is available to them.
The reason isn’t sophistication. It’s familiarity. Excel is where finance professionals already work. It’s the tool they were trained on. It’s the interface they trust, and the format nearly every stakeholder in a business (from department heads to the CFO) already knows how to read. Rather than replacing that familiarity, AI is being built directly into it.
AI-Powered Excel Workflows Are Becoming the New Standard
Instead of asking finance professionals to abandon spreadsheets for a new interface, AI developers are bringing intelligence into the environment finance teams already use. Copilot, Azure, and Fabric have been steadily layered into the Excel experience. Newer integrations with AI models are extending what a spreadsheet can do without changing what a spreadsheet is.
This shift matters because it lowers the barrier to entry. A finance professional doesn’t need to learn an entirely new platform, a new query language, or a new interface to benefit from AI. They can prompt a model directly inside the tool they’ve used for years and get support cleaning data, building formulas, reconciling accounts, or building out a financial model in a fraction of the time it used to take.
This is where AI prompting becomes a genuinely useful finance skill. Knowing how to ask an AI model the right question. Asking AI with the right context, the right constraints, and the right level of specificity is quickly becoming as valuable as knowing which formula to use. AI and spreadsheet automation are no longer separate categories. They’re converging inside the same cell grid finance teams have relied on for decades.
What This Means for AI in Finance Professionals’ Day-to-Day Work
The same survey data that confirms Excel’s staying power also reveals why finance teams are eager for this kind of AI support in the first place. Data quality and availability were cited as the top bottleneck for FP&A teams, reported by 58% of respondents. More than half said they experience revenue forecast variances greater than 6%. Only 34% said they’ve fully integrated real-time operational drivers (like unit sales, headcount, or marketing spend) into their forecasting models.
TThese are exactly the kinds of problems AI-powered Excel workflows are suited to address:
- Cleaning messy inputs;
- Flagging inconsistencies;
- Connecting siloed data sets;
- and speeding up the manual work that keeps analysts from spending time on higher-value analysis.
Seventy percent of finance leaders in the same survey reported that their C-suite had already mandated AI adoption across finance. More than a third expect AI agents to manage over half of their FP&A workflows within the next two years.
None of that requires finance professionals to leave Excel behind. If anything, it requires deeper AI literacy within the tool they’re already using.
Is AI Replacing FP&A Software?
Not exactly. It’s redefining the playing field!
It’s worth being clear-eyed about what’s actually changing. AI isn’t eliminating the need for structured planning processes, audit trails, or multi-user collaboration. These are core problems dedicated FP&A platforms were built to solve. What’s shifting is where those problems get solved.
As AI models become more capable of connecting to existing business systems, more of that planning, reconciling, and forecasting work can happen inside tools finance teams already own (including Excel) rather than requiring a separate, specialized application. That doesn’t mean FP&A platforms disappear. It means the competitive bar for justifying a dedicated platform’s price tag keeps rising, and Excel keeps absorbing more of the intelligence that used to require leaving it.
For finance professionals, the practical takeaway isn’t that spreadsheets are being replaced by AI. It’s that spreadsheets are being made smarter by it.
The Real Skill Shift From Building Models to Auditing Them
Perhaps the most significant change AI brings to Excel isn’t technical, it’s about what “being good at Excel” will actually mean going forward.
For decades, deep technical mastery of Excel (advanced formulas, array logic, complex model architecture) was a genuine career differentiator. That’s changing. As AI takes on more of the model-building itself, the ability to construct a spreadsheet from scratch matters less than the ability to evaluate whether the spreadsheet AI just built is correct.
This is where model auditing, interpreting AI outputs, and human oversight become essential finance AI skills. It’s not enough to accept whatever number an AI model produces. Finance professionals need the judgment to catch a broken formula, question an unrealistic assumption, or recognize when a forecast doesn’t match operational reality. AI auditing such as reviewing, testing, and stress-testing AI-generated outputs before they inform a business decision, is quickly becoming as core to the job as building the model once was.
The professionals who will get the most value out of AI in Excel won’t necessarily be the fastest formula-writers. They’ll be the ones who know how to direct AI toward the right task, and who have the experience to recognize when its output can (and can’t) be trusted.
Excel’s Future Is More Intelligent, Not Less Relevant
The data is hard to ignore: spreadsheets remain deeply embedded in how finance teams operate, and that isn’t likely to change anytime soon. What is changing is the amount of intelligence built into every cell, formula, and workbook.
Rather than displacing Excel, AI is reinforcing its position as the connective tissue of finance work: accessible, familiar, and now considerably more capable. As AI prompting, model auditing, and interpreting AI outputs become standard finance AI skills, and as AI-powered Excel workflows continue to mature, one conclusion becomes increasingly hard to avoid: AI will make Excel even more popular than it is today.
