Across finance, the pressure to “do something with AI” is intensifying.
Boards are asking for progress. Executives want tangible outcomes. New tools promise copilots, agents, and automation that will fundamentally change how work gets done. Yet inside many finance organizations, momentum is slowing rather than accelerating.
Not because AI isn’t powerful—but because something far more basic is missing.
Understanding.
Before finance can automate anything meaningfully, it must first understand what already exists.
Most conversations about AI in finance start with ambition. What can we automate? Which processes can we accelerate? Where can we eliminate manual effort?
These are reasonable questions. But they assume clarity. They assume finance teams have a clear view of where critical logic lives, how processes actually operate, and which pieces of work are truly foundational versus incidental.
In reality, that clarity is often absent.
And the absence becomes most obvious when teams look at their spreadsheets.
Spreadsheets are frequently described as a necessary evil—temporary tools that lingered too long or failed to be replaced. But that framing misses what they really are.
Excel isn’t a workaround. It is infrastructure.
Over time, spreadsheets have become the place where finance work actually happens. They hold calculations that matter, assumptions that drive decisions, and logic that never quite fit into formal systems. Even after major transformations, spreadsheets persist—not out of resistance, but because they fill the gaps that enterprise platforms inevitably leave behind.
Many finance leaders only grasp the scale of this dependency once a transformation is already underway, or even completed. That realization can be uncomfortable, particularly when the original business case assumed spreadsheets would largely disappear.
AI unquestionably changes what’s possible. It can read formulas, interpret VBA, surface patterns, and automate manual tasks that once consumed entire teams.
But AI doesn’t create understanding on its own.
It doesn’t tell you which spreadsheets matter most, which ones are variations of the same model, or where critical logic is quietly concentrated. It doesn’t explain how data moves across files, teams, and time. And it doesn’t provide a coherent picture of risk, duplication, or opportunity across an entire finance function.
Without that foundation, automation tends to emerge in pockets. Teams see local productivity gains, but those gains are difficult to scale. Confidence remains low, governance struggles to keep pace, and finance leaders hesitate to move beyond experimentation.
The issue isn’t a lack of AI capability. It’s a lack of visibility.
On paper, many organizations believe they understand their spreadsheet estate. There are inventories, registries, and documentation efforts meant to capture what exists.
In practice, these artifacts rarely reflect reality.
They list files, but not meaning. They capture names, but not logic. They provide a snapshot, but not an understanding of how spreadsheets are actually used, reused, and relied upon across the business.
This makes it hard to answer the questions that matter most. Which logic is truly scalable? Where do variations signal risk versus intentional design? Which data elements appear repeatedly, and how are they transformed along the way? Where are compliance issues most likely to emerge? And, critically, which parts of the estate are even ready for AI-enabled enhancement?
Until those questions are answered, automation remains constrained by uncertainty.
In response, a quiet change in mindset is emerging among finance leaders.
Rather than starting with how to automate, they are starting with what they have.
They are recognizing that visibility isn’t a bureaucratic exercise—it’s a strategic prerequisite. Understanding comes first. From understanding comes prioritization. From prioritization comes action that can be scaled with confidence.
This shift reframes transformation. Instead of speculative bets or incremental tweaks, finance teams can pursue progress that is iterative, grounded, and measurable.
The future of finance isn’t about eradicating spreadsheets. It’s about finally seeing them clearly.
For decades, the spreadsheet layer of finance has been too complex, too fragmented, and too opaque to optimize at scale. AI changes that—but only if finance has the visibility and governance to support it.
That’s why understanding must come before enhancement.
And it’s why Insights, as a core pillar of the Coherent platform, exists: to bring clarity to the spreadsheet layer of finance, so AI can be applied deliberately, responsibly, and at scale.
Because finance doesn’t need more automation ideas.
It needs a clear line of sight.
See the Platform in Action
If you're exploring how AI can elevate your financial workflows, a personalized walkthrough of the Coherent platform can show you what's possible with your own spreadsheet estate.