It’s the first thing you open in the morning, and the last you close at night. The home of your actuals, forecasts, and everything in between. The financial plumbing that the world’s largest companies rely on.
On the surface, it’s just a digital grid. But even as new tools do their best to disrupt it, the humble spreadsheet remains the beating heart of finance. It’s flexible, powerful, endlessly customizable—and nearly half a century later, still ubiquitous.
In this post, we’ll look at how spreadsheets became the most enduring software in business, and how they’re evolving again—this time with a dose of AI.
From ledgers to LANPAR: Where it all started
Spreadsheets got their name from the way accountants used to lay out the numbers—literally spread across facing pages in massive ledger books. Rows represented transactions, and columns represented dates, debits, and credits.
It was a great way to keep things organized, but updates were a nightmare. Change one number, and you’d have the unenviable task of recalculating the rest by pencil and adding machine.
This was how finance ran for decades. Precision and plenty of patience were required to keep everything in balance. But as computers started to emerge in the 1960s, finance pros started asking themselves if this new tech could take on the monotony.
That idea eventually became LANPAR—short for LANguage for Programming Arrays at Random—developed in 1969 by Canadian programmers Rene Pardo and Remy Landau. It introduced features that we now take for granted: forward referencing, natural order recalculation, and true cell addressing, just to name a few. Industrial behemoths like AT&T and Bell Canada used it to build budgets and run forecasts on mainframes.
At the time, it was groundbreaking.
However, despite its innovative capabilities, LANPAR failed to gain mainstream adoption. It was powerful but inaccessible—built for engineers, not everyday analysts. Ultimately, LANPAR offered a glimpse of what was possible with electronic spreadsheets but remained out of reach to the average user.
The real breakthrough came a decade later when spreadsheets moved from the mainframe to the desktop.
VisiCalc and the birth of modern modeling
The year was 1979, and Harvard Business School student Dan Bricklin was watching his professor work through a financial model on the blackboard—erasing, rewriting, and recalculating by hand every time a number changed. It was painfully tedious. There’s got to be a better way, Bricklin thought.
So he teamed up with his classmate Bob Frankston, and they set out to build one. Soon after, VisiCalc was born.
Short for “visible calculator,” VisiCalc was the first electronic spreadsheet built to run on personal computers. It did exactly what Bricklin had imagined: let users enter values, write formulas, and see the entire model update in real-time. No mainframe. No punch cards. Just a grid and a keyboard.
It was an instant hit. Tasks that used to take 20 hours now took 15 minutes. Analysts could run what-if scenarios on the fly. And for the first time, you didn’t need to know how to code to run powerful models yourself.
The software was so popular that many companies bought Apple IIs just to run VisiCalc. Steve Jobs later called it the thing that helped put Apple on the map—the first “killer app” that made the hardware worth buying.
More than anything, VisiCalc changed what it meant to do financial analysis. For the first time, business users had a tool that let them explore—not just record—ideas. The grid became a space to model possibilities and pressure-test decisions.
The spreadsheet was no longer just a calculator. It was a canvas for thinking.
Lotus to Excel: The golden age of spreadsheets
If VisiCalc lit the spark, Lotus 1-2-3 poured gasoline on the fire.
Released in 1983 for the IBM PC, Lotus 1-2-3 took what VisiCalc started and brought it to a whole new level. It combined spreadsheet modeling, charting, and even basic database functionality into one seamless experience.
You could:
- Automate tasks with macros
- Visualize trends with built-in charts
- Build forecasts that actually scaled
For finance teams in the ’80s, it felt like a superpower.
Lotus quickly became the gold standard. If you were building an M&A model or a five-year plan, chances are you were doing it in Lotus. It was the Swiss Army knife of finance—and for a while, it looked unstoppable.
Then Excel came onto the scene.
When Microsoft introduced Excel for Windows in 1987, it upended the status quo. The interface was cleaner. The features were deeper. Pivot tables made slicing and dicing data a piece of cake. And as Windows swept through corporate IT departments, Excel came along for the ride.
Visual Basic also gave finance teams a whole new gear. They began to think of themselves as quasi-engineers—hacking together workflows, layering in third-party plugins, and turning spreadsheets into mini software applications.
By the mid-90s, Lotus was fading. Excel had become the new default—and the rest, as they say, is spreadsheet history.
What made Excel so sticky? It hit the sweet spot: sophisticated enough for power users to run Monte Carlo simulations or spin up multi-tab forecasts, yet simple enough for anyone to track expenses or build a basic budget. And if it didn’t do what you needed out of the box, chances are someone had a workaround—or you could build one yourself.
More than just winning the spreadsheet wars, Excel became the universal language of finance.
Why spreadsheets still run the show
Since the 90s, the spreadsheet has been under siege. ERPs, EPMs, BI platforms, and a host of cloud-native tools have all promised to be the thing that finally renders it obsolete.
None have.
No matter how slick the interface or powerful the functionality, nothing has been able to replicate the spreadsheet’s most valuable trait: its flexibility.
That’s not to say spreadsheets haven’t leveled up. Google Sheets introduced real-time collaboration—instead of emailing files back and forth, teams could work together in the same document. Then came tools like Airtable and Smartsheet, rethinking the spreadsheet as a home for everything from project plans to campaign calendars. The use cases widened, but the core value proposition remained intact.
At the end of the day, finance teams need a place to think. A space to test assumptions, model scenarios, and poke holes in their plans. Most of the tools that tried to replace spreadsheets missed that part. They focused on structure, not flexibility.
That’s why, even in tech stacks filled with specialized systems, the spreadsheet still holds its ground. Not because teams are stuck in old habits, but because it still does something that nothing else can.
Will AI finally dethrone the spreadsheet?
Ok, you may be thinking, the spreadsheet may have survived broadsides from ERPs, EPMs, and a wave of cloud-based tools, but it’s no match for a technology as powerful and all-encompassing as AI.
Many share this belief, but we’re not buying it. If history’s taught us anything, it’s that spreadsheets will find a way to evolve.
And that’s exactly what’s happening as we speak.
Tools like Excel Copilot, Google Gemini, and Aleph are folding AI directly into the fabric of the spreadsheet, turning tasks that used to eat up half your afternoon—writing formulas, building charts, running summaries—and turning them into natural language prompts. Need a quick variance breakdown or a heatmap of spend? Just ask for it, and boom—it’s ready in seconds.
But speed is just one part of the equation. More importantly, AI is changing what the spreadsheet is on a fundamental level. When it starts automatically serving up insights, flagging anomalies, and helping you connect the dots, it becomes more of a thinking partner than a tool.
Take Aleph Scan for example, which can activate AI as a way to analyze changes and surface variance without even having to leave your spreadsheets. Need to see what happened between your budget and your actuals last month? Scan it.
Magically, AI-generated commentary fills your spreadsheet, telling you exactly what happened, where to look, and how to access the underlying data with one-click drilldowns.
Making this kind of analysis so easy and effortless shifts the finance’s focus from data hunting to decision-making. It translates into more frequent analysis, having the capacity to lower thresholds, better collaboration, fewer issues flying under the radar, more accurate forecasting, and the list goes on.
That shift is raising the bar for what finance teams expect from their applications—and from themselves.
We’re watching a new generation of 10X finance professionals emerge. They’re still working in the tools they know and love, but with an entirely new set of capabilities. Instead of late-night reformatting sessions or emailing version 38 of the same file, teams are working from live models. They’re building the story as it unfolds. Skipping the grunt work and getting straight to the takeaway.
And while AI might take the wheel for some tasks, it doesn’t replace what makes a great finance team great. The craft still matters: sharp judgement, business fluency, and the ability to tell a story the business will rally behind.
So yes, the spreadsheet is still open.
But now, it’s part of something bigger.
Long live the spreadsheet. 👑
