It’s 11 PM, and you’re shaken out of your stupor by another Slack ping.
“Can someone compare the Salesforce pipeline against our latest forecast?”
The drill is all too familiar: export the CSV, copy, paste, and cross your fingers the formulas don’t break. By the time you’re done, the numbers are already stale—and your CFO expects a “fresh” report by 8 AM.
This isn’t a nightmare. For teams shackled by manual processes, it’s Tuesday.
We’ve covered a lot of ground in our FP&A Pillar series thus far: the importance of good (not perfect) data (Pillar 1), why finance teams need to know their business inside and out (Pillar 2), and how to build models that balance simplicity with sophistication (Pillar 3).
Now it’s time to scale those efforts.
Pillar 4 is about leverage: putting automation and AI to work so your team has the bandwidth to add the strategic value that defines modern FP&A.
Here’s how top teams use AI and automation as a force multiplier—and how you can, too.
The role of AI and automation in modern FP&A workflows
FP&A isn’t what it used to be. Leadership wants more from their finance function—less data wrangling, more strategic insights.
But while expectations have risen, the day-to-day workload hasn’t exactly gotten lighter. If anything, it’s ratcheted up—reporting cadences are accelerating, and more software tools mean more data sprawl to contend with.
Pleading for more headcount usually isn’t an option. Even if it was, it means more training, greater risk of errors, and more silos. Instead, leading teams are leveraging automation and AI to take busywork off their plates so they can focus on the higher-level insights leadership is looking for.
This starts with a simple mindset shift: if a task is repetitive, it’s an automation candidate. That means constantly asking yourself:
- What's slowing us down? (spoiler: manual data entry)
- Where are the friction points? (hint: siloed systems)
- Could a machine do this faster or better? (probably)
Automation and AI are the connective tissue that stitches your entire finance stack together. When your systems speak the same language, data flows where it needs to go, when it needs to get there, giving you the breathing room you really need to steer the business.
Before we dig in, it’s important to understand how these terms are really two separate workstreams that are now starting to blend together into one.
In our recent webinar on Harnessing automation and AI to transform finance, Brandon Sullivan, CFO at 2X Marketing, describes automation and AI in finance as two separate circles of a Venn diagram. They can both exist and provide value independently, but where they overlap is where finance superpowers will come into play in the coming years.
Where automation makes the biggest impact in FP&A
Manual entry and consolidation
It’s hard to move fast when you’re stuck in manual mode. Days are spent shepherding data across systems rather than figuring out the story it’s trying to tell. Your ERP and CRM aren’t necessarily to blame—they were built to record transactions, not connect the FP&A data dots.
Automation is how you get out of this trap. The best tools don’t require you to rip out your tech stack and start from scratch. They sit between the systems you already use—ERP, CRM, HRIS, billing tools, you name it—automatically pulling in the actuals, transactions, and KPIs your models run on. You’re left with a single, clean base layer of data—no copy-and-paste required.
Just ask Ryan Freudenburg, Director of FP&A at AllCloud, who, before implementing Aleph would spend a substantial amount of his week exporting, cleaning, and consolidating cross-system data in spreadsheets. “It was a total nightmare,” said Ryan, “I know because I did it for a while.”
Learn more about how automation revolutionized how AllCloud does FP&A, reducing data consolidation tasks from days to minutes.
What’s more, you can build in automated checks to catch issues, like a missing vendor name, miscategorized expense, or unmapped accounts, before they ripple through your model.
Mapping your data
Nothing derails a budget review faster than labeling confusion. One minute you’re walking through department spend; the next, someone is asking why you’re paying both “AWS” and “Amazon Web Services.” Cue the awkward silence as your team is sidetracked by an explanation that, actually, these are the same vendor.
Mappings help you group and label your data in a way that makes sense in context, whether that’s a simplified investor P&L or a granular, audit-ready view. Or as Ryan mentioned in the section above, it can ensure different source systems are always talking the same language.
But building and maintaining mappings by hand is a thankless, never-ending chore. Reconciling them takes time—time you don’t have enough of when you're faced with thousands of transactions per month or different systems having different naming conventions.
Aleph automates the heavy lifting with Mappings, and now, with the help of AI, intelligent suggestions. Simply set some basic logic, and the system does the sorting—all you need to do is review and approve. Mix-ups and mistakes become a thing of the past.
Slow or infrequent forecast updates
Even if your source data is pristine, your forecast is only as good as your ability to keep it current. For a lot of teams, this is the real challenge. Refreshing a report or forecast kicks off a chain reaction of exports and formula tweaks, while hoping nothing breaks in the process.
We’ve heard customers joke that before they automated, they’d kick off a forecast run, head to lunch, and hope the spreadsheet didn’t crash before it finished calculating. Because it’s such a pain, re-forecasting happens less often than it should.
But the value of automation is the ability to spot the mole hills before they become mountains, and adjust course quickly, for both your backward and forward-looking views. Brandon at 2X’s philosophy is that “if you're on a voyage across the ocean and you can touch the wheel fifty-two times or twelve times, touching it fifty-two times is probably gonna give you a greater likelihood of success of landing where you wanna land.”
Automation injects dynamism into the forecasting process. With actuals flowing in automatically and updates cascading through your model, you can re-forecast as often as needed. And because there are fewer manual touchpoints, there’s less room for error.
This shift to frequent reporting and continuous forecasting is also reshaping how teams package and present data. Instead of static decks that are obsolete on arrival, best-in-class teams are opting for live dashboards and flexible reporting tools that connect directly to source data. With Aleph, you can link Excel, Google Sheets, and even board slides to a live cloud database. Just refresh, and your numbers update on the spot.
Version control
We’ve all been there—someone sends out “Final Budget v7_FINAL.xlsx” only for the next reply to say, “wait—I was using v6.” The scramble to compare versions, consolidate edits, and figure out which tab has the real numbers ensues.
It’s a mess. Along with being frustrating for all involved, poor version control erodes trust among your team and your stakeholders.
Passing files around is a relic of yesteryear. A single, live model is better in every way—everyone can see the same numbers at the same time. No more hoping the file you’re working on is the latest. No more merging edits across six email threads. Just one source of truth that updates in real time.
Modern tools like Aleph take this a step further with built-in permissions that keep your logic and assumptions consistent. Collaborators can view, update, and share from the same source without stepping on each other’s toes. This is especially useful when it comes to custom logic, such as a gross margin calculation or a business-specific metric underpinning your forecast.
Workflow and process automation
Many FP&A bottlenecks have nothing to do with spreadsheets. Some of the most insidious ones are lurking in your recurring workflows: monthly close, budget submissions, forecast revisions, variance analysis, and the like. The stuff that fills up your team’s calendar without adding much strategic value.
Top teams don’t just automate data flows. They automate the work around the work.
That could look like a version-controlled Google Sheet that auto-updates from a cloud database so department budgets are always current. Or a simple alert that pings the CFO when a team goes 10% over budget. These aren’t revolutionary ideas. They’re just the kind of operational improvements that compound over time.
Variance analysis is a perfect example—something your team does every month, and where even small time savings could add up over time. Or worse, not doing them frequently or only having the time to spot big variances, leads to correctable mistakes that cost companies a ton of money.
These are all very solvable solutions with the help of automation and AI. For example, Aleph’s AI Scan feature takes the legwork out of explaining variances. Instead of wading through spreadsheets, you can:
- Scan for material deviations from forecast or prior-month values
- Drill into transaction-level detail to find root causes—like a vendor that’s billing inconsistently or a campaign that went over budget
- Surface the story behind the numbers by knowing exactly where to look and what happened
The more you can offload operational minutiae, the more capacity you have to turn data into direction.
A practical framework for painlessly implementing FP&A automation
Change can be scary. No one wants to break a process that basically works (even if it’s inefficient). But nobody said you need to automate your entire function or go all in with AI on day one, either. Rather than automating everything overnight, top teams focus on a slow and steady rollout that builds over time.
Here’s the blueprint:
Step 1: Map out the mundane
Start by auditing your team’s calendar. How many hours are eaten up by data pulls, report assembly, or variance calculations? Which processes happen on a monthly, weekly, or even daily basis?
Mapping these out gives you a clear view of where you should initially deploy automation. Often, teams end up discovering that 20% of their tasks are taking up 80% of their time.
Step 2: Prioritize quick wins
With all of your routine tasks on the table, it’s time to go after the low-hanging fruit. Prioritize those that are frequent and rule-based—like refreshing actuals from your ERP or auto-generating variance reports.
For example, linking your accounting system to your planning model might take a little legwork to set up, but it saves dozens of hours every month. Something like automating an entire board deck? Save that for later. It might be a huge time-saver for your team, but will require a much greater lift upfront. These early wins build momentum for bigger initiatives down the line.
Step 3: Crawl, walk, run
Once those initial automations are live, closely monitor how they’re performing. Are they working as intended? Is your team running into any issues? Before moving onto bigger projects, work out the kinks here first. This will reinforce the confidence your team has in automation or shine a light on where you should buy vs. build.
Step 4: Choose the right tools for the job
FP&A tools are plentiful, but so are solutions that take months to implement and dedicated headcount or third-party consultants to maintain them. Buying an automation tool should eliminate FP&A bottlenecks, not create new ones—be careful!
When selecting your next tool, keep these guiding principles in mind:
- Start with the problem, not the tool: Use your notes from steps 1-3 above to help you clearly define what issue you’re trying to solve to make your evaluation process more efficient.
- Prioritize compatibility and integration: Tools should seamlessly integrate with your existing technology stack and reporting packages. Smooth integration reduces complexity and ensures a unified workflow.
- Opt for flexibility and scalability: Your FP&A processes and team will evolve over time. Choose platforms that offer flexibility to adapt and scale as your business grows.
- Value ease of use: Tools that require extensive training or overly complex setups can diminish efficiency gains. Fast implementation and user-friendly interfaces encourage team adoption, while delivering a quicker return on your investment.
If you’re looking to learn more about automation and AI in finance—the past, present, and future—then check our recent webinar on Harnessing automation and AI to transform finance with Brandon Sullivan, CFO at 2X Marketing, and Johnnie Walker, Co-founder at Rooled.
We tried to leave Aleph out of the talk tracks as much as possible, but when someone asked Brandon and Johnnie to speak about their experience implementing Aleph for automation, we were not going to stop them. Here’s the clip 👇
If you’d like to learn more about Aleph, we’d love to show you around.
Up next is our fifth and final installment of this FP&A pillars series, where we’ll bring it all together to talk about how to turn numbers into compelling narratives. Stay tuned!
