AI Is Finally Ready for Accounting. Are We?
If you're feeling behind, you are. Just like the rest of us.
Hey there đ,
Iâve been to a lot of AI events lately. More than usual. Something has shifted since December â and itâs moving at an exponential pace.
Both in the tools. And in the rooms.
It shows up when someone demos what theyâve actually built. When the reality of whatâs possible lands in a room full of people who didnât know it was possible yet. Itâs not excitement exactly. Itâs quieter than that. A little unsettling. The kind of quiet where everyone is doing the same mental calculation and nobody wants to say it out loud.
Iâve been sitting with that feeling for a few months. Yesterday, I finally got to do something about it.
We ran the largest AI share session weâve ever done at Gaapsavvy. 670 invites. 160 practitioners showed up â controllers, revenue leads, CAOs from 100+ enterprise tech companies, 90% audited by Big 4 firms. No panels. No vendor demos. Just practitioners telling each other whatâs actually happening.
I started the way I always do. With a practice poll.
Your CFO just sent a company-wide email. âWeâre going all-in on AI for finance by Q2.â
A. Nod confidently, add âAI strategyâ to your LinkedIn, and figure out what that actually means later.
B. Raise your hand and ask has anyone actually done this yet? â and watch the whole room go quiet.
80 responses. 90% Big 4 audited. 52% A. 48% B.
Iâll tell you something about that poll: I iterated on the question with Claude for quite some time, trying to get at the heart of it. When the results came in, my co-facilitator Jim said: âThis is way more split than I expected.â
My answer: âThatâs because weâre pragmatists.â
Both answers are honest. And I feel both, completely.
Hereâs what I want to say before we get into the data.
For the first time in my career, the thing standing between accounting teams and whatâs possible isnât the tools, the budget, or even the access. Itâs just the learning. Thatâs both the most encouraging thing I can tell you, and the most demanding.
The models and tools are finally ready. The only thing left is us.
Hereâs the thing the accounting world doesnât hear enough: they didnât fully work for us before. The tools youâve been hearing about for two years just became capable enough to actually use. Even if you felt behind. You were waiting for something that wasnât ready yet. It just became ready. The timeline starts now.
To put some context around the pace: in the last six weeks alone, over 250 model releases across the major labs. Claudeâs context window hit one million tokens â your entire contract portfolio, every policy memo, every prior audit conclusion, all loaded at once. Claude Cowork launched, meaning AI can now use your actual computer while youâre in a meeting. Claude Code revenue doubled since January 1st. Engineers have stopped coding without it.
This is not a slow trend you missed. This is a wave that broke last month.
The thing about exponential: it doesnât feel exponential while itâs happening. It feels like you blinked. The question isnât whether youâve caught up â itâs whether youâre learning fast enough to keep up with something that keeps doubling.
Thatâs what learning in community is really about. Not just sharing use cases. Learning together, fast, in a moment when learning alone is almost impossible.
Letâs dive in.
This article is brought to you by Everest Systems
Most ERPs werenât designed for AI. They were built for stability â which means when you try to layer automation on top, youâre testing blind, deploying into production, and hoping nothing breaks.
Everest does it differently. AiSpecify lets finance and ops teams build custom apps using natural language â no code, no IT ticket. Live Sandbox lets you test and validate those changes against real data across your systems, before anything goes live.
The frontier models are ready. Now your ERP needs to be too.
What does enterprise finance actually have access to?
Engineering teams have been using frontier models for close to a year. Finance teams at the same companies are just now getting approval.
That gap â same company, different floor â is what the data shows.
Q: What tools does your company actually let you use? ( i.e. IT approved)
Google Gemini leads at 53% â mostly because it ships with Google Workspace and doesnât require a separate approval conversation. Claude and ChatGPT Enterprise are tied at 38% each. NotebookLM at 34%. Copilot at 23%.
But the tie between Claude and ChatGPT tells only part of the story.
A migration from ChatGPT to Claude
Of companies with Claude approved, 46% have dropped ChatGPT entirely. They didn't add Claude â they replaced ChatGPT with it.
One controller said it directly:
âWe had ChatGPT, then moved on to Claude. We donât have GPT anymore â now itâs just Claude and Gemini.â
Enterprise security teams are making deliberate choices. The data shows which way they're moving.
Worth noting: Anthropic had a rough week â they accidentally leaked Claude Code source code via a packaging error. No customer data involved. Claude Code is the developer CLI engineers use to write code â a different product from Claude Enterprise, which is what your security team is approving. I'm mentioning it because you probably saw the headlines, and that's what we do here.
Getting Claude through InfoSec â some helpful accelerators
For standard Claude: the enterprise agreement is the unlock. Multiple security teams confirmed they got comfortable once a true enterprise agreement was in place. Same with Gemini â one team said IT had concerns about the Pro tier but the enterprise version resolved them immediately.
Claude Cowork is different. Itâs currently in beta, and enterprise agreements donât automatically cover beta products. One team that got it approved described making specific concessions around folder access and going through additional security review. They got there â but it was a longer, more detailed conversation than approving standard Claude.
If youâre trying to get Cowork through InfoSec, go in knowing this. Itâs not a blocker. Itâs just a different conversation.
And you have standing to have it. 38% of this community â 90% Big 4 audited, 42% already public â has Claude enterprise-approved. Print the chart. Thatâs your peer group. đ
Whatâs actually happening on the ground
Across five share sessions this quarter, 51 documented use cases from 30 companies. The maturity picture: 49% in production. 29% in progress. 12% prototype. The "we're exploring" era is over for most of this community.
What have you done vs. what do you want to crack in the 6 months?
Two-thirds of the room has used AI for contract review or technical memo drafting. There's a reason those two lead: Klarity and Numeric spent years teaching the market that these were the places to start. So when practitioners answer this poll, they're reporting what the industry told them was possible â and what they've now proven works. One-third have built something beyond that. 51% want to build something in the next six months.
One practitioner put the moment perfectly: âBack in the day, everyone had their own Excel workbook. Now we all have our own AI workflows on our desktops.â The proliferation has already happened. The next question â how to centralize, govern, and share â is the same one we asked about spreadsheets. Just ten times faster.
I showed the community what Iâve been building to help organize community sharesâ an excel use case tracker and an AI index website, both created maintained entirely by Claude Cowork. I donât populate any of the fields. I drop a transcript into the folder, it populates any new use cases, or tools. Next meeting, another transcript update. The reaction in the chat wasnât âwow, AI is amazing.â It was quieter. More like: oh. that would make my meetings actually useful.
That shift â from impressed to capable â is the one Iâm trying to create every time I show something instead of just describing it.
The conversation kept coming back to the same tension: Finance and engineering are at the same companies, using different languages, sitting on each other's data.
The data layer is the real bottleneck. The most sophisticated teams arenât stuck on which AI to use. Theyâre stuck on getting clean data out of engineering. Usage data sits with the AI team. Capitalization data sits with the dev team. Finance is still waiting on monthly extracts. One controller framed it perfectly: âHow do we create better data accessibility throughout the organization that we can then put an AI layer on top of?â The AI is ready. The pipes arenât.
The best reframe I heard all session. Someone pushed back: arenât these just accounting projects with âAIâ in the name? It was exactly the right question. And by the end of the discussion, heâd answered it himself: AIâs highest-leverage use in accounting right now is getting you out of the business of normalizing unstructured data. Five hundred emails. Contracts written in paragraphs. Sales orders that arrive as sentences your shared services team has never seen. The AI handles the transformation so practitioners can do the judgment. Thatâs not a small thing. Thatâs the thing that was eating the hours.
Where are you feeling pressure right now?
60% are feeling pressure from leadership â with no clear path forward. 16% are leading the initiative themselves. 13% have no pressure at all. Only 3% said theyâre stuck waiting for InfoSec.
That surprised me too. The bottleneck people experience as an access problem is usually something else. Itâs not knowing what use case to propose. Itâs not having data in the right shape. Itâs not knowing where to start.
Then someone asked the really hard question: how do we frame KPIs that report up without it sounding like headcount reduction?
The room got a little quiet. Then the expected answers came â speed and accuracy, measured simply. One person with the tool, one without. Time to completion. Error rate. Hours to first draft. Real, measurable, safe to show a CFO.
But hereâs the reframe I keep thinking about: at NVIDIA, engineers are literally measured on how many tokens they use. Thatâs their productivity metric. Accounting doesn't have that language yet â but we're about to need it.
If youâre in the 60%, youâre the norm. The pressure isnât a sign youâre behind. Itâs a sign youâre paying attention.
The one thing AI still canât do
I was at an event a few weeks ago where a panel was asked: what is the one thing AI canât do right now?
I didnât listen to the answers. I already knew mine.
Take responsibility.
AI can generate infinite content. It can normalize unstructured data, draft your memos, build your flux analysis, scour 12 years of Box files to find a variance from 2014. It is getting very, very good at all of it, faster than any of us expected.
But when it gets it wrong â and it will get it wrong â it cannot own that. It cannot stand in front of your auditors and say: this is my judgment, here is my reasoning, and Iâm accountable for this conclusion.
Thatâs still yours. Thatâs always going to be yours.
Iâve been thinking a lot lately about what it means to run community in a moment when it is so noisy I can barely hear myself think, when attention is the scarcest resource we have, and when every vendor and consultant and LinkedIn connection is competing for a piece of it.
The thing I keep coming back to: The thing AI canât do, is show up. It canât be in the room when the air changes. It canât notice the silence. It canât decide, together, to stop performing certainty and start actually sharing.
We are only limited by our capacity to learn. Thatâs terrifying if youâre trying to do it alone. Not so much if you're not.
Weâre in this together. Whether we know it or not. But I think itâs how weâre going to figure it out.
Angela
Whatâs Coming up:
Weâre running two events in April for exactly this reason â one hands-on session at Deloitte SF where you get to actually play, and one where you get to see what it looks like when a team that builds these tools uses them on their own finance problems.
Both are worth your time.
April 15 â AI in Finance Lab half day, in person, hands on session @ Deloitte SF, co-hosted with Coterie CFO. I will be teaching AI Fundamentals, and you have space to play with all the frontier models - FULL
April 17 â âBuilt Between Meetings: How Anthropicâs Finance Team Actually Uses Claudeâ virtual with Adam Dix, head of FinOps. Must be a Gaapsavvy community member . No recording. Adam shares his learning journey and demos his builds. Worth it. Join hereâ
Want to see Claude Cowork, Excel plugins, and agentic workflows in action? Devon and I spent an afternoon playing with it and discovering new features â watch here.
From real practitioners, for learning purposes only. Polling data shows industry leans, not final positions. Always work with your auditors before implementing anything new.