The Four JTBD in Accounting

When people talk about AI in accounting, the conversation often drifts into broad promises and vague headlines. But accounting isn’t vague. It’s structured, outcome-driven work, built on repeatable processes that firms execute every single day.

That’s why it’s more useful to frame this conversation around jobs to be done—the foundational tasks that underpin how firms operate and deliver value.

Across disciplines and firm sizes, four show up again and again:

Whether you’re closing the books, filing taxes, preparing for audit, or offering outsourced finance, some version of these four jobs shows up in every engagement. They cut across service lines, tech stacks, and org charts. They are the backbone of accounting work.

And they all have the potential to be meaningfully impacted by AI.

So instead of speculating about where AI might theoretically help, let’s break down each job and look at:

1. Data Collection & Ingestion

This is the unglamorous but essential backbone of accounting work, the behind-the-scenes grind. Pulling in raw data from disparate sources like bank feeds, GLs, payroll systems, AR/AP platforms, ERPs, point-of-sale systems, even emailed spreadsheets, and structuring it so the rest of the process can begin.

Matching files. Chasing formats. Cleaning inconsistencies.

Why It Matters

Every workflow depends on accurate, timely data. If the inputs are wrong, the outputs collapse. This job is about creating the foundation, one clean, connected source of financial truth.

For most firms, and rightfully so, this is where the time goes.

Take, for example, a controller at a mid-sized firm who used to burn 3+ hours each week downloading CSVs from five different bank portals. That time now vanishes with a tool that fetches, formats, and reconciles everything automatically, before lunch on Monday.

Why AI Is A Good Teammate Here

Because data collection and input tends to be repetitive, pattern-based, and largely rules-driven. It’s also work few enjoy.

AI (especially when paired with traditional automation) excels at parsing formats, mapping fields, and normalizing inputs across messy systems. Even better? It doesn’t burn out from reconciling PDFs at 2am.

What’s The Impact

Internally, it frees up junior capacity, reduces manual errors, and speeds up the monthly close. More importantly, it sets your advisory team up to work with real-time data, not last month’s spreadsheets.

Externally, it shortens client wait times—something Blake Oliver rightly points out matters more than just speed for speed’s sake. Faster answers. Happier clients. That’s the real win.

Can This Be Done?

This is already within reach. AI can match vendor names, identify duplicates, propose journal entries, and extract transaction-level data from unstructured documents.

In not a distant future we’ll see smarter ingestion that learns client-specific patterns, flags anomalies automatically, and builds a usable trail for audit or tax. In five years? Autonomous ingestion agents that maintain real-time ledgers with minimal oversight.

2. Research & Retrieval

Accountants aren’t just number crunchers, they’re investigators. And this JTBD is the detective work behind accounting. Whether it’s understanding a niche tax treatment, referencing audit standards, or looking up how a similar transaction was handled, research supports compliance and judgment.

Why It Matters

Research is how accountants apply context. It’s also how they avoid costly mistakes. No one wants to make a treatment decision in a vacuum or redo last year’s work from scratch. Supporting the work by relevant standards, codes or laws is crucial to the work being done.

AI Shines as a Co-Pilot

AI can surface relevant guidance fast, flag treatment anomalies, and cut down the time spent digging through docs or racking your brain for a prior case.

Because research is mostly about finding the right thing fast, large language models (LLMs) are excellent at pulling the right rule, summarizing guidance, or retrieving prior context, especially when trained on a firm’s internal history.

What’s the Impact

Internally it can lead to faster onboarding for juniors, smarter reviews and more consistent decisions across teams. Externally, clients get confident answers faster. Less “I’ll get back to you” and more proactive insight.

Is It Feasible Today?

Retrieval-augmented generation (RAG) works well now for static guidance and precedent search. Custom-trained copilots are already in play in leading firms. Very soon we’ll see research copilots embedded across firm systems. Ask a question, get a link, a citation, a treatment suggestion, and historical precedent—all traceable. AI will assist in edge-case evaluation and flagging inconsistent logic in decisions.

3. Report Generation & Filing

The formal output. Whether it’s an audit report, tax return, board-ready financials, or a month-end close package, this job is about structuring, summarizing, and presenting financial information. It’s high-stakes, deadline-driven, and detail-heavy.

Why it matters

This is what clients, regulators, and stakeholders see. It’s the “finished product” of your work. Accuracy, timeliness, and consistency are everything.

Why it’s primed for AI

While this isn’t always where AI starts, structured data makes it dramatically more efficient. If you can trust the inputs, automation can help build the outputs in a fast, traceable, and ready for review manner.

Because once data is structured, generating reports becomes a formatting problem. AI can draft, populate, and even narrate reporting—while following firm or industry templates.

Impact if supported by AI

Feasibility today. Medium. Basic population of templates, variance analysis, and simple commentary is very doable. Output formatting is improving. Excel manipulation, however, still trips up AI.

Where it’s going. In 2–5 years, AI will manage full report drafts—highlighting what changed, identifying outliers, and offering commentary based on trends. It’ll be a teammate in the prep process, not just a tool.

4. Client Service & Strategic Advice

The most human part of the job and the most irreplaceable. Whether it’s answering client questions, flagging risks, or advising on margin improvement, this is where firms move from vendor to partner. This is about making sense of the data, providing interpretation, and offering forward-looking guidance.

Why It Matters

This is where firms prove value. It’s what keeps clients coming back. It’s also what turns accounting from reactive to strategic.

AI’s Role Here?

Keep accountants informed, proactive, and responsive.

Because AI can do more than deliver data, it can spot patterns, surface insights, and even suggest next steps. But judgment, empathy, and trust? Still human territory.

The biggest impact is obviously client facing. Clients experience more proactive communication. They feel guided, not just informed.

Doable?

AI can already assist with insight surfacing, benchmarking, and basic what-if analysis. But nuanced recommendations still require human input.

In a couple of years, AI will generate tailored talking points, prepare Q&A context for client meetings, and surface timely nudges based on real-time data. In the end, how much of this JTBD accountants will want to delegate to AI is still be be seen.

TL;DR: Start With the Job That’s Slowing You Down

Every firm has a bottleneck. A job that’s eating capacity, delaying delivery, or draining energy. Instead of trying to “AI your firm,” pick the job that’s costing you the most and fix that one.

Start by asking: which of these four jobs is eroding your team’s time today?