The Quiet Expertise Gap AI Is Creating in Accountancy — And How to Close It

There’s a paradox playing out in accounting. Automation is freeing up capacity across firms with 80% seeing increasing client demand for financial planning and business strategy. But here’s the problem: as AI handles more of the detailed compliance work, accountants are losing the technical immersion that once built their expertise. They’re no longer spending hours deep in a client’s finances, spotting the anomalies that only come from intimate familiarity with the numbers. Experienced accountants who trained “pre-AI” will retain that ability – they’ve done enough hands-on work not to forget it. But new joiners will have an easier path and are therefore at risk of developing shallower expertise.

Put simply, AI is accelerating demand for higher-value advisory work at the exact moment it risks hollowing out the technical foundations needed to deliver it. And the market reflects that shift. The global accounting advisory market is projected to grow from $101.62 billion in 2024 to $165.15 billion by 2034. The future growth opportunity is clear: it’s in advisory, not compliance. . But with the former dependent on the latter, how can firms close this gap? The answer lies in how AI is redefining expertise itself.

The expertise erosion issue

When an accountant spends 20 hours preparing a corporation tax return manually, they develop an intuitive understanding of that client’s business. They notice when the R&D spend jumps unexpectedly. They flag when the payroll doesn’t align with the growth trajectory. They build pattern recognition that becomes consultative insight.

Automation streamlines much of that. 95% of accountants say technology has helped reduce time spent on compliance tasks. But the uncomfortable truth is this: their people no longer need to know the details about clients that they previously did. They don’t have the ability to go as deep on certain fields. And the challenge is: how do you build advisory skills when people haven’t spent years learning the business through compliance work?

The reality is that technical depth and advisory capability are different skill sets. One doesn’t automatically translate to the other. Growing accountants to become good advisors requires developing enhanced skills like strategic thinking, consultative approaches and business empathy. These aren’t skills you pick up through osmosis. They need deliberate cultivation. And how firms respond to this gap is already shaping very different futures across the profession.

Two futures emerging

The accounting profession in 2026 won’t be a uniform landscape. We’re watching a widening divide take shape between firms that are adapting strategically and those that haven’t yet started on their AI journey.

Progressive firms already AI-ready are focusing on transitioning their workforce into more advisory roles. They’re democratising advisory work by leveraging software that scaffolds client conversations, packaging up knowledge that junior partners historically wouldn’t have been able to access. Junior staff can step into advisory roles sooner, armed with insights that used to take years to accumulate.

Meanwhile, many smaller firms are still trying to get onto the AI wave and become more data literate, working to ensure their workforce can be trusted advisors at all. And then there are the firms with partners looking to retire soon who aren’t discussing AI at all. It’s these firms where the expertise gap hits hardest: new joiners aren’t developing the same depth as prior generations and they’re also far harder to hire. Which is why 94% of accountancy leaders worldwide say talent and recruitment challenges will limit their ability to grow. Firms that don’t evolve  aren’t just missing out on efficiency gains – they’re becoming increasingly unable to compete for the talent they need to survive.

The workflow vs chatbot problem

Even among firms that are actively investing in AI, one thing is holding many back: how they’re thinking about AI adoption. Many are experimenting with public LLMs like ChatGPT, treating AI as a research assistant rather than as infrastructure embedded in their compliance workflows.

But advisory strength is built on compliance strength. Firms can only free up the capacity for deeper client conversations if they dramatically reduce their time-to-compliance. And you don’t achieve that with bolt-on chatbots. You achieve it by embedding automation and AI directly where the compliance work actually happens.

LLMs are powerful but they have limitations. They’re excellent at working with natural language – summarising research, explaining concepts, answering questions – but they can’t perform the  complex calculations or data-secure quantitative analysis that accounting demands.

That’s why firms seeing real ROI aren’t just prompting ChatGPT. They’re adopting AI-native features that sit within their bookkeeping and compliance stack – tools  that automate reconciliations, flag compliance issues and surface insights from financial data as part of the workflow. When compliance is automated at the source, the insights produced naturally flow into advisory, giving accountants richer conversation starters and more value-added context for clients.

But even the right tools won’t deliver results without the right capabilities. 71% of accountants and bookkeepers are ready to upgrade their AI skills, but less than a quarter receive AI-related training from their firms. That gap between enthusiasm and enablement is becoming a critical bottleneck – because strong advisory isn’t just powered by automated compliance, it’s powered by people who know how to turn those insights into conversations.

What actually needs to happen

The firms that will dominate in 2026 and beyond aren’t necessarily the ones with the most sophisticated AI. They’ll be the ones that have connected the dots between their technology, their skills strategy and their business model.

That means a few things:

First, it means making a decisive choice about your firm’s direction. Are you building an advisory practice or staying focused on compliance? Both are valid, but the training investments, hiring profiles and technology choices look completely different for each path. The firms struggling most are the ones trying to straddle both without clarity.

Second, it means recognising that AI adoption isn’t only a technology project. It’s a workforce transformation project. You can’t just buy software and expect results. You need governance frameworks, training programmes and cultural change management.

Third, be intentional about how you develop advisory capabilities in your team. That might look like pairing junior staff with senior advisors on client calls, creating structured training or leveraging software that surfaces client insights for advisory conversations. The firms getting this right aren’t leaving advisory development to chance.

The accountability that matters

One thing’s for sure – 2026 will make it clear which firms have treated AI as a genuine strategic priority and which have just been experimenting around the edges. The gap between leaders and laggards is widening fast.

But – and here’s the encouraging part – the profession has always adapted to technological change. Excel didn’t make accountants redundant. Cloud accounting didn’t eliminate firms. And AI won’t either. What it will do is reward the firms that approach it as an opportunity to fundamentally rethink how they build expertise, serve clients and grow their people.