The accountants of the future won't look like the accountants of the past

Every few decades, accounting goes through a quiet reinvention. Not a dramatic rupture, and rarely a moment anyone can point to in hindsight, but a steady shift in what clients expect and, as a result, what firms are actually valued for.

New technology has always played a role in these transitions. Desktop software moved the profession away from paper and towards systems of record, where compliance was the primary expectation. Cloud accounting made data always-on and shareable, and collaboration became part of the service. Automation reduced manual processing, which in turn reset expectations around speed and fees.

AI is simply the latest step in that same progression, but what’s different this time is the pace. Automation and AI didn’t start the shift, but rather they accelerated it. Attempts to slow that momentum in order to preserve traditional roles won’t protect the profession. They will only make it less relevant to the clients it serves.

This is where the conversation often becomes uncomfortable, particularly for established firms that have built strong businesses on existing delivery models. But history suggests that the real risk has never been change itself; it has been failing to adapt how value is delivered when client expectations move on.

Technology changes capabilities, but clients change the rules

One of the easiest mistakes to make is to treat AI as a standalone disruption rather than part of a longer pattern. In every previous era, new technology expanded what accountants could do, and clients responded by expecting more. Now, with AI capable of synthesising information in real time, clients increasingly expect relevance, context, and proactive advice not just accurate numbers.

Firms that succeeded in past transitions did so by rethinking how they delivered value, not by clinging to the workflows they already knew. Those that didn’t rarely failed overnight, but simply became less central, less differentiated, and eventually easier to replace.

As Lee Maughan, CEO of Green & Purple, put it:

“Automation is coming either way… you’re either part of the leaders who engage with it, or you wait and let the rest of the industry get ahead of you.”

Framed this way, AI isn’t really a technology question at all. It’s a delivery model question.

The best advisors aren't defined by technical ability alone

There’s another assumption that deserves challenging: that the value of an accountant is primarily determined by technical competence. Technical skill matters, of course, but it has never been the full story.

“Some of the very best advisors are not necessarily the most numerate advisors,” Lee said.
“They’re the ones who are emotionally really intelligent.”

Clients don’t lack access to data. Rather they struggle to understand what the numbers mean for their decisions, their risk exposure, or the future of their business. The most valuable advisors have always been the ones who can align financial insight with context, purpose and human reality.

This is why the role of the accountant has been shifting upstream for years, away from producing outputs and towards interpreting them. AI doesn’t eliminate that responsibility; it makes it more visible.

Training, technology and the quiet battle for talent

One of the most common objections to automation is the fear that junior accountants will lose essential learning opportunities. In a profession where judgement has traditionally been built through repetition, that concern is understandable.

But repetition alone has never guaranteed understanding or engagement.

What’s often missed in this debate is that training models and talent expectations are changing at the same time. Future advisors will spend less of their careers on manual processing and adjustments, not because fundamentals no longer matter, but because technology handles those tasks more efficiently. Professional bodies are already adapting to this reality, placing greater emphasis on interpretation, communication, and decision-making alongside technical foundations.

For firms, this isn’t just a training question. It’s a talent strategy question.

As Lee Maughan put it:

“I want the team to do work that they find interesting. That isn’t doing things manually. It’s using technology to get things done quicker so they can spend time doing something more valuable.”

Talented people don’t join firms because they want to become exceptional at low-leverage work. They stay where they are trusted to apply judgement, solve problems and develop commercially. Firms that use automation to deliberately redesign roles (rather than simply to increase throughput) create environments where strong advisors actually want to build their careers.

Over time, that becomes a meaningful competitive advantage. Not just in efficiency, but in retention, capability, and the quality of advice clients experience.

From protecting standards to designing relevance

For many firms, hesitation around AI is framed as a commitment to quality and to “doing things properly.” But quality has never been static. In every era, standards were redefined by what clients needed most, not by how work had always been done.

The next generation doesn’t need to spend most of their careers proving they can do work machines now handle better. They need earlier, more deliberate exposure to judgement, commercial thinking and client decision-making.

The firms that treat this as a design challenge will raise stronger advisors, and the firms that treat it as a threat will simply produce professionals optimised for a shrinking slice of the value chain.

The accountants of the future won’t look like the accountants of the past. Not because the profession is being replaced, but because relevance has always had to be rebuilt, and this moment is no different.