From numbers to navigation: how AI is reframing the accountant’s role

Paul Redmond writes. Paul is the founder of RDA Accountants. A recognised voice in modern accountancy, Paul helps business owners and accountants achieve clarity, growth, and long-term impact through his frameworks on wealth, strategy, and advisory transformation.

Introduction: a defining decade

Every profession has defining decades – periods when technology and expectations force a complete reinvention. For accountants, this is one of those decades.

We’ve already lived through three major shifts: from ledgers to spreadsheets, from desktop software to the cloud, and from static reporting to real-time collaboration. Each step freed us from manual drudgery and increased our efficiency.

Artificial Intelligence (AI), however, is different. Unlike past shifts that digitised existing work, AI reshapes the work itself. It changes what accountants do, how we deliver value, and even how clients perceive us.

Used poorly, AI risks reducing us to faster processors of compliance tasks - a commodity in a race to the bottom on fees. Used strategically, it gives us the power to become navigators of business success, guiding clients with insight, foresight, and clarity.

The choice is ours.

Why AI is arriving now

AI’s rapid arrival in accountancy isn’t random. Four converging forces make this the perfect moment:

1. Data overload: businesses now produce enormous volumes of data from e-commerce, CRM systems, banking feeds, and apps. Most of it goes unused because humans can’t process it all. AI thrives in this environment, ingesting and analysing vast datasets in seconds.
2. Rising client expectations: Netflix predicts films, Google anticipates searches - our clients live in an AI-powered world. They now expect real-time insights, proactive guidance, and personalised advice from their accountants, not just year-end reporting.
3. Margin pressure: Compliance work is being commoditised by cloud software and low-cost providers. To escape shrinking margins, firms must shift towards higher-value, insight-led services.
4. Talent shortages: Fewer graduates are choosing traditional accounting. The repetitive nature of compliance makes retention difficult. AI offers relief by automating low-value work, freeing teams for more engaging, strategic roles.

Together, these forces make AI not optional, but essential.

Practical AI in today’s firm

AI isn’t a distant future – it’s already embedded in tools we use daily. Here are six practical applications that are reshaping firms:

• Automated data capture: OCR and machine learning categorise invoices, receipts, and bank transactions with minimal human input (e.g. Dext, Auto Entry).
• Predictive forecasting: Dynamic models replace static spreadsheets, enabling scenario planning in real time (e.g. Futrli, Fathom).
• Plain-language reporting: NLP tools translate financial data into clear narrative commentary clients can actually understand (e.g. Microsoft Co-pilot).
• Workflow optimisation: AI analyses projects, reallocates workloads, and helps practices meet deadlines more reliably (e.g. FYI Docs with Co-pilot).
• Anomaly detection: Machine learning flags unusual transactions and potential fraud instantly.
• Knowledge management: AI assists with tax or compliance research, cutting hours from manual work and increasing confidence in advice.

Key point: AI replaces repetitive effort, not accountants. It frees us to spend more time interpreting, guiding, and advising.

Avoiding the trap: tech-first thinking

One of the biggest mistakes firms make is starting with the tool instead of the outcome. Too often, a partner buys software after a slick demo, only for it to gather dust when it doesn’t fit real client needs.

The better path is client-first adoption:

1. Define the client result (e.g. “improve cash flow visibility”).
2. Map the process to deliver it.
3. Identify the AI that accelerates or enhances that process.

When AI is embedded in a structured, outcome-driven workflow, it stops being a shiny toy and becomes a genuine profit driver.

A client-first model for AI adoption

Firms succeeding with AI often follow a five-stage rhythm:

1. Discovery – data pull: AI-enabled tools gather a client’s full financial position in minutes, not hours, creating a rich foundation for advisory conversations.
2. Clarity – turning data into insight: AI converts raw data into dashboards, benchmarks, and models, highlighting the top opportunities or risks without drowning clients in spreadsheets.
3. Guidance – human + AI: Accountants interpret insights, ask deeper questions, and deliver recommendations. AI provides the analysis; humans provide wisdom and context.
4. Execution – reliable delivery: Workflow tools automate follow-ups, deadlines, and task allocation so advice is consistently delivered.
5. Continuous monitoring – always-on support: AI alerts accountants to risks or opportunities between meetings (e.g. low cash thresholds), enabling proactive contact.

This model transforms advisory from one-off sessions into continuous partnership.

Case studies – AI in action

1. Manufacturing cash flow turnaround:
   A €2.8m family-owned manufacturer struggled with stock inefficiencies. Using AI forecasting, the firm modelled different reorder strategies. A just-in-time approach cut stock write-offs by 40% and freed €120k in cash, which funded new machinery and growth.
2. Retail margin improvement:
   A retailer saw sales rising but margins falling. AI sales mix analysis revealed 12% of SKUs (Stock Keeping Unit) were unprofitable once marketing spend was factored in. Dropping these improved net margin by 2.5% annually.

Result: In both cases, AI supplied clarity, but the accountant supplied confidence and strategy.

Overcoming adoption barriers

Even with clear benefits, adoption isn’t smooth. Common barriers include:

• Skills gap: Teams fear they lack knowledge.
  Fix: Run small AI literacy workshops on tools staff already use. Nominate an “AI champion.”
• Cost concerns: Licences feel expensive.
  Fix: Start with one high-impact use case, prove ROI, then expand.
• Cultural resistance: Staff fear job loss.
  Fix: Frame AI as support, not replacement – removing low-value work so people can focus on meaningful, engaging tasks.
• Data security: Clients worry about confidentiality.
  Fix: Vet vendors rigorously, demand compliance certifications, and communicate transparently about data use.

Handled well, these barriers become opportunities to build trust.

Redefining the accountant’s role

AI doesn’t change what clients ultimately seek: trust, clarity, and strategic partnership. It simply enhances our ability to deliver it.

The accountant of today – and certainly of 2030 – will be:

• A navigator: using AI insights as a compass to help clients chart their course.
• A translator: converting complex data into clear, empowering stories.
• A strategist: aligning financial insight with business goals, spotting opportunities, and mitigating risks.

Future specialisms will emerge, from data accountants skilled in governance and analytics, to CFO-as-a-Service providers offering real-time strategic guidance to SMEs who can’t afford full-time CFOs. The automation of compliance gives us back the most precious resource: time. What we do with it defines our future.

The ethical compass

As trusted professionals, we must ensure AI is used responsibly. Four principles matter most:

1. Bias: AI learns from historical data, which may carry hidden biases. We must question and validate outputs.
2. Transparency: Black-box models can’t justify conclusions. Accountants must ensure advice is explainable.
3. Governance: Clients deserve clarity on where data is stored, who can access it, and how it’s used.
4. Accountability: No matter how advanced the AI, responsibility for professional advice rests with us.

Our credibility depends not on how advanced our tools are, but on how responsibly we use them.

Roadmap – bringing AI into your practice

You don’t need a revolution overnight. A structured approach works best:

1. Identify one high-value client outcome (e.g. faster invoice payments).
2. Map your current process.
3. Choose an AI tool to enhance it.
4. Pilot with a small group of willing clients.
5. Refine based on feedback.
6. Standardise and roll out more broadly.
7. Review quarterly to adapt and improve.

This rhythm turns AI from an experiment into a consistent growth engine.

Conclusion – leading the change

AI will reshape accountancy whether we like it or not. The firms that thrive will not be the cheapest or the fastest at compliance, but those who combine AI’s scale with human judgment, trust, and empathy.

We can remain record-keepers of the past - or become navigators of the future.

That future is already here. The only question is: will you lead with it?

This excerpt has been taken from the September 2025 edition of Practice News.