Key takeaways

• Data and technology skills are now essential for modern audit
• Auditors are moving from sampling to analysing full datasets
• Excel, data visualisation, and AI are critical tools
• Upskilling improves both audit quality and career progression
• Collaborative initiatives like data-wranglers groups accelerate learning

Audit is undergoing rapid transformation, driven by advances in data analytics, automation, and artificial intelligence (AI).

To explore what this means in practice, Matt Rawlins, Director of Growth at Kaplan, sat down with James Berridge, Director at Saffery, to discuss how technology is reshaping auditing — and how professionals can build the skills they need to keep up.

Why data and technology skills matter more than ever in audit

Matt Rawlins: Why is upskilling in data and technology becoming so important for auditors?

James Berridge: The volume and complexity of data businesses generate today has changed the nature of audit. Traditional approaches — particularly sampling — are still relevant, but they’re no longer sufficient on their own.

We’re increasingly expected to analyse full datasets, identify patterns, and provide deeper insights. That requires a different skill set.

Matt Rawlins: So it’s not just about efficiency — it’s about audit quality as well?

James Berridge: Exactly. Data analytics allows us to enhance audit quality by testing more data and identifying risks more effectively. Regulators are also placing greater emphasis on how technology can support stronger audit outcomes.

How data analytics is changing the audit process

Matt Rawlins: How is data analytics changing the way audits are actually carried out?

James Berridge: One of the biggest shifts is moving from sample-based testing to full-population analysis.

Instead of selecting a subset of transactions, we can now interrogate entire datasets. That gives us a much clearer picture of what’s going on and helps us spot anomalies that might otherwise be missed.

Guidance from the IAASB supports this direction, highlighting how data analytics can strengthen audit evidence through more comprehensive testing.

The most valuable data and technology skills for auditors

Matt Rawlins: What skills should auditors be focusing on if they want to stay relevant?

James Berridge: There are a few core areas.

First, Excel is still absolutely fundamental — but people need to go beyond the basics.

Tools like PivotTables, Power Query, and advanced lookup functions allow you to work with much larger and more complex datasets. Microsoft’s guidance shows how Power Query, for example, can automate a lot of the data preparation work.

Second, data visualisation tools like Power BI are becoming increasingly important. Being able to communicate insights clearly is a huge part of the role.

And then there’s AI. Auditors don’t need to become data scientists, but they do need to understand how these tools can support their work.

Does AI replace sampling or enhance it?

Matt Rawlins: There’s a lot of discussion around AI — do you see it replacing traditional audit techniques like sampling?

James Berridge: Not replacing — enhancing.

AI and data analytics allow us to analyse full populations and identify patterns much more efficiently. But the audit still relies on professional judgement.

So rather than replacing sampling entirely, technology helps us apply it more effectively and focus our attention on higher-risk areas.

Launch a data-wranglers programme in six steps

Matt Rawlins: You’ve spoken before about “data-wranglers” groups. What are they, and how can firms set one up?

James Berridge: It’s essentially a collaborative learning group where people come together to build data skills by working on real problems. It’s a very practical, low-cost way to upskill teams.

What you’ll need

• 5–10 motivated team members
• Access to tools like Excel or Power BI
• Regular sessions (e.g. every two weeks)
• Real audit data or case studies

Time commitment

• 1–2 hours per session
• Run for at least three months to build momentum

Expected outcomes

• Improved confidence with data tools
• More efficient audit processes
• Greater adoption of analytics across teams

Step 1: define your goal

Start with a clear objective — for example, improving Excel capability or introducing data visualisation.

Step 2: start small

Pilot the group with a small number of people before scaling.

Step 3: focus on real problems

Use real audit scenarios rather than theoretical exercises.

Step 4: rotate leadership

Encourage different people to lead sessions. It builds confidence and spreads knowledge.

Step 5: share what you learn

Capture outputs like templates or dashboards and share them more widely.

Step 6: scale over time

Once it’s working, expand the model across the organisation.

Build your data and technology skills in audit

This conversation underlines why data literacy and technology skills are no longer optional in professional services. Firms that invest in upskilling their teams will not only improve efficiency and audit quality but also empower their people to innovate and add value.

As James put it:

“Don’t develop habits - embrace change.”

Develop the skills needed to succeed in modern audit with Kaplan’s specialist apprenticeship programme.

Explore the ACCA Finance Analyst Level 3 apprenticeship.