Audit as a profession has been in a holding pattern in recent decades. The captive audience of large businesses obliged to undergo statutory audit on a regular basis, combined with a relatively tight market of firms with the scale and expertise to conduct audits at the quality required by regulators has led to predictable results.
A 2024 report found that audit fees for UK-listed companies rose by 75% over the past five years. The cause? A lack of competition, tougher regulation and an increasing shortage of skills. With demands on the profession growing, firms are effectively tasked with carrying out increasingly detailed reviews with fewer resources.
While the short term windfall for accounting firms is no doubt welcome for auditors, the long term view of fewer firms conducting squeezed audits benefits no one. However, change is on the horizon. Audit is an area where growth in the scale, popularity and sophistication of artificial intelligence (AI) and machine learning (ML) have the potential to be much more than buzzwords or passing trends.
They offer practical solutions that can help us tackle some of the most time-consuming and mundane aspects of our work, like data gathering and initial analysis, freeing us up to focus on more strategic and higher risk tasks.
However, from my conversations with peers and clients alike, it’s clear that many people aren’t fully aware of how these tools can be applied in our day-to-day work. I want to use this opportunity to explore how AI and ML can transform our profession and why we should all be paying close attention.
The dream of perpetual audit
Imagine a world where audits aren’t confined to a once-a-year tick box. Instead, they’re a continuous process—an "always-on" audit that provides real-time insights into the accuracy of a company’s accounts and the company’s financial health.
This isn’t just a dream; it’s becoming a reality thanks to AI and ML.
Currently, audits are an annual snapshot, giving us a look at how a company was performing at a specific point in time. But we all know that a lot can change in a year. What if we could move to a model where we’re constantly monitoring and analysing data, catching issues as they arise, rather than after the fact?
By integrating financial information at the point of generation – something already well underway with the adoption of cloud accounting and enhanced by the increasing adoption of business intelligence (BI) reporting tools – we have a chance to monitor audit health in real time.
Practical steps for implementing AI and ML
To make this vision a reality, we need to start with the basics: investing in the right technologies.
Recent years have seen new software designed specifically for audit come to market such as DataSnipper. These are the first step toward more sophisticated AI-driven processes that can automate routine tasks and allow us to focus on what really matters—analysing and interpreting the data to provide clients with actionable insights.
But technology alone isn’t enough. We also need to encourage our clients to invest in their own data processes.
Reliable, high-quality data is the foundation of any successful AI-driven audit. If our clients don’t have their data in order, it doesn’t matter how advanced our technology is—we’ll still be limited in what we can achieve.
There’s also a cultural shift that needs to happen. Both within our firms and with our clients, we need to move away from the mindset that an audit is a once-a-year event. Instead, we should be thinking of it as a continuous process that adds value throughout the year. This is where AI and ML can really shine, helping us to provide more timely and relevant insights that can drive better decision-making.
What does this mean for the bottom line?
One of the most exciting aspects of AI and ML in audit is the potential to reduce costs without sacrificing quality.
As these technologies become more advanced and more widely adopted, we can expect the cost of implementing them to decrease, along with the human resources required to conduct an audit. This will lead to lower audit fees in the long term, making high-quality audits accessible to more companies – and making offering an audit service more profitable and accessible for firms outside of the largest providers, which currently account for 98% of audit revenue.
Cutting the time and manpower required to conduct an audit is a genuine game-changer.
- Integrating new regulations will be a matter of tweaking algorithms, rather than having to find new pairs of hands to sift through documents
- Firms can scale their audit offerings without losing control of headcount
- Clients can engage more whole-heartedly with their audits without having to count the hours on the clock
Make no mistake – this will reduce the costs of audits that clients need to shell out. And while firms may stand strong to maintain their prices for a time, it will only take a few challenges to bring an AI-powered audit to the market at a fraction of the price to bring wide-scale arbitrage. But while costs will drop for clients, they will also decrease for firms, enabling them to grow their audit businesses while still maintaining margins.
There will also be a genuine rise in utility – as AI and ML become more capable of predictive analysis and trend monitoring, we’ll be able to provide our clients with earlier warnings of potential risks and more strategic advice.
There will always be a place in the market – and a price – for genuine value.
What happens next for audit?
If we want to stay relevant and competitive in the audit industry, we need products, processes and ways of working that are fit for purpose.
This means investing in the right tools, training our teams, and working closely with our clients to ensure they’re ready to support a more advanced audit process.
We’re on the verge of a transformation that could fundamentally change how we do our work and how our clients perceive the value we bring. The technology is here, the potential is clear, and the opportunities are vast.
