There is widespread frustration with the impact of data analytics (DA) in internal audit functions – with 80% of chief audit executives (CAEs) wanting to see improved outcomes, according to Gartner.
Gartner conducted a survey of 107 CAEs in March 2025 revealing that using DA within the scope of an audit engagement only led to materially improved outcomes about half the time.
“CAEs feel pressure to get better value from their DA investments – both to meet growing stakeholder expectations and to secure further budget for continued technology investment and innovation,” says Tegan Gebert, vice-president, Advisory in the Gartner Assurance practice. “However, to get to greater value, CAEs have been focused on better motivating and preparing their teams to use DA wherever feasible, which isn’t the right way to improve outcomes.”
Focused approach
CAEs are drawn towards broad DA usage for a number of reasons. First, a narrower focus on analytics feels counter to many audit leaders’ current strategies. For example, many CAEs track the percentage of audits using data analytics as a KPI.
CAEs can also feel that identifying DA opportunities happens at a more granular, engagement level than they’d typically operate – and they often doubt their own technical expertise (knowledge of the data or tools or analytic techniques), so they rely more on their data experts or auditors to report up to them what is possible.
“The problem with trying to use analytics wherever feasible is that not all analytic opportunities are good ones,” says Gebert. “This broad approach to DA quickly hits a point of diminishing returns.
“Once the obvious, high-impact opportunities are addressed, spreading analytics across every audit leads to wasted effort and diluted impact, and it likely puts a strain on the limited capacity of expert DA resources as well.” adds Gebert. “In contrast, when CAEs deliberately select fewer, high-impact audits and allocate more analytic resources to them, audit teams achieve deeper, more meaningful outcomes.”
How CAEs should prioritise audits for DA
To improve outcomes, Gartner recommends CAEs take personal ownership of DA prioritisation using their unique understanding of business objectives, risks, and strategic priorities. This involves evaluating potential audit projects not just on the feasibility of applying analytics, but on the necessity and potential impact – specifically whether analytics is likely to deliver significant value or insight.
CAEs should use explicit, structured criteria – such as scorecards or qualitative filters – to compare and rank audit opportunities based on criteria such as business impact, alignment with strategic goals, and the likelihood that analytics will lead to actionable outcomes.
“Once high-impact opportunities are identified and prioritised, CAEs should concentrate analytic resources – such as skilled staff, data experts, and advanced tools – on these select audits. This enables deeper analysis, higher quality insights, and greater overall value,” says Gebert.