AI is everywhere right now, especially in auditing. We hear bold claims that AI will revolutionize the profession, automate everything, and even replace auditors, but what’s really happening? While AI has immense potential, much of what’s being marketed as AI today is just well-branded automation or analytics. While these solutions can still be helpful, they often don’t live up to the hype. The solution: education around what’s being sold versus the underlying technological solutions being offered.
With over a decade of experience in product and technology and currently serving as the VP of Strategy at AuditMiner, I have spent years evaluating how emerging technologies can create value across industries. My perspective is not from a CPA or auditor's lens but as a technology leader focused on practical implementation and solving real problems for customers.
One of the biggest reasons AI is gaining traction in auditing is because the profession has been vastly underserved from a technology perspective. Many firms still rely heavily on Excel spreadsheets, manually consolidating multiple data sources, copying and pasting numbers, and spending excessive time on administrative work rather than analysis.
This lack of modernization makes the profession especially vulnerable to overpromises from vendors. Auditors are looking for ways to streamline workflows, but with increasing demand on time auditors cannot be expected to be AI experts as well, and may be sold tools that don’t truly solve their problems.
AI isn’t just one thing. It is a broad term encompassing different technologies, each with distinct capabilities. Here’s a breakdown of the key types of AI and where they realistically fit into auditing:
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AI isn’t a magic button that will eliminate manual work overnight. Instead, it should be seen as a tool to enhance efficiency, improve accuracy, and assist professionals - not replace them.
A common misconception is that AI can thrive simply by having vast amounts of data. While data is important, the quality and structure of that data are even more critical. AI models need clean, labeled, and well-governed data to produce meaningful results. Poor data quality can lead to incorrect outputs and unreliable decision-making.
At AuditMiner, we recognize that while AI has a promising future, the most pressing issues today revolve around data quality, change management to help firms adopt technology, and consistent processes that reduce staff training time and turnover. The focus should not be on replacing auditors with AI but on creating real efficiencies that improve accuracy and workflow. That’s why we prioritize solutions that:
These are the real, tangible problems that need to be solved today. AI may play a role in the future, but only when it can be implemented responsibly and in a way that aligns with the industry's needs.
Rather than buying into the hype, audit firms should take a measured approach to AI adoption:
Ask the right questions. Before adopting any AI tool, firms should evaluate:
AI has a bright future in auditing, but the road to meaningful adoption requires education, realistic expectations, and strategic implementation. By taking a thoughtful approach, the industry can move beyond the marketing buzz and into real true innovation, where AI works alongside professionals to create real value.
At AuditMiner, we aren’t chasing AI hype. We are focused on solving the most pressing issues for auditors: improving data quality, streamlining change management, and creating consistent processes that reduce staff training time and turnover. By standardizing data, reducing manual workflows, and helping firms integrate technology effectively, we empower auditors to work more efficiently with greater accuracy.
So before believing the next big AI claim, ask yourself: Is this a game-changing innovation, or just well-packaged automation? If it’s the latter, is it really solving my firm's biggest problems at scale?
