AI-Powered Audits: Read Everything, Miss Nothing

Most audit and assurance partners have known for years that modernizing their technology stack would be critical to their future success, and their focus has been on audit platforms and data analysis/testing tools. While I completely agree that modern SaaS solutions to address these key areas will be absolutely necessary, this strategy results in two outcomes: your audit approach will be largely constrained by the capabilities of the platforms you select, and it ignores the wealth of knowledge your firm has accumulated over the years.

Most of us have heard the phrase ‘data is the new oil,’ and while that generally is a revenue statement, it also is your competitive advantage if harnessed. New firms have the upper hand today.  They can create a firm with an accessible data architecture and build insight learning with AI from the start.

Established firms are struggling not because they lack talent or experience, but because they have a fundamental data architecture problem that is quietly undermining everything they hope to accomplish.

After working with dozens of audit leaders over the past few years, it has become clear that structured data is not just a nice-to-have technology upgrade; it is becoming the defining factor.  CPA Practitioner highlighted the difference between firms that thrive by harnessing their data and firms that slowly lose relevance and fall behind because they do not empower their staff with AI solutions.

The Hidden Crisis Every Audit Leader Faces

When firms map out where their client information lives, the result is eye-opening: local drives, document management systems, practice management solutions, multiple workpaper platforms, email archives, and legacy systems that hadn't been updated in years.

The best and brightest people are spending nearly half their time hunting for information instead of analyzing it. More critically, they are missing opportunities to provide real value to clients because they simply cannot access their own institutional knowledge quickly enough.

This pattern appears repeatedly across the industry. Audit leaders recognize their teams' capability for more sophisticated analysis, but they are hindered by data chaos that renders even basic insights seem impossibly complex to deliver.

The firms that are winning are not necessarily smarter or more experienced; they have just solved the data foundation problem that everyone else is still wrestling with.

For a deeper dive into how audit leaders are approaching AI adoption, the Accounting AI Playbook, an independent resource co-authored by audit leaders from top firms- offers practical frameworks and case insights.

The AI-Powered Data Transformation is Happening Across The Audit Profession

Structured data creates advantages in three critical areas that directly impact competitiveness, profitability, and innovation.

1. Speed Becomes a Competitive Weapon.

Leading firms have transformed from teams spending hours hunting for documents to finding any piece of information in seconds. AI-powered search across all client data, automated workpaper organization, and real-time collaborative reviews are operational realities that create dramatic efficiency gains.

Initial steps in structuring data have happened in finance and CAS practices, and a recent article by McKinsey confirmed that structuring financial data has led to efficiency gains of 39% or more. Many firms are finding further efficiencies by deploying AI agents and automating workflows that fit the firm’s practice and client needs, creating a flywheel of competitive opportunities. These same structured data practices make the performance of audit work eligible for AI audit agents and AI/ML transactional testing automations easier, faster, and explainable. Audit AI is no longer theoretical, it powers real-time testing, fraud detection, and predictive analytics.

Financial data started as being reasonably structured, but what about all your unstructured data? Think about the knowledge and experience that is trapped in your emails, documents, PDFs, images, and even text messages.

Start with financial statement footnotes. Your firm has written a lot of these, and they are trapped in documents and PDFs in your new/old audit platform, your client portals, and your document management systems. Having an AI data model that can scan, classify, and associate your footnotes with accounts means that the next time you need to write a specific footnote, you can have an AI agent, like Tellen’s footnoteAI,  serve up the most common, the latest version, and the partner’s preference for this account. The footnote itself is structured data, so it can insert the account balance and ensure that it is correct if changes to the account balance occur later. That is more than a time saver, it’s peace of mind and improved time to delivery.

Another great example is your subject matter expert who is about to retire. Your firm has relied on her highly specialized knowledge, and it’s been your competitive advantage.  She’s been coaching a couple of your junior staff, but with the usual staff turnover, you are worried about continuity in your practice. Using an AI data model that processes her email correspondence, her local drive, the documents, workpapers, and training materials she’s developed will create a rich and powerful repository that staff can query when they have a question. In fact, your expert can test that repository herself by chatting with it and asking questions to ensure it’s as complete as possible.

As new knowledge is gained, new work is performed, and it can be added to the repository to make it richer and more valuable. That’s a competitive weapon.

2. Premium Pricing Through Genuine Insights

When historical data is accessible and standardized, firms can suddenly offer predictive analytics that would have been impossible before. Leading practices that marry AI audit agents with structured data now identify fraud risks months before traditional red flags appear, forecast cash flow issues with remarkable accuracy, and provide industry benchmarking that drives real strategic decisions.

The history of engagement data can also be harnessed to quote the engagement more appropriately. Understanding the complexity of this engagement compared to similar engagements, the timeliness and accuracy of client communications, new regulators or standards, and the experience of staff can all be used to model the ideal price to quote for work.

3. Talent Becomes a Magnet Instead of a Struggle

The best auditors coming out of school expect modern tools. When firms can demonstrate integrated platforms, automated workflows, and cutting-edge analytics and AI capabilities, they attract people who stay longer and produce better work. New staff also want to know they are supported while learning and working.

With your firm’s knowledge accessible and attentive to the exact needs of staff, you can demonstrate that they are a priority, not just their utilization rates.

Firms still wrestling with scattered Excel files, non-integrated systems, and manual processes are losing talent to competitors who have invested in their data foundation.

The Proven Implementation Approach

The most successful transformations do not try to solve everything at once. Success starts with understanding the current data landscape, mapping exactly where information lives and how it flows through processes. This exercise is often revealing, sometimes embarrassing, but always essential for planning the path forward.

Smart firms pick one specific pain point to tackle first. Maybe it is concentrated subject matter expert knowledge, training materials, or footnotes. They prove the concept and build confidence before expanding to other areas. Deploying an AI agent workforce enables firms to automate repetitive workflows while scaling experience.

Throughout the process, everything gets measured, and you see time saved, errors reduced, client satisfaction scores improved, and team efficiency metrics go up. This approach focuses on demonstrating clear business value at every step rather than just implementing new technology.

Firms that follow this methodology see sustainable transformation. Those who try to change everything overnight usually struggle with adoption and see limited results.

The Competitive Window is Now

Firms investing in creating a data model that AI can harness are positioned to dominate the next decade of public accounting. Scanning every document your firm has ever created, classifying that data, and making it accessible to your AI enterprise search will ensure firms realize the power of that data. Your stored data will be an asset not a storage cost and that asset has the potential to improve your profits, enhance your staff, and create new service lines to propel firm growth.

Firms who don't harness their data will gradually become less competitive, less profitable, and less attractive to both clients and talent. Tellen is helping firms structure and unlock their data for AI-driven insights.

Since the time of electronic workpapers, unlocking firm data has been the vision, but it’s taken the evolution of Gen AI in the last couple of years to make this possible. The technology is mature enough now that implementation risk is manageable, but the competitive advantage window won't stay open forever. Every quarter that passes is another quarter competitors get further ahead.

The question isn't whether this shift will happen; it is whether forward-thinking audit leaders will lead the change or be forced to follow it.