From Excel to AI: Future-Proofing Your Audit Process

Given how much has changed in recent years, the way businesses approach audits looks nothing like it did before. 

Read: From Seasonal Spikes to Talent Gaps: Is Audit Support Worth It? 

The Gaps in Traditional Audit Processes 

Back then, auditors spent long hours buried in spreadsheets, manually cross-checking figures and reconciling accounts. It was a time-consuming process, and even the smallest oversight could create big problems later. 

Today, that same work can be done in minutes. With the help of automation and advanced tools, what once required late nights, and multiple revisions is now just a click away. 

This shift has raised the bar across the industry. Firms that don’t adapt to these tools risk falling behind, especially as stakeholders demand quicker insights, stricter compliance, and greater transparency. 

In fact, 2024 research from Deloitte shows that about 67% of organizations report GenAI is now integrated into broader finance or work processes. While not all use cases are directly audit-focused, this demonstrates a clear shift toward Artificial Intelligence (AI) adoption in financial function. 

What is Artificial Intelligence in Auditing?

Artificial intelligence in auditing refers to the use of AI tools and technologies to make the audit process faster, more accurate, and less repetitive. Instead of going through thousands of rows in spreadsheets manually, a generative AI tools can scan large sets of financial data in seconds and point out anything unusual. 

Think of it as having an extra set of “smart eyes” that never get tired. This doesn't mean it will replace the role of auditors, but its focus is supporting them by taking care of routine tasks like checking numbers, spotting errors, or comparing transactions and strengthening internal control. 

The Benefits of Using AI in Auditing 

Once you understand what artificial intelligence in auditing is, the next question is why more firms are starting to use it. The short answer is that it makes the audit process more accurate, faster, and more reliable. Below are some of the key benefits of AI in auditing: 

1. Greater Accuracy and Fewer Errors

When an organization gets audited whether it’s externally or internally, it needs to be detailed. Since even the smallest can raise questions and create problems later on, without accuracy, the value of an audit is compromised. 

However, by integrating AI within the processes, auditors can review the entire dataset instead of relying on limited samples. Leveraging this tool allows them to run advanced data analytics that makes it easier to catch anomalies, spot inconsistencies, and ensure that nothing important is missed. The outcome is an audit that not only saves time but also gives leaders more confidence in the accuracy of the results. 

2. Efficiency and Time Savings

Audits are known for being time-intensive, and much of that comes from the sheer amount of data that has to be reviewed. Even with a highly skilled team, manually sifting through records, verifying details, and preparing reports can stretch the process out longer than businesses would like. 

By using AI, auditors can streamline many of these repetitive steps. For example, AI can quickly sort large datasets, highlight unusual patterns, and prepare preliminary reports. While this doesn’t remove every phase of an audit, it does free up time and resources, making the entire process more efficient. The result is a smoother workflow that allows auditors to focus on areas that require deeper analysis and judgment. 

3. Better Risks Detection and Prioritization

Catching every issue is important, but what really matters is knowing which ones pose the greatest risk to the business. Sometimes, warning signs are buried deep in the data, and without the right tools, they can be hard to spot or too late to act on. 

But with AI in the audit process, auditors can scan through all transactions and highlight patterns or anomalies that deserve attention. This helps them focus resources on areas that carry the highest risk. 

In fact, a recent study finds that companies using AI shows significantly better audit outcomes, including improved accuracy in spotting “high-risk” transactions and reducing “material weaknesses” in reporting. 

4. Improved Transparency and Audit Trail

 
One of the most important parts of any audit is being able to show how conclusions were reached. Without a clear trail of evidence, it can be difficult for stakeholders, regulators, or even internal teams to fully trust the results. 

AI can help by automatically documenting the steps taken during an audit, from the data reviewed to the anomalies flagged. This creates a transparent record of the process, making it easier to trace back findings and explain why certain decisions were made.  

When there’s a traceable audit trail, it’s easier to answer questions, confirm compliance, and provide stakeholders with assurance that the audit was thorough and transparent. 

Read Next: Audit Intelligence: How Can Auditors Use AI in Internal Audit? 

How to Use AI in Auditing? 

AI in auditing can be used in different ways that make an auditor’s role much easier and at the same time more reliable. Instead of spending endless hours on repetitive checks, AI tools can take over the heavy lifting and let auditors focus on the work that really needs their attention. Here are a few practical examples: 

a. Minimizing the Risks of Over-Testing

One of the most useful ways AI helps is by reviewing the entire dataset, not just a small sample. This means auditors don’t have to scan large amounts of data line by line. Instead, AI can go through everything at once and quickly flag the transactions that look unusual. That way, the audit team can spend their time focusing only on the items that really need attention.

b. Changing the Way Data Is Gathered and Tested

Back then, auditors usually had to work with smaller pieces of data because systems couldn’t handle the full set. But with AI becoming more available in the market, that limitation is no longer a problem. In fact, the Journal of Accountancy reports that “auditors can now request a full dataset and derive many of the needed sub-datasets and not worry about the inability to analyze the full dataset.” 

What this means is you get a clearer, more complete view right from the start. Auditors don’t have to guess which chunks to sample they can begin with full data, then zero in on what really matters. 

c. Refining Audit Scope and Planning

In auditing, planning refers to the process of setting objectives, assessing risks, and designing procedures to ensure the audit is efficient and effective. It’s the stage where auditors decide what areas to examine more closely and how resources will be allocated. 

Planning has always been one of the most crucial parts of an audit, because it sets the stage for everything that follows. The challenge is that, without the right tools, auditors often had to rely on limited samples or instinct to decide where to focus their attention. That approach left room for blind spots. 

However, AI changes this by giving auditors a clearer starting point. Instead of guessing, it can analyze the full dataset and highlight patterns, anomalies, or areas that carry higher risk. With that information upfront, auditors can refine their scope, concentrate resources where they’re needed most, and improve risk management from the beginning. 

d. Creating More Space for Strategic Work

In any audit, a balance has to be struck between detailed checking and higher-level analysis. Detailed tasks are essential, but they can consume much of the available time. AI helps by handling many of these steps quickly and consistently in the background. 

What this does is give auditors more room to concentrate on areas that call for professional judgment, such as assessing risks, reviewing controls, or interpreting results for decision-makers. Rather than changing the purpose of the audit, AI supports it by ensuring that more time is available for the parts of the process that add the greatest value. 

Implementing AI in Your Audit Process 
  

Now that we’ve looked at how AI can be applied in audits, the next step is figuring out how to put it into practice. For many firms, the idea of bringing in new technology can feel overwhelming, like it means tearing down everything they’ve already built.  

But the truth is, it doesn’t have to work that way. Implementing AI can be done in small, practical steps, allowing firms to ease into the transition without disrupting existing systems. You can begin with manageable changes such as using AI tools to handle routine checks or flag unusual transactions.  

Once that foundation is in place, it becomes easier to expand and apply AI to more complex parts of the audit process. The key here is to view it as a gradual shift, not the other way around.  

Steps to Get Started with AI in Auditing 

Now that you get the sense of implementing it, the next question is: where do you actually begin? The good news is you don’t have to transform everything at once.  

In fact, firms that succeed with AI usually start small, test it in the right areas, and then expand once they see results. 

Here are a few practical steps to guide the process: 

a. Start with Pilot Projects

To make it less overwhelming with you and your organization, then begin by testing AI in one or two focused areas, such as anomaly detection or transaction reviews. Think of this stage as “learning by doing” on a smaller scale. 

By starting small, it will be easier for your end to measure the result of integrating it within your processes, as long as you set clear KPIs to track performance. 

For instance, Kingston Smith, a UK audit firm, piloted AI on transaction reviews and quickly freed up auditors from repetitive tasks. 

When planning your pilot, keep these points in mind: 

• Choose a manageable area: Start with one process that’s repetitive but critical, such as testing transactions. 

• Set measurable goals: Define success upfront — e.g., reduced time per review, fewer manual errors, or improved anomaly detection. 

• Evaluate and refine: Use the pilot to gather insights, then decide whether to scale up or adjust your approach. 

This way, you’re not overhauling everything at once but steadily building confidence with AI in a low-risk, high-learning environment. 

b. Train Your Team

Even if you have the best AI tools in the market, they won’t deliver results if your team doesn’t have any idea how to use them. Hence, proper training is the key to making sure the technology actually supports your audit process instead of slowing it down and overwhelming your staff with technical jargon. 

Here are a few ways to approach it: 

• Awareness first: Let your team know what the tool can do and where its limits are. 

• Hands-on practice: Give them a chance to try the system on smaller, non-critical datasets. 

• Continuous learning or ongoing support: Offer refresher sessions or assign someone as a go-to resource when questions come up. 

By doing this, it’s like you’re making the whole process less intimidating for your team. Instead of seeing AI as a threat, they’ll begin to see it as a tool that helps them work smarter. 

c. Choose the Right Tools and Vendors

Not all AI tools are designed the same and picking the wrong one can make or break your sanity. The key here is to look for solutions that fit your firm’s specific audit needs, rather than chasing every new piece of AI technology in the market. 

To help you decide, consider these points: 

• Integration matters: Make sure the tool can work smoothly with your existing audit software or accounting systems. 

• Data security and compliance: Since audits deal with sensitive financial information, check whether the vendor has strong security certifications and compliance features. 

• Vendor credibility: Go with providers that have a proven track record in the financial or audit space, not just general AI tools. 

• Ease of use: Even the most advanced system won’t help if your team finds it too complex, so find a tool that is user friendly. 

Think of it less as buying software and more as choosing a partner. The right vendor will guide you through setup, training, and scaling, so the technology actually delivers results. 

d. Start Building Governance and Oversight

Since many organizations are becoming more digitally inclined, it’s only right to make sure that the use of AI in audits is carefully managed. Without proper oversight, even the most advanced tools can create new risks instead of solving old ones. 

Here’s how you can start building strong governance around AI: 

• Set clear rules: Decide when and where AI should be applied in the audit process, so it’s consistent across the team. 

• Keep humans in the loop: AI can process data at scale, but auditors should still review the findings and make the final call. 

• Maintain audit trails: Keep a record of how AI tools reach their conclusions to support transparency and accountability. 

• Focus on compliance and ethics: Make sure AI use aligns with privacy regulations and professional standards. 

Strong oversight not only protects your organization but also reassures stakeholders that your audits remain reliable and trustworthy. 

Need Extra Support for Your Audit Team? 

Consider D&V Philippines. We provide scalable, cost-effective audit support solutions that help your team get the job done efficiently without compromising quality. Schedule a free consultation with us today or visit our website to know more about our audit support solutions.      

You can also download our whitepaper Seasonal Audit Support for US Audit Firms to see how our solutions have helped other firms and how they could help your team too.