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From vision to implementation: crafting your audit firm’s AI strategy

In the dynamic landscape of auditing, the pressure to provide accurate, timely, and insightful services has never been greater. Clients are demanding deeper insights and faster responses, while regulatory environments continue to evolve. For audit firm owners, developing a tailored artificial intelligence (AI) strategy is no longer optional — it’s essential for maintaining competitiveness and delivering high-quality, efficient audits.

Many audit firms are unsure of where to start when it comes to crafting an AI strategy. That’s why it’s important to understand why AI is needed, what it can do for audit firms, and how to approach AI adoption as an evolution rather than a complete overhaul. The goal is to implement AI in a practical, guided way that aligns with your current processes and complies with professional standards.

What is an AI strategy?

An AI strategy is a structured plan for integrating artificial intelligence into your operations and gaining a competitive advantage by improving audit quality, reducing manual effort, and unlocking new advisory capabilities, all while aligning AI with your firm’s long-term growth and client service goals.

A successful AI strategy entails a comprehensive approach that goes beyond simply implementing AI tools. It provides clarity on how AI will transform your audit processes, enhance client services, and drive growth. It should encompass several key elements to ensure effective integration and maximize the benefits for your audit firm. A well-crafted strategy typically includes:

  • Clear vision: A defined goal of how AI will support and align with your firm’s goals
  • Adoption roadmap: A detailed plan outlining specific use cases, implementation timelines, and measurable goals
  • Workforce impact plan: Strategies for upskilling and reskilling employees to work effectively alongside AI systems
  • Data governance framework: Guidelines for responsible data management and usage in AI applications
  • Ethical considerations: Principles and protocols to ensure responsible and unbiased AI use
  • Regulatory compliance: Measures to adhere to relevant industry regulations and standards
  • Performance metrics: Key indicators to measure the success and ROI of AI implementations

Why audit firms need an AI strategy

An AI strategy is not just about technology; it’s about positioning your firm for long-term success. By enhancing accuracy, boosting efficiency, and delivering deeper insights, AI enables audit firms to meet client expectations, adapt to regulatory changes, and stay ahead of the competition. Delaying the integration or effective use of AI puts your firm at risk of falling behind competitors already leveraging AI.

Many firms are hesitant to adopt new technology, but it’s important to note that adopting AI doesn’t mean starting from scratch. With solutions like those from Thomson Reuters®, AI implementation is an evolutionary process. You can build upon your existing infrastructure, enhancing current systems rather than replacing them.

This incremental approach offers reduced risk through gradual implementation that minimizes operational disruption. When you start with smaller, high-impact projects that quickly demonstrate value as opposed to a complete system overhaul, you’ll realize faster ROI and enjoy a smoother transition for staff.

In terms of competitive advantage, audit firms that adopt AI will differentiate themselves by the quality and depth of their services as AI enhances not only internal efficiencies but also client-facing opportunities. For example, AI-driven analytics provide tailored insights that strengthen client relationships — and with the ability to identify risks before they become issues, your audit firm can naturally make the lucrative shift to advisory services.

Understanding the power of AI for audit

AI-powered audit technology has the capability to swiftly analyze vast datasets, identifying patterns, anomalies, and potential risks with exceptional speed. This enables auditors to concentrate on more intricate and strategic aspects of their work, such as interpreting results and offering insights based on experience.

Moreover, AI facilitates predictive analytics, empowering firms to anticipate potential risks and trends based on historical data. This proactive approach enhances risk identification and decision-making, providing a more comprehensive understanding of the financial landscape.

AI and machine learning algorithms also continuously learn from auditors’ interactions, allowing them to adapt to evolving industry regulations. This adaptability is essential in a profession that is constantly changing.

Let’s look at 5 specific ways AI can transform audit and why it is necessary to remain competitive in today’s fast-paced landscape.

1. Leveraging AI for an automated, risk-based engagement process

In today’s competitive business environment, clients expect auditors to provide more than just financial compliance. They want a holistic view of their financial well-being, along with opportunities for improvement.

Transitioning to new audit software may seem daunting, but the benefits are substantial. AI and data analytics technologies continue to evolve, making the audit process increasingly effective and efficient.

Imagine a comprehensive audit preparation, compilation, and review tool powered by AI, ensuring compliance with professional standards and facilitating peer review. With AI’s assistance, auditors can create customized audit programs based on documented risks and assertions, eliminating over- or under-auditing.

Embracing AI enables firms to meet evolving demands quickly while enhancing audit efficiency and quality. Partnering with a trusted provider like Thomson Reuters ensures a smooth transition, minimizing disruption to existing processes and maximizing the benefits of AI-driven audit technologies.

2. Automating the analysis of transaction data to improve audit quality

AI-powered audit intelligence software like Thomson Reuters Audit Intelligence Analyze provides auditors with an automated way to analyze all transactions as part the current workflow. The results save time with the ability to focus audit procedures on high-risk areas and minimize work on low-risk areas. This improves audit quality by pulling out unusual transactions, proving the required documentation, and catching items that would normally be missed by humans.

You can also customize the rules for each engagement for full control over how the analysis is performed. Within minutes, smart analysis technology can automatically select samples to test so you can evaluate the test results. When the analysis is complete, simply select a destination folder to save as a workpaper in your engagement binder.

Although implementing new technologies in audit solutions can be challenging, opting for AI-powered solutions that seamlessly integrate into the existing workflow and don’t require the firm to adopt a new audit methodology or time-consuming data conversion can simplify the process. With an easy data ingestion process to obtain general ledger, sub ledger and trial balance data, you can simplify communication and minimize postprocessing of data.

3. Transforming risk assessments with AI

In the past, auditors relied heavily on manual processes to uncover risks in financial statements and business operations. While effective, this approach is time-consuming and susceptible to human error.

AI-driven audit software with assisted decision-making capabilities can proactively access anonymized data from the audit community, suggesting areas of risk that may have been overlooked. This empowers audit teams to conduct audits more efficiently and confidently. In addition, AI can help auditors quickly identify the risks that come with changing tax legislation by analyzing large volumes of data and flagging areas that could affect a client’s financial position.

4. Keeping pace with evolving legislation

With cloud-based audit technology, audit teams can standardize and update procedures instantly, ensuring consistency across engagements. This flexibility is essential for adapting to new tax laws quickly and at scale. AI algorithms can analyze historical tax data and past client filings to identify trends and patterns, helping you assess the potential impact of new tax laws on a client’s risk profile.

Together with AI-powered tax research tools embedded in audit platforms, your firm can continuously monitor regulatory updates, issuing alerts for legislative changes that might pose new risks or opportunities for misstatements. Using AI-driven insights allows auditors to proactively reassess inherent risks and plan audit adjustments more efficiently.

5. Unlocking insights with data analytics

Data analytics — the process of examining raw data to extract meaningful insights — is not new to auditors. The profession has long relied on analytics to enhance audit quality. Today, firms are leveraging increasingly sophisticated data analytics tools to conduct high-quality audits more efficiently and with reduced manual effort.

AI further enhances the power of data analytics by enabling deeper trend analysis, anomaly detection, and risk assessment. AI-driven systems streamline and automate these processes, ensuring consistent and thorough evaluations. Predictive analytics powered by AI can offer more nuanced insights, leading to better identification of high-risk areas and improved audit outcomes.

By integrating data analytics and AI, audit firms can elevate both the quality and value of their audits, driving more efficient, insightful, and impactful results. Common applications of data analytics in auditing include:

  • Invoice matching: Aligning purchase orders with invoices and payment records to verify accuracy.
  • Inventory analysis: Comparing purchase history with sales data to monitor inventory turnover and pricing.
  • Revenue trends analysis: Examining revenue performance across different products and regions.
  • Segregation of duties testing: Identifying potential role conflicts by analyzing transaction metadata to ensure proper controls.

In short, AI offers a data-driven audit strategy that enables your staff to understand the data population more thoroughly and know where risk resides for reduced testing time and a higher level of confidence in your work.

A step-by-step guide to crafting an AI strategy for your audit firm

Creating an AI strategy tailored to your audit firm involves several critical steps to ensure alignment with business objectives. Below is a guide to help audit professionals develop an AI strategy:

  1. Explore AI use cases. Investigate how AI technologies like machine learning, natural language processing, and robotic process automation are being applied to audit tasks. As described above, pinpoint areas like risk assessment, compliance, and financial reporting where AI can deliver tangible benefits for your firm.
  2. Assess firm readiness. Evaluate your IT Infrastructure and determine whether your firm has the necessary tools to support AI implementation, including data management systems. Many audit software providers, like Thomson Reuters, have AI built into their existing products and can help you take advantage of these features effectively. It is also important to identify gaps in your staff’s expertise and work with your software provider on training.
  3. Define your AI roadmap. Be sure to establish measurable goals for AI initiatives to ensure the project directly supports broader firm objectives, such as improving audit efficiency, reducing errors, or enhancing client services. Focus first on practical needs, such as automating sampling processes, identifying anomalies in financial data, or improving report generation. Your roadmap should also outline the necessary implementation steps, support requirements at each phase, and the key performance indicators (KPIs) to measure success.
  4. Understand your data. With a solid roadmap in place, it is time to identify the types of data required — both existing and new — to power your AI solution. Data is the lifeblood of AI. Reliable, high-quality data is essential for driving insights and automation in audit processes (see next section for details). Assess whether your firm already has access to the necessary datasets or if you need to source additional data. This step ensures you maximize the potential benefits AI can bring to tasks such as risk assessment, anomaly detection, and compliance checks.
  5. Develop an algorithm strategy. Algorithms form the core intelligence of any AI system. These models can revolutionize audit tasks, from predictive analytics to fraud detection. Developing and deploying effective algorithms requires specialized expertise. Engaging experts via your software provider ensure your AI applications meet the rigorous standards expected in audit operations.
  6. Build up your infrastructure. Robust infrastructure is critical for implementing AI systems. This encompasses the computing power needed to process large volumes of audit data efficiently. With advances in cloud computing, firms now have scalable options to handle complex AI workloads. Determine whether to host AI systems on your own infrastructure or leverage third-party platforms, like Thomson Reuters Cloud Audit Suite. A well-planned infrastructure strategy guarantees that your AI solutions are not only operational but also scalable as your firm grows.
  7. Execute your AI strategy. Secure stakeholder buy-in, engage leadership, and communicate how AI will align with the firm’s goals, improve client satisfaction, and enhance efficiency. Most important, demonstrate ROI and highlight potential cost savings, increased productivity, and improved accuracy.

The importance of clean data as part of your firm’s AI strategy

The quality and integrity of data is paramount when it comes to the effective use of AI, and auditors must have confidence that their data is clean. When you consider that the data is the source material that the AI learns from, the need for clean data becomes clear. Analysis based on bad data is not only unhelpful — it results in wasted work and can even be detrimental to the reputation of your firm.

Gathering data in disparate forms from various sources increases the risk of unclean data or errors occurring during the data gathering process. That’s why quality checks are so important before diving into any data analysis.

Data quality is based on the following:

✓ Verification of completeness

✓ Accuracy

✓ Data integrity to ensure it has not been altered

✓ Consistency in data formats, naming conventions, and precision

✓ Multiple data source agreement

✓ Exportability and portability

✓ Cost effectiveness considering the effort and time required to obtain, clean, and verify the data

Unfortunately, sometimes there are barriers to data access. When a client has numerous accounting systems, all containing different sets and types of data, it can present potential challenges. Data existing in disparate forms and locations increases both the risk of unclean data and the time and complexity necessary to even access data.

The solution to this risk is to use a high-quality data ingestion service provider that offers connectors for the accounting systems that your audit clients use. Such a service can make ingesting, cleaning, and standardizing data a highly efficient process, and this is a critical first step in a data-driven audit.

Act now to stay ahead

As the auditing landscape continues to evolve, embracing AI is not just about keeping pace with technological advancements — it’s about unlocking new possibilities for growth and innovation. By integrating AI into your audit processes, your firm can transcend traditional boundaries, offering clients greater insights and value. This provides opportunities not only to enhance operational efficiency, but it also positions your firm as a leader in the industry.

The path to AI adoption is a strategic evolution. With Thomson Reuters, adopting the latest AI-powered technology doesn’t mean you have to disrupt or replace your current audit workflow, and you can seamlessly integrate AI technologies into your existing processes. This approach ensures that you remain compliant with professional standards while maximizing the benefits AI has to offer.

✓ Thomson Reuters Cloud Audit Suite uses AI to analyze historical financial data, transactions, and industry benchmarks to identify anomalies, trends, or outliers that could indicate potential risks. This ability helps your firm identify areas with a higher risk of material misstatement or non-compliance.

✓ Thomson Reuters Audit Intelligence Analyze is the first in our audit Intelligence suite of AI-powered tools for data-driven audits. With Analyze, your firm can automate transaction analysis, enhance audit quality by focusing on high-risk areas, and cut the time your firm spends on selecting and testing samples by 50%.

Now is the time to harness AI’s potential and secure your audit firm’s competitive edge. For more information on how modern technology can enhance your audit firm, watch our on-demand webcast Future proofing-audit firms: Embracing modernization and technology.

Ready to see how the Cloud Audit Suite can accelerate your firm? Check out our interactive demo.

Audit Intelligence Analyze

The first in our Audit Intelligence suite of AI-powered tools for data-driven audits.