AT Think

Generative AI: Optimizing pursuits to fuel growth

The Virginia Society of CPAs' Future of Work Survey 2022 found that the most significant challenges facing CPA firms are understaffing and overwork. To tackle this capacity challenge while sustaining growth, accounting firms are exploring how artificial intelligence technologies can boost productivity and curtail costs by automating time-consuming repetitive tasks and streamlining inefficient workflows across the practice.

The survey revealed that the primary tactic CPAs are using to address the capacity crunch is automating or enhancing work with technology (63%), with 62% of respondents extremely or very prepared to invest in and adopt new technology; investment in AI ranked second in importance only to implementing advanced cybersecurity measures.

Similarly, a 2022 Client Advisory Services (CAS) benchmark study from CPA.com and AICPA found that the majority (76%) of top-performing CAS firms have deployed workflow technology, with 24% implementing AI tools in their practice. 

As generative AI tools become more readily available, more firms will look to augment accountants' roles with AI-powered technology in order to reduce inefficient manual data entry and processing, decrease the risk of human errors, and free up accountants' time to concentrate on more strategic and value-added activities. In fact, AI adoption in the accounting market is predicted to grow by 45% by 2028.

Leading by example

A testament to the growing importance of GAI for optimizing accounting practices, PwC is pouring $1 billion into its U.S. operations over the next three years, working with Microsoft and OpenAI (ChatGPT) to automate aspects of its tax, audit and consulting services. Similarly, EY is investing $1 billion in a next-generation assurance technology platform focused on AI, data access capabilities and advanced analytics.

KPMG also has its finger on the pulse of the rapidly evolving AI landscape, recently expanding its relationship with Microsoft — including a multibillion-dollar commitment in Microsoft 365 Copilot and Azure OpenAI Service — to optimize the firm's tax, audit and advisory services. 

Meanwhile, Deloitte dove into the AI pool headfirst with the Deloitte AI Institute, focused on leveraging GAI to help clients "accelerate the pace of business innovation" across various disciplines. In the accounting arena, Deloitte AI Robot is an example of the company's AI-powered audit-focused tools, helping auditors automate and accelerate tasks — such as financial data extraction, working paper generation, and reviewing and analyzing documents — to dramatically reduce the labor and time costs typically associated with these activities. 

Unlocking the potential of generative AI

Accounting firms of all sizes and specialties are dipping a toe into the GAI pool, leveraging the power of machine learning (ML) and large language models (LLMs) like Generative Pre-Trained Transformer (GPT)—the LLM that powers the popular ChatGPT tool—to transform workflows across the practice. From audit, compliance, and reporting to forecasting, client experience, and business development, use cases include: 

  • Coding accounting entries and improving accuracy of rules-based approaches;
  • Improving fraud detection through more sophisticated ML models of "normal" activities and better prediction of fraudulent activities;
  • Forecasting revenue using ML-based predictive models;
  • Improving access to, and analysis of, unstructured data (e.g., contracts, emails) through deep learning models;
  • Deploying AI-powered chatbots to handle customer support enquiries during tax season;
  • Enabling auditors to analyze massive datasets to quickly identify patterns and anomalies;
  • Training employees on cybersecurity threats by providing real-time simulations of cyberattacks; 
  • Rapidly analyzing data from large volumes of financial documents to inform decision-making;
  • Automating the creation of financial reports (e.g., income statements, balance sheets); and,
  • Simplifying content management and optimizing the pursuit process to increase client engagement rates.

AI-powered pursuit management

Whether a Big Four firm or a small independent accountancy practice, an optimized pursuit process is foundational to profitability. The pursuit workflow should be a well-oiled machine that drives sustainable, organic growth: expanding the number of new clients, retaining existing clients, increasing win rates, improving the success rate of winning back lost clients, and increasing average order value.

Savvy accounting firms have recognized the potential of AI-powered proposal management software to improve the efficiency and efficacy of the pursuit process. GPT optimizes a firm's ability to research, write and analyze content — whether from the public domain or a closed source, such as a content library — to create higher-quality, personalized pursuit documents (e.g., proposals, RFP responses) that translate to more client wins and revenue growth. 

LLMs like GPT are unique because they are trained with vast amounts of data, using deep learning algorithms and natural language processing (NLP). As a result, they become highly skilled at generating coherent and logical sentences. Applied to pursuit management, GPT will be able to automatically draft answers to RFP questions and seamlessly insert them into documents; answers can be sourced from an approved Q&A list, broader firm content, other datasets or past RFP responses. 

Accounting firms will be able to use GAI to analyze and optimize proposals for increased engagement, identifying key themes and topics likely to resonate with clients, based on data analysis of past proposals and client interactions. Similarly, proposal management software that leverages ML and NLP can recognize different ways the same question may be asked in multiple RFPs, suggesting content with a higher win rate to create an optimized response every time.

With the injection of GAI into proposal automation solutions, business development teams will be able to realize gains in content creation, contract review and due diligence. In addition, by analyzing past performance data, GAI could help predict future trends and enable firms to make informed decisions about which clients to pursue and industries to target moving forward.

Risk and reward: A balancing act

While GAI may mean that firms benefit from increased operational efficiency and profitability, the nature of the accounting profession — most notably the sensitivity of financial data — creates potential risks and challenges, including data security and privacy concerns; ethical considerations of transparency, accountability and compliance; and data availability and quality.

From the outset, accounting firms must address the elephant in the room and acknowledge the inherent risk of errors due to poor data quality. Unfortunately, GAI is only as good as the data that "trains" it, which opens the door to inaccuracies and outdated content if firms are not using data from verified closed datasets or up-to-date content libraries, or if they skip a human review process.

On the business development front, firms should view GAI tools as junior researchers and writers when creating pursuit documents, making sure to thoroughly review, edit and supplement any results or draft language. Similarly, auditors, for example, should not rely solely on AI technology to evaluate financial records and should always make the final judgment as part of a multilevel review process.

While accounting firms must be cognizant of the risks and challenges of GAI — and implement best practices to vet content, ensure data security and safeguard client privacy — AI-powered technologies are transforming the roles of accountants, freeing them from time-consuming, mundane tasks and empowering them to provide strategic insights and guidance. Plus, by increasing efficiency, improving accuracy and optimizing pursuit management, GAI tools can unlock sustainable growth, driving top- and bottom-line benefits through increased client business and reduced costs.

For reprint and licensing requests for this article, click here.
Technology Artificial intelligence Machine learning Automation
MORE FROM ACCOUNTING TODAY