ChatGPT, chatbots and other AI tools are now familiar to many people in daily life.
But what may not be apparent is that AI actually features in a vast range of tools across infrastructure, analytics, and enterprise applications. And to reap the benefits of automating more and more complex processes, accounting, tax, and finance practices must invest to keep up-to-date with AI and machine learning.
In the past few years we’ve seen systems and tools transform at a rapid pace. In fact, there have been over 2000 distinct applications of AI principles that impact everyday business operations.
In accounting, there’s been greater focus on predictive analytics and real time reporting. The market share of AI tools reached $1.15 billion in 2023 and is expected to grow further to reach $12.5 billion by 2031 — that’s growth at an average compound annual rate of 34.51%. Despite this, only 25% of accountancy firms surveyed were actively investing in AI training for their teams.
Use cases
These new systems and tools are commonly leveraged to make improvements in four main areas: communications, task automation, research, and talent acquisition. The specific use cases depend on the service line. For example, in financial consulting they are typically used to provide more specific and targeted reporting. In audit, by contrast, tools are used to evaluate much greater volumes of documentation than manual audits.
Across service lines, these tools can take the form of chatbots, which can assist with client queries using natural language processing, and advanced fraud detection during onboarding through improved data analysis. Beyond this, tools can be used for organisational functions such as firm-wide sustainability reporting and environmental impact analysis to better plan, meet, and measure CSG goals.
Key concerns and pitfalls
Upfront costs — as with all significant organisational change, there are upfront costs involved for training and onboarding systems.
Quality control — as AI and machine-learning tools become more closely involved in ‘direct’ client work, quality control will be more important than is the case for support-based and organisational software. As such, all AI-processed work should be thoroughly checked, with all high-level decisions made by an informed person.
Transparency — use of these tools raises questions as to how we maintain trust and transparency with clients and stakeholders. While there’s a generally-accepted principle that AI tools should be used in an open and honest way, most practitioners would agree that clients should be aware if a considerable amount of a paid service was AI-driven.
Underestimating AI involvement — when it comes to quoting fees, it’s likely many practices would prefer to underestimate how much AI will be involved in the process. This could have serious implications when you consider the risks inherent in protecting the privacy and security of sensitive financial data. As these tools become more prevalent in the industry and algorithmic bias is better understood, it’s likely we’ll see the introduction of clear, generally-accepted guidelines for use – including regular audits and reviews in accounting firms – to prevent these issues as far as we possibly can.
AI chatbot replacement fear — another common concern among accounting professionals is that they may be replaced by AI chatbots. But given AI cannot replicate all aspects of human intelligence, this is currently thought to be unlikely. A future model is likely to consist of AI tools to provide reliable data, reports and analysis, alongside human decision-making based on learned experience and judgement.
While many practices are confident AI could take over more of the mundane processes in accounting and finance, there is a fear that as this technology develops the ‘human touch’ within service lines could be lost. It’s this human element that’s proven critical to building customer relationships, thinking in strategic terms, and providing a more personalised service.
Potential effect on technical competence — there’s concern that using tools early on in an employee’s career could hamper the development of technical competence in more junior members of staff. Accountants and advisors may also become too reliant on a particular tool or service.
As things currently stand, AI tools cannot replace building and maintaining trusting client relationships. But what’s unclear is how further developments in this area will impact the industry. Over the short term, it’s likely the biggest impact of these tools on the accounting profession will be a greater emphasis on building meaningful connections with customers.
It’s going to be interesting to assess the effects of an AI-driven service on client satisfaction, and whether any client concerns are offset by potential decreases in fees as a result of reduced human labour.
Author: Will Shiner, R&D Tax Senior Associate
