AI in the professional services sector

Francesca Lukes at Wanstor examines the road ahead for AI in the professions

 

The increasing integration of automation and AI in the professional services sector marks a significant shift from longstanding traditional manual processes to a more efficient, technology-centric approach.

 

This transformation is spearheaded by a range of innovations, from AI-powered analytics and predictive insights to personalised client engagement, among many others.

 

At a high level, for instance, organisations across the sector are embracing AI-driven analytics to extract actionable insights from data. This shift not only streamlines data processing but also aids in strategic planning and informed decision-making, significantly impacting business growth and development strategies. This has the potential to be applied to the way professional services firms are run as well as to the services and advice they provide to clients.

 

In addition, the use of AI for predictive analysis is transforming the ability of professional services firms to anticipate client needs and market trends. Moreover, armed with the ability to proactively identify potential risks and opportunities has the potential to deliver substantial competitive advantage, ensuring firms remain agile and responsive to market dynamics.

 

AI also supports the growing need for more effective, personalised services and communication. For instance, automation and AI enable bespoke client interactions, enhancing relationship building and client satisfaction. This goes beyond mere service customisation because it draws on a deep understanding of client preferences and needs, leading to more effective and engaging interactions. 

 

The race to adopt AI

According to the FT, law firms have been “racing to adopt artificial intelligence” to automate the process of drawing up contracts, assisting in due diligence processes and drafting legal opinions. This not only streamlines the contract creation process but also ensures accuracy and consistency in legal documents.

 

Intriguing as these developments are, they represent the tip of the AI and analytics iceberg for law firms, with the technologies being more broadly applied to various processes, including e-discovery, legal research and document management, among many other roles and requirements. As the sector increases investment in AI and analytics solutions, this list is certain to grow.

 

Indeed, the FT analysis goes on to suggest that Magic Circle law firms are already experimenting with AI platforms to suggest legal opinions – a trend that gives a strong indication as to the ultimate direction of travel the profession is taking.

 

Elsewhere, recent industry research revealed that nearly three-quarters of tax professionals acknowledged that AI can be used for tax, accounting or audit work. Interestingly, however, only half thought it should be used in a professional tax setting. Despite this contradiction among professionals, the Big 4 accounting firms are investing in AI tools for a range of use cases, from predictive analytics and auditing to tax compliance and delivering client insights.

 

What every professional services organisation has in common is that AI is likely to play a huge role in enhancing productivity by automating routine tasks, allowing experienced experts to focus more on client-specific needs and strategic aspects across their areas of practice.

 

Data readiness: the foundation for AI success

Given the significant levels of emphasis that professional services firms are placing on AI, what are the barriers to success they face? For many, the most likely stumbling block is data readiness, or more specifically, the absence of it.

 

For AI systems to function effectively, they must be powered by data which is of high quality, well organised, accurate, subject to the correct levels of governance and, of course, secure. The whole exercise hinges on the availability of relevant data to which AI algorithms will be applied. Whether it’s case files, financial documents or client interactions, without sufficient data, the AI’s learning process is impeded, leading to unreliable predictions and analysis.

 

Next, the accuracy of the underlying data directly impacts the credibility of AI outputs. Inaccurate, outdated or biased data can skew findings, resulting in misinformed decisions. Meticulously ensuring data is error-free and unbiased is essential for AI credibility and effectiveness.

 

And crucially, data-readiness also means that whatever information is provided to AI systems must adhere to compliance regulations and data protection laws. It should go without saying that maintaining confidentiality and prioritising cyber-security upholds client trust while mitigating legal and reputational risks.

 

This also includes the importance of carefully defined access permissions and information rights management to ensure access to data complies with both internal and external rules.

 

Together, these considerations can help ensure that data governance and compliance provide the ethical foundation upon which effective AI systems are built.

 

When high-quality, accurate, organised data is combined with responsible data practices, organisations can leverage the full potential of AI to drive better outcomes. Clearly, there is a great deal more to come, but AI seems certain to play a transformational role in shaping the professional service sector in the years ahead.

 

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Francesca Lukes is CEO of Wanstor

 

Main image courtesy of iStockPhoto.com