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The future of AI in professional services

In our final blog based on the AI for Services report by KTN, we will be exploring what the future of AI and data technologies looks like in the UK services sector. There is no one product or technology that has taken the industry by storm. But entrepreneurs are finding multiple fissures where new technology has the potential to change how professional services are delivered.

When discussing the future outlook for AI and data technologies in the UK services sector, it is key to look at the drivers and the barriers that affect this change. These may either facilitate and drive innovation or bring it to a halt.

The drivers include:

Value proposition: One of the drivers is that implementation of AI tools increases efficiency and productivity across a range of workplaces - particularly by enabling the improvement of processes such as fraud detection, data analysis, document review and customer satisfaction (Deloitte, 2017; ICAEW, 2018; The Law Society, 2019). As such, a reduction in operating costs certainly incentivizes firms to adopt AI-based systems. This will only increase with time.

Competitive pressure: Another enabler relates to competitive pressures. Indeed, a combination between a change in customer expectations and the steady emergence of new technologies creates a flourishing place for new competitors. For example, client pressure for better quality products and better customer service has been one of the most significant drivers for the adoption of new technologies in the LegalTech sector (The Law Society, 2019). The same may be said for the InsurTech sector, where change has been incited by technological advances in other industries. For example, the ability to track a package delivery has translated into customers wondering why they are not able to do the same for their insurance claims (Sachdev & Tottman, 2018).

Ecosystem: The next driver for the widespread adoption of AI and data technologies is found in the strength of the UK’s AI and data ecosystem. In particular, the foundation of a strong research base and a thriving industry landscape means the sector does a remarkable job of fostering innovation. Nonetheless, the report’s findings suggest that the biggest driver still remains to be the benefits that AI and data bring to the sector, with 96% of survey correspondents agreeing it is the key driver for future innovation.

But there are barriers.

Talent: On the other hand, according to 83% of correspondents, one of the large barriers relates to the accessibility to highly skilled staff who are capable of maximizing the use of implemented data systems. In this regard, it is important to consider the barrier not only relates to the employment of staff in this area, but also to the ability to incorporate these talents in a way that is valuable and sustainable. In other words, skilled staff must be complemented by IT and data infrastructure (Mateos-Garcia, 2019). There is a trend where the busy schedule of junior lawyers inhibits training, and a cultural reluctance among senior practitioners challenges proficiency (The Law Society, 2019). Law schools are still providing the market with a 20th century legal workforce when 21st-century lawyers are needed.

Capital: The next present barrier is a lack/lag in funding. According to 38% of respondents, this is due to an overall lack of money to invest in technological adoption (Thomas-Bryant, 2019). Lags in investment increase relative to the rate of technological advances. While investment in the LegalTech sector is likely to increase (The Law Society, 2019), this has to be justified by the development of worthy products.

Access to data: Lastly, access to data in incumbent firms is challenging, mostly, due to difficulties in identifying customer appetite. But it can also manifest due to a limited understanding of AI and data technologies, as agreed to by 82% of respondents. This may be linked to another barrier related to liability concerns as there is a fear of an open gap for inaccuracy in the legal sector - particularly, in terms of conclusions made by AI data systems.

Overall, the report highlights a large majority of stakeholders believe there will be an increase in availability of AI and data technologies for use, driven by more granular product categories and targeted pricing (Everett et al., 2019; McKinsey, 2018).

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