Creating Future Services with AI and Data
Posted on 21/08/2019
The AI for Services network is a new initiative bringing together service professionals, researchers, technologists and entrepreneurs who are developing AI and new data-powered solutions in the accountancy, legal, insurance and financial sectors. The network is part of a major programme being undertaken as a response to the Industrial Strategy Next Generation Services Challenge which is driving a step change in the UK’s research and development in AI and data technologies.
As the network strengthens in the coming months this blog will explore key issues arising in this space and provide case studies, updates on network events and news on areas where innovation is needed and where it is happening.
The transformational effect of AI and data applications is starting to be felt within the UK’s world-class, high value services sector which, until recently, did not have a reputation for investing in R&D. Now terms such as fintech, lawtech and insurtech are becoming more familiar as new and established companies respond to customer demand, intense competition and globalisation. These professions are inherently data-rich, investing in AI-based solutions to drive significant benefits, reduce costs, acquire and support clients and create valuable, leading edge services.
Change is happening but the UK must do more in order to retain a competitive edge. Greater focus on R&D, innovation and collaboration is needed – a point highlighted in the recent white paper, AI in Corporate Advisory from the ICAEW which recommended that:
“In a global AI market dominated by the US and China, countries such as the UK will need to increase public and private investment sharply and may well need to create new forums for international R&D collaboration in economic sectors such as professional services.”
To date AI and Data-focused R&D within the professional service sector has tended to be localised. Larger corporations often have established R&D divisions driving internal innovation based on their specific internal needs. Smaller firms, who cannot justify such investment or hire the required talent, find it harder to take advantage of new technologies and fall back on the tools provided by global giants such as Microsoft, Google or Amazon who are jostling to control the AI space. Meanwhile the UK’s growing talent pool of AI and Data Analytics entrepreneurs (who may hold the keys to valuable new solutions), social and academic research teams are eager to collaborate, solve problems and help unlock opportunities.
The AI for Services network seeks to bring interested parties together to learn from each other and from the R&D funded projects, to share insights, identify solutions and strengthen cross-sector connections. New members are welcomed from accountancy, legal, insurance and financial services, from AI and data analytics start-ups or SMEs and also from research institutions focused on AI, Data or Social and Behavioural Sciences. Professional bodies such as the ICAEW, the Law Society, and the British Association of Insurers are also invited to become important channels for disseminating knowledge and information and assist in forming a powerful network of networks.
Members of the community will be given exclusive access to resources, invitations to innovation events and insights from experts. The network newsletter will also deliver the latest industry news and funding opportunities straight to your inbox. To get ahead of the curve and join the network you can register here for free.
At a recent Innovate event held for those involved in the R&D funded projects participants discussed some of the common challenges that they face, and we plan to cover certain topics in more detail, including:
Accessing Data Sets
Service companies are rightly sensitive about data management, control and sharing, while start-ups often struggle to access the right size and quality of data sets needed to develop machine-learning algorithms. This is an issue affecting all sectors and which can stifle new business models, an issue covered in last year’s ODI paper The Role of Data in AI Business Models which pointed out that:
“Those with the most data are often able to train the best AI systems and those with the best AI systems are often able to collect the most data.”
Enabling access is an issue that Innovate UK/UKRI intends to address by investing up to £3.5 million to develop responsible data access or sharing methods within accountancy, insurance and legal services. Individuals are invited to apply to take part in a 3-day residential Innovation Lab to be held on the 14th-16th October. During the lab, the selected participants will work together to develop collaborative proposals for research and innovation projects. After the Innovation Lab, the project consortia will have 4 weeks to finalise their proposals before submitting them for assessment. “This is a fantastic opportunity for the sector to come together and find mutually beneficial ways to unlock data” says Astrid Ayel – Next Generation Services Challenge Lead at the KTN. You can read more about the competition and apply to take part in the Innovation Lab here.
Encouraging responsible use of AI
A key objective for the network will be the fostering and dissemination of ethical best practice. As AI techniques are more widely adopted there will be a need for more transparency in how the decision-making is achieved or how it can be augmented with professional expertise.
The AI for Corporate Advisory explores this need for the accountancy sector:
“Emerging technologies present significant opportunities and challenges for the accountancy profession, such as those relating to the future role of professional judgement, which could become even more, rather than less, important in the Age of AI.”
Finding value in collaboration
Collaboration between professional service companies and AI technologists in start-ups and academia is vital if the UK is to stay ahead of the game, but there is evidence that engagement is hard. Collaboration will foster broader innovation in areas where the business case might be too weak for a single company to undertake the required R&D. There may also be significant benefits to sharing data in order to build better cross-sector models, for example in the area of due diligence. AI is often seen as a threat to traditional jobs, particularly administrative ones, but there may be opportunities for collaboration to define new employment roles which complement AI development. As the AI for Corporate Advisory paper suggests:
“Collaboration between professional services firms and technology developers in AI and big data should be stepped up. However, the role of professional expertise and judgement will remain essential for public and business confidence, and will not simply be ‘disintermediated’ by technology platforms.”
In the coming weeks we will be delving more deeply into these topics and highlighting useful case studies and developments.
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