School of Business academic shares his passion for knowledge exchange and thoughts on AI future

A University of Leicester School of Business academic is highlighting the importance of enterprise and knowledge exchange between industry, policymakers and academia.

With increasing demands for multidisciplinary teams to address societal challenges, Dr William Darler focuses his efforts on translating academic research into tangible real-world impacts.

A Lecturer in Applied Analytics and Digital Economy, he has led approximately £10 million worth of projects during his six years at the University. Many of these have focused on the use of AI to impact business.

Here Dr Darler shares his passion for knowledge exchange, his thoughts on the impact of AI on businesses and innovation, and suggestions about future developments.

Tell us a bit about your background

I have a varied background with experience in engineering, entrepreneurship, data science and marketing.

I studied engineering for my undergraduate degree at the University of Nottingham, where I was offered a research fellowship at the Business School. During this European-funded project I researched experiential service design and staging customer experiences across different creative industries. I enjoyed meeting a range of business leaders across the cultural sector and investigating the creative ways in which they could provide unique, memorable experiences to their customers. I stayed at Nottingham for my PhD where I used data science techniques to analyse changes in consumer behaviour at national retailers.

Following my PhD, I joined the University of Leicester School of Business (ULSB) as a Lecturer and have been here now for six years. Aside from lecturing, I spend my time driving the enterprise strategy for the College of Social Sciences, Arts and Humanities, engaging with businesses, training organisations on the Government-funded Help to Grow Management programme, coaching executives, and leading various UK and EU-funded projects.

Can you give an overview of your area of research?

My background is in data science and the digital economy, using AI and data analysis to understand changes in human and business behaviour across a variety of different industries. I have led approximately £10 million worth of projects over the past five years, including the creation of tools to optimise match attendance for sports clubs, dashboards to analyse customer behaviour at cultural institutions, and the development of fintech software to reduce invoice payment times. Currently, I am working on an Innovate UK-funded project in collaboration with The Institute of Digital Culture and The Audience Agency aiming to create new AI methods to increase involvement in the cultural industry across communities from diverse backgrounds. 

What are you most excited about at this time in your career?

I am excited to be supporting the University’s performance as a whole and encouraging my fellow academics to engage in knowledge exchange activities, such as applying for research funding and collaborating with external partners. This also extends beyond funding to include consultancy, executive education, and engagement with policymakers, funders, and external organisations across profit and non-profit sectors.

A lot of people tend to get into academia because of their passion for knowledge creation, but I am much more interested in knowledge exchange and how we can apply research to real life and make a positive impact. Across the university sector we have fantastic researchers creating amazing research, but we have fewer people engaging with the external environment, which I think is what makes my contribution unique. There is so much amazing research being carried out which could provide widespread, positive impacts across society but the full potential is not realised. Funders and policy makers are acknowledging this and there are some great initiatives being implemented to accelerate the impact that university research has on people, places and organisations.   

Several projects you are working on at the moment incorporate Artificial Intelligence. What is the impact of AI on innovation?

AI can be used for so many different things and has the huge potential to increase innovation, business growth, and accessibility across various fields. As AI tools become more accessible to regular people (not just technical experts), they have the potential to increase creativity through the generation of ideas for new products and services, facilitate innovation across different business functions, and increase productivity across sectors from arts, entertainment and the environment, to finance, manufacturing and transport.

I anticipate the emergence of new business models and opportunities, akin to the transformative impact of the internet and digital media. There is also the potential for AI to enhance accessibility for individuals with disabilities, enabling greater participation in various activities and employment opportunities. Although AI brings some exciting opportunities for creativity, innovation and productivity, it is also important to consider potential negative impacts of inaccuracy, bias, and discrimination. We are also starting to see some of the negative consequences of AI which provides opportunities for universities, businesses and policymakers to contribute to laws and regulations guiding the use of data and applications of AI software too.

I also think there is the exciting potential for creative people to start implementing their ideas in the real world and to directly influence the external environment. I sometimes get a little fed up with academic think-tanks and would love to see a transition towards action (or perhaps action-tanks). Only by shifting towards action, impact and collaboration, can we enhance the effect our work has on wider society. I am excited by the shift which is currently happening in the academic landscape and it will be really interesting to see how this can benefit the external environment.

How can AI help businesses?

AI can be a great tool for businesses, and the applications range from improving product design, operational decision-making, and increasing efficiency, to enhancing customer service, sales, and marketing too. Analytics has played a huge role across different industries for decades (such as credit-scoring analytics or algorithmic trading in finance; or targeting different customer groups with adverts from retailers) but modern advances in AI have increased the scale and sophistication of the capabilities which are no longer the preserve of large organisations but are accessible to smaller businesses too.

These all showcase the versatility of AI in addressing many tasks and challenges across different industries, and how it can contribute to efficiency, cost reduction and increased accessibility.

How do you see AI evolving in the next decade?

In light of the rapid advancements in AI in the last few years, particularly with the excitement generated around ChatGPT, I would say that the next decade is quite a long timeframe to consider.

A big area of focus will be around responsible AI, its impact on business and society, and the changes in law and Government policy to facilitate this. Explainable AI – which refers to AI which can be interpreted by “regular” non-technical people – will become increasingly important, particularly in light of ongoing legal cases, such as Uber being fined after ‘robo-firing’ employees based on decisions made by AI.

I also see the potential for it to revolutionise business processes, and we can already see that coming in to play with the launch of Microsoft’s chatbot, Copilot, which is designed to increase productivity and reduce human workload.

The impact on jobs will also be interesting. In a report on how AI will impact jobs in the next few years, IBM and Barclays reported that employers have reverted to valuing soft skills (such as problem solving and communication) over technical skills (such as programming) as AI becomes more pervasive. It was found that AI will likely have a greater impact on jobs at the lower end of the hierarchy, so perhaps the focus of AI training will shift to “how to use AI tools” for people in administrative positions, and “how to utilise the potential of AI” for people in managerial positions. On the whole, the report suggests that jobs will be augmented and supplemented by AI, rather than replaced by it.

There is the slightly more worrying aspect where we run the risk of machines communicating with each other and making decisions without human intervention. For instance, we are starting to see AI-generated funding applications and CVs which go on to be judged and filtered by AI as well, which takes out the human element of the process. However, I think we are long way off AI completely taking over, as there is a necessity for human intervention to comply with GDPR regulations.

Ultimately I think AI’s integration into society is exciting in the near term, and it will be interesting to see how it impacts jobs, businesses, and society as a whole – but of course there are many legal, ethical and policy considerations to take into account.

Where do you see AI taking us in the future?

The concept of artificial general intelligence (AGI), which represents a significant advancement beyond narrow AI to achieve human-level thinking by AI, is an interesting one. It would have much broader capabilities beyond specific tasks and a vast array of potential applications.

There are conflicting opinions on when AGI might be realised; some suggest it could happen in the late 2020s while others argue it is still a distant goal. I would argue that we need interdisciplinary collaboration among businesses, policymakers, and academics to address the complex challenges and debates surrounding AGI, and to establish regulations to guide its development and use. It is an exciting prospect, but one that requires a nuanced understanding and analysis to navigate its implications for society.