Introducing the Greater Manchester AI Foundry: Business Acumen That Meets Technological Prowess.

Author Sean Brophy, Enterprise Fellow, Manchester Metropolitan University
February 2021

AI presents stark visions of the future, visions which can be grouped into two now-familiar over-simplifications: a utopian version where the mundane tasks of work and life are delegated to machines and a dystopian version where automation heralds a new age of mass unemployment and human misery.  

These tropes are caricatures, of course, but the promise and the perils of AI are very real. It was the late Stephen Hawking who famously said that “…AI will be either the best, or the worst thing, ever to happen to humanity.” And as fascinating as these ruminations may be, The Greater Manchester AI Foundry is focused on much more practical goals: supporting the development of commercially viable products, services, and systems using AI.

Essentially, this is what Brynjolfsson and Mcafee (2017) call ‘the business of artificial intelligence’. In this blog post, I will sketch out a few simple propositions on the business of AI that have informed the design of a series of workshops at Manchester Metropolitan University to train local entrepreneurs and business leaders on the business fundamentals of technology, innovation, and AI.

1. Greater Manchester has a unique place in the history of AI, and the Greater Manchester AI Foundry is part of its future. Alan Turing was an academic at the Victoria University of Manchester from 1948 until his tragic suicide in 1954. Turing’s short but brilliant career is credited with starting the field of AI, particularly his 1950 article on “Computing Machinery and Intelligence”. Although much of the investment and institutions supporting in AI are concentrated in the fabled “Golden Triangle” in the South of England, Greater Manchester is punching well above its weight on a number of important metrics (The Data City, 2020).
2. The business of AI is growing rapidly, but this growth is unevenly spread across certain sectors, locations, and types of firms. Although large corporates are using AI, SMEs and B2B firms are less likely to use it because they lack the expertise and data to use the technology effectively (Davenport, 2018). In the U.K., PwC (2017) estimates that AI will lead to a 10.3% increase in GDP by 2030, but this growth will not be shared equally across the nations of the UK. One can only speculate as to whether the AI-derived gains will be shared equally across the regions of England or if AI will add to growing calls for ‘levelling up’ the investment and take-up of technologies across the regions.
3. There are different types of AI that can be used to develop new products and services but identifying the most suitable form of AI is often the key to success. Part of the mission of the AI Foundry is developing ‘AI literacy’ amongst the participants by making them conversant in terms like machine learning, neural networks, robotics, expert systems, fuzzy logic, natural language processing, and computer vision. At the AI Foundry, we are interested in developing commercially viable AI products, services and systems that are responsive to the needs of customers and the market.
4. A customer-centric approach should be the starting point for those who are interested in developing AI-enabled products and services. Take the B2B market as an example, a Deloitte study in 2017 found that only 32% of executives were looking to use AI to create new products, but they see more potential for the technology in enhancing the performance of existing products, optimising operations, automating tasks, and making better decisions. (Davenport & Ronanki, 2018) It is incumbent on anyone who seeks to design solutions for the B2B market to understand how AI is being used by the very businesses who will be their future customers. For B2C firms, a customer-centric approach to innovation can take any number of forms, but human-centred design approach as advocated by firms like IDEO and Google offers a promising way forward.
5. Many large companies are investing in infrastructure and processes to manage AI, but the same cannot be said of SMEs. There is an open question as to whether SMEs are developing the effective processes, governance structures, and operating procedures to successfully onboard the technology effectively. At the AI Foundry, we will be discussing a number of these processes and procedures, but we will pay particular attention to the ethics of AI.
6. The transformational potential of AI has yet to be realised. It is still early days in the development of AI for commercial uses, and not all companies, particularly SMEs, have the data that is suited to using AI. Despite this, I am convinced that AI is the most important general-purpose technology since electricity and the internal combustion engine, and the potential of AI to transform everyday life is substantial. Although the speed and direction of this transformation is uncertain, the Greater Manchester AI Foundry will accelerate this transformation among local businesses.
7. The impact of AI on jobs and employment is uncertain, but the nature of work will be fundamentally changed. Writers and researchers on AI speak about the ‘augmentation’ of work by smart machines and people working together, and this is a far more likely scenario than large scale automation where machines replace human workers. Employers, including the beneficiaries of the AI Foundry, ought to be preparing employees to work side work alongside smart machines that add value to the human efforts, whilst also minimising harm to workers, the community, and society.
8. AI raises profound ethical questions, but ethics is the domain of human beings. Ethics is the examination of how human beings ought to behave to other human beings, and in many ways, technology is incidental to ethics. AI does, however, present some unique ethical challenges. Ethical issues arise upstream at the point of data collection; they arise when AI is used for analysis, and ethical issues are present downstream in the application of AI to products, services, and systems. The AI Foundry will be uncompromising in embedding ethical practices at every stage of the project.
9. We need entrepreneurs, innovators, and scientists to ask the right questions and to tackle the right business opportunities. Pablo Picasso once provocatively said that “Computers are useless. They give you only answers”. What is meant by this statement is that correct answers – and the algorithms that arrive at those answers – are only as good as the questions they’re meant to answer. The task of those engaged in the work of innovation is to ask the right questions and solve the right problems for the betterment of all.

On the 27th of January 2021, the Greater Manchester AI Foundry welcomed our first cohort of 25 business leaders. Although we initially envisaged a series of face-to-face workshops, COVID has required us to deliver our workshops online via Zoom. I commend those leaders and entrepreneurs who have taken this important step in their personal development while also starting the process of developing an AI-enabled growth strategy for their businesses.  The goal of the Greater Manchester AI Foundry is to drive growth and productivity not only for the businesses involved, but to pass this growth onto Greater Manchester, the North West of England, and the UK economy.

So, stay tuned and watch this space. We will be publishing a series of blog posts that coincide with the main themes of the Greater Manchester AI Foundry: business acumen that meets technological prowess.

About the author:

Dr Sean Brophy is the Project Manager of the Greater Manchester AI Foundry, where he oversees the project across the four partner universities. He is also an Enterprise Fellow at Manchester Metropolitan University, and his research interests include the role of technology and human capital in economic development. He spent a decade at the Wharton School of the University of Pennsylvania where he developed learning programmes for leading firms Google, Twitter, Accenture, and KPMG. He has conducted research at Oxford’s Department of Education on the role of commercial activities at UK and US business schools.

References:

Brynjolfsson, E., & Mcafee, A. (2017). The business of artificial intelligence. Harvard Business Review, 7, 3–11.

Davenport, T. H. (2018). From analytics to artificial intelligence. Journal of Business Analytics, 1(2), 73–80. https://doi.org/10.1080/2573234X.2018.1543535

Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.

PwC. (2017). The economic impact of artificial intelligence on the UK economy. https://www.pwc.co.uk/economic-services/assets/ai-uk-report-v2.pdf

The Data City. (2020). UK’s Top Digital Tech Cities. https://www.thedatacity.com/uks-digital-tech-cities-report-2020/

Turing, A. (1950). Computing machinery and intelligence. Mind, 59(236), 433.