AI Helping Keep UK firms Afloat

This is indisputably a testing time for UK firms with domestic political uncertainty with Brexit, international trade wars and increasing environmental pressure. However, despite all these obstacles, British firms are still competing efficiently on the world stage partly due to a greater focus on AI. Here are a few surprising statistics enforcing this gradual shift towards AI:

  • 57% of Uk firms are now using AI

  • including a 12% rise in the use of machine learning and an 8% rise in automation

  • 73% of banks and other financial institutions are using AI.

Graphical Representation of the Surge in UK investment in AI, Source: Tech Nation

Graphical Representation of the Surge in UK investment in AI, Source: Tech Nation


A possible cause of AI flourishing in the UK may be due to low government intervention to shape its direction. This approach directly contrasts with, for example, the German government which has directed AI to enhance its manufacturing process, for example using ‘smart goods’ to improve oil supply chains. By contrast, low UK state influence has created an innovative and flexible grassroots start-up culture. This culture means that it is well placed to optimise the opportunities created by an unpredictable AI environment.

Analysing the impact AI has had in the UK: a research study found that firms implementing AI were over 12% more productively efficient than those without AI. The evident success of AI has fuelled a growing appetite for more innovation, with 39% of UK business leaders stating being at the forefront of pioneering new AI technologies as one of their key aims, up from 14% last year. These strides in AI in the UK mirror a global change as a case study from TechJury predicted the global AI market to be $61 billion by 2025, up from $2.1 billion in 2016.

However, AI has not just improved firms’ productive efficiencies but also helped them simultaneously maximise their other secondary objectives, such as environmental impact. A notable example is how smart algorithms have made oil supply chains much smoother by making the transportation of oil much smoother; oil is transported through underwater pipes at low sea temperatures, but many factors including low temperatures, mean the pipes often get blocked. Smart algorithms can much more accurately monitor and predict how these external factors can lead to pipe blockage, allowing automated responses to release chemicals into the oil to unblock the pipe. Rather than much less effective monitoring of the tubes and very limited predicting coupled with a slower manual response of releasing chemicals, that would be the case without smart algorithms. Therefore significantly improving the fluidity of the oil supply chain thus, improving the productive efficiency and therefore reducing greenhouse gas emissions.

The pivotal impact of AI to the UK’s economy has even influenced policymaking, as highlighted by the findings in the 2018 House of Lords report: ‘AI in the UK: ready, willing and able?’ Furthermore, in this year alone, the UK government made a £121 million pledge to assist AI training at the graduate university level.

However, the 2018 House of Lords report also identified some key concerns with AI in the UK economy. Notably, how firms focus on the rapid implementation of AI without a clear roadmap of how and where to use it. Therefore, many firms do not identify the parts of their business model that can be most productively improved by AI, thus limiting its impact.

You should know your problem first and realise AI can be a solution. If you don’t understand what you are trying to solve, you are carrying a hammer looking for a nail and AI is going to be of no real use to you
— Nick Wise, Chief Executive Officer of OceanMind

Yet even those firms who have integrated AI into their supply chains, often fail in combining AI with their existing labor. This hypothesis is empirically verified by a study that found just 36% of UK leaders and 20% of employees knew how to analyse the financial benefits of their organisation’s AI investment. Similarly, 62% of leaders did not know the process which the AI employed; this statistic rises to an alarming 78% for employees. This raises the question as to whether UK firms have sufficient human capital to mirror the rapid advancements in AI.

The report also identified another key concern of AI regarding data monopolies, as data storing firms benefit from natural economies of scale, creating barriers to entry for new firms. This means that tech giants dominate the market. They are even metaphorically described as ‘data moats’ to signify their unassailable commercial positions.

The dominance of technology giants is a vexing problem
— UK's Information Commissioner

However, in response to this, the UK’s Competition and Markets Authority argued that data is non-rivalrous; customers can give their data to many different companies simultaneously, which would undermine a possible monopoly. However, if there is a data monopoly, this could have severe repercussions as monopolies tend to restrict market output (here data provision) to maximise abnormal profits. This would seriously impede the development of the UK’s AI sector.

Furthermore, there has also been a widening gap between firms using AI on a large scale with those trapped in the exploration phase. While this creates a positive multiplier effect for some with success fuelling success, those that spend too long on the research stages risk falling into the ‘Adoptive Chasm’ - the gap between experimentation and implementation.

Organisations that are new to AI are not experiencing the same speed of progress as those that are already on the journey
— Clare Barclay, Microsoft UK Chief Operating Officer

Therefore to conclude, AI is crucial for UK firms to maintain their international competitiveness especially in the service sector as developing countries such as Nigeria have rapid expansions in their tertiary sector fuelled by significant strides in improving human capital. However, to exploit the full advantages of AI, UK firms will need to introduce and scale AI which they will need to integrate coherently with the rest of their business model. In tandem with the UK government monitoring and regulating key associated markets, for example data markets to prevent monopolies that restrict the growth of AI in the UK.

FinanceArun Singh Dhillon