There can be no doubt. These are testing times for UK industry. Faced by great political and economic uncertainty at home and abroad, an intensifying climate change agenda and ever more rapid digital disruption, many of the nation’s businesses are understandably focused on surviving as much as thriving. Yet amidst the tumult, a chink of light too. Despite the noise and distractions externally, organisations across sectors are increasingly recognising the value of AI – both by positively impacting their own business and by helping the UK compete on the world stage.
And they are acting upon it too. More than half of UK organisations (56%) are now using AI to some degree, including a rise of 11% in machine learning, a 9% rise in automation, a 7% rise in voice recognition and a 6% rise in smart assistants compared to this time last year. (See Figure 2.)
Similarly, nearly half (44%) of leaders believe AI is a skill that will help secure their future prospects in the UK. And while last year 11% of leaders said they had an AI strategy in place, this has more than doubled to 24% today.
There is also a clear and growing appetite for innovation. Of the UK business leaders we spoke to in 2018, just 14% expressed an ambition to be at the forefront of pioneering new AI technologies and applications.
Fast forward to today and this has grown to 38%, underlining not just their openness to change but a burgeoning understanding that, when it comes to AI, keeping pace with the pack is not necessarily enough. True success comes from getting out in front.
Put another way, we ask how organisations can ensure they are taking the right approach to AI. One that unlocks the power of the technology to generate and expedite growth. That prevents over-analysis and a fear of ‘what if?’ – both of which can paralyse progress before it begins. And that helps employees at all levels develop the skills to thrive in an augmented workplace.
Nearly half (44%) of leaders believe AI is a skill that will help secure their future prospects
Perhaps most critically of all, we consider the importance of establishing a clear code of ethics, commitments, and values when it comes to AI’s development and use. Why? Because only then can we build trust in the technology (both inside and outside the workplace), allay concerns about data security, and ensure that the positive impact of AI is felt as keenly from a social perspective as it is from an economic one. Not just now, but for generations to come.
As Robbie Stamp, Chief Executive Officer of management consultancy firm BIOSS, puts it: “There is an element of organisations looking over their shoulders and fearing they are missing out on something that will provide a massive competitive advantage – that if they are not engaged in AI, they are going to lose.”
Figure 2. AI technologies being used by UK organisations – 2018 vs. 2019
A huge opportunity
These progressive intentions are well-placed. According to figures from TechJury, the global AI market is expected to be worth almost $60 billion by 2025, an increase of $58.6 billion from 2016.2 Start-up funding and corporate investment in AI are also at an all-time high, while the latest forecasts from McKinsey Global suggest the technology will add $13 trillion to global economic activity by 2030.3
$13 trillion to global economic activity by 2030.
Closer to home, the 2018 House of Lords report, AI in the UK: ready, willing and able?, continues to have a powerful influence on policymakers. Indeed, this year alone saw the UK government make a £115 million commitment to support AI training at graduate university level.4
Organisations who act now to embed AI across their business therefore have a huge and compelling opportunity to transform themselves for an AI-led future. To get out in front and reap the financial, operational and cultural rewards for many years to come.
From openness to action
Yet, while being open to an AI-led future is one thing, actually using the technology effectively is another. As the House of Lords’ report author, Lord Timothy Clement-Jones, points out: “The discourse about AI has accelerated enormously, as has the pace of adoption.
But it is really important people ensure they are creating solutions that actually benefit workers and organisations rather than simply adopting it for its own sake.”
In other words, although these steps forward are positive, there is much still to be done to truly unlock AI’s transformative potential at both an organisational and national level.
Firstly, and as Clement-Jones alludes to, a large number of organisations struggle with balancing their desire to introduce AI quickly and the need to establish a clear roadmap for where and how they do it. Consequently many miss the vital step of actually identifying the precise business problem(s) AI is best equipped to solve and, thus, fail to experience the true value it can deliver.
As Nick Wise, Chief Executive Officer of OceanMind, a not-for-profit using insights and intelligence to protect the world’s fisheries, puts it: “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.”
Figure 3. The difficult journey
The traditional S-curve, used in previous reports, shows how organisations can avoid any potential slow-down in their digital transformation journey by focusing on the next step before the previous one is complete. Here we combine the S-curve model with Chasm Theory, which represents the journey from experimenting with AI to scaling it. The key to crossing this chasm is to power technical improvements through incremental, measurable, predictable progress and to support these with the social and cultural changes required to operationalise AI at an organisation-wide level.
Mind the chasm
There is also a clear and widening gap between organisations that are deploying AI solutions at scale and those that are either caught in the exploration phase or, more worryingly, not yet using it regularly at all.
Put another way: success tends to breed success, with businesses already feeling the benefits of AI more likely to learn from that experience to increase the speed and effectiveness of adoption elsewhere. Meanwhile, as we see in Figure 3, those who spend too long testing the use of AI in local silos or departmental pockets are more likely to fall into what we refer to as the ‘Adoption Chasm’ – the gap between experimentation and full implementation. We explore the process of bridging this chasm in more detail in the next chapter.
As Microsoft UK Chief Operating Officer, Clare Barclay, explains: “Organisations that are new to AI are not experiencing the same speed of progress as those that are already on the journey.”
This disparity is not limited to companies operating in the same industry either. As we see during the Industry Spotlight chapter of this report, there are significant differences in how different sectors across the UK are harnessing the power of AI.
With progress comes complexity
Yet even those organisations who have successfully integrated AI into their value chain can ill-afford to rest on their laurels. Why? Because with advancement comes complexity. Alongside the evident benefits AI brings, so do a raft of new challenges and questions that, in many cases, businesses seem unable and/or unready to answer.
For example, just 34% of UK leaders and 20% of employees say they know how to evaluate the business benefits of their organisation’s AI investments, begging the question of how they can determine if the technology is delivering what they actually need it to – not to mention how they know what to replicate or improve as the use cases expand.
Similarly, nearly two-thirds of leaders (63%) admit they do not understand how the AI they use arrives at its conclusions – a figure that rises to 74% among employees – while more than half of leaders (57%) and nearly three-quarters of employees (73%) confess they do not know what to do when AI is following the wrong course of action.
The impact of this knowledge gap from both a competency and ethical perspective is explored further in Chapters 3 and 4. Suffice to say though, if an organisation’s people are unaware of how or why the technology is working, the chances of them ensuring it is correctly, effectively and responsibly deployed are naturally reduced.
The next step
Clearly, then, for organisations across sectors, progress on their journey of AIled digital transformation remains far from straightforward. Yet it is – or at least must be for those looking to secure competitive advantage – inevitable.
Their task now is to not just introduce AI, but to scale it. To unlock not just its business value, but its cultural and societal benefits too. To move from experimentation to implementation and become not just a business that employs AI solutions, but a truly AI-enabled organisation.
In the remainder of this report, we examine how they do it, considering the following three core pillars in particular:
1 From experimentation to implementation: Scaling AI across the whole organisation, not just in local or departmental pockets.
2 Creating a culture of participation: Ensuring staff at all levels feel empowered to re-skill and actively contribute to the implementation of AI technologies.
3 Making AI work for everyone: Establishing a clear set of developmental standards and operating principles to ensure the technology is not biased, deployed ethically and in a way that actively promotes diversity and inclusion.
We also lay out some practical steps for how every organisation can move forward on its own unique AI journey. Yes, there may be a challenging road ahead. But for those who get it right, unprecedented opportunity awaits.
As more organisations recognise the value of AI and seek to adopt it across their organisation, they have a chance to not only outperform their own competitors but to help the UK take a leadership position in AI on the global stage.
But is the country ready to do so? According to the nation’s business leaders, possibly not, with just over a quarter (26%) saying they believe the UK has the socio-economic structures in place to become a world leader in AI.
“The UK has a proud history of AI research and development but when it comes to implementation, we are starting to lag behind the US and China,” says Microsoft UK Chief Operating Officer, Clare Barclay. “Political and economic uncertainty can understandably breed caution but in today’s climate, it actually needs to be the catalyst for greater, faster change. It is time for UK organisations across sectors to focus on innovation and in leading the world on AI.”