From development to adoption – Tapping the power of AI

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Artificial intelligence, or AI, is advancing, spreading fast, and will soon permeate every industry, impacting all areas of life.

Not the breathless blurb for a dystopian sci-fi movie or a corporate brochure – this is the positively optimistic pitch of HM government’s National AI Strategy. Published in September 2021, the plan aims to harness the power of artificial intelligence to “increase resilience, productivity, growth and innovation across the private and public sectors” over the next 10 years – confirming the UK’s status as an AI “superpower”.

Britain can claim to be among the world’s leaders in this field. In 2020, the sector – surpassed only in China and the US – attracted almost £3 billion in equity investments. And there is no denying that this deep technology has truly transformative potential. From tackling the toughest challenges in health, such as cancer detection, to forecasting and controlling energy demand and distribution using machine learning – to cite two examples from the strategy.

Intelligence & learning

Artificial intelligence (AI) and machine learning are closely connected. AI is the capability of a computer system to mimic human cognitive functions. Using maths and logic through AI, the computer simulates the reasoning people use to learn from new information, solve problems and make decisions.

Machine learning (ML) is an application of artificial intelligence and how a computer develops its intelligence. It is the process of using mathematical models to help the computer learn without direct instruction. It can then continue learning and improving on its own, based on experience.

Where do businesses adopt AI?

In the UK, 15% of all businesses have adopted at least one AI technology (432,000 companies). Among larger companies, penetration rises to two out of three, according to government research published in January 2022. One in three medium-sized businesses are using AI.

While healthcare is seen as a high-growth area, the sector currently is among those with the lowest AI adoption in the UK, at 11%, whereas IT & telecommunications has the highest, along with legal sector, at more than 29%.

Increasingly artificial intelligence software is embedded in software products, services and applications across industries, as the technology spawns new businesses and markets as well as disrupting existing ones.

These same two industries – IT and healthcare – provide many examples of successful enterprises driven by AI technologies.

Ai in the cybersecurity space

Cybersecurity is a high-growth area due both to burgeoning cybercrime and digitalisation. Artificial intelligence can help companies’ systems navigate this rising sea of data and its hidden dangers. To give two examples:

  • OneTrust developed a platform powered by AI and a robotic engine that manages workflows across privacy, security, data governance, risk, ethics and compliance, and environmental, social and governance. Co-headquartered in Atlanta and London, the fast-growing company is one of the UK’s leading unicorns, with a $5bn-plus valuation.
  • Quantexa uses AI to secure clients’ data and to flag illegal activity through advanced analytics. Working with organisations handling huge datasets – such as banking, e-commerce and the public sector – the company creates analytical models. These uncover data risk, reveal opportunities, and enhance decision-making.

AI makes advancements in healthcare

Healthcare is a fertile ground for AI applications due to its complex problems and vast data generated in multiple areas. These range from disease research and clinical trials to drug performance and patient records. New business models that embody artificial intelligence are tackling these and other challenges:

  • BenevolentAI builds technology combining advanced AI and machine learning to analyse the expanding landscape of biomedical data, helping its scientists to speed up drug discovery and new therapeutic interventions.
  • Huma (previously Medopad) has developed a digital ‘hospital at home’ and decentralised clinical trial platform that uses real-time health data from smartphones to help patients, clinicians, researchers, and healthcare systems manage health records more efficiently.

The UK’s national strategy recognises that AI will become mainstream in much of the economy. But there needs to be action to ensure every sector and region benefits from this transition. Various measures to encourage this diffusion of AI across the economy are set out, with separate strategies promised for health and social care, and defence.

R&D tax credits can tap in on your AI capabilities

At Ayming, we see our clients increasingly tapping AI/ML capabilities, while earning R&D tax credits towards their costs. In some cases, the technology is at the core of their offering; in others, the application may just be a small element of a larger R&D project:

  • A company that supports employee learning has used ML to enhance its AI-powered service platform, adding a cognitive search capability. This contextualises answers in real time, boosting accuracy and efficiency for users.
  • Another client, in the construction industry, explored how AI could help predict the quality of its building product. This was based on measurements of properties of the raw materials going into the production process.

2017’s national industrial strategy supported many UK successes in AI development. The strategy set out the government’s vision to make the UK a global centre for AI innovation. A ‘sector deal’ worth nearly £1 billion for the AI ecosystem followed in 2018.

There is global competition for the skills and finance on which R&D and the technology’s progress depend, along with access to data and computing power.

Investment around the world

In Singapore, for example, the government is investing in ambitious projects to accelerate AI/ML adoption in key sectors. Its national programme for financial services is funding an AI platform that will allow institutions to assess environmental impacts, identify emerging risks and make more environmentally sustainable investments. In the public sector, another aim is to leverage AI’s capabilities in natural language processing (NLP) so frontline government agencies can serve citizens better.

Japan’s government invested in 10 ‘AI hospitals’ designed to streamline administration and ease the impact of a doctor shortage. It believes the technology will help improve treatments and cut down on unnecessary tests and procedures.

International cooperation can also advance R&D. The UK and US governments have signed a joint declaration outlining a shared vision for driving technological breakthroughs in AI. The UK strategy envisages other global partnerships to extend collaboration on research and innovation.

A complete understanding of AI is vital for its adoption

At a business level, many R&D projects involving AI/ML fail due to a flawed strategy, poor data or lack of expertise. Even when companies get these critical factors right, they face the longer time and higher costs involved in commercialising artificial intelligence technologies compared with many other spheres of R&D.

The UK’s ambitions for global leadership in this field also depend on accelerating the adoption of AI by businesses. This has long been slow compared with other leading nations due to companies failing to understand how AI can address the challenges they face.

Promoting responsible development and deployment of artificial intelligence technologies is another priority identified by Innovate UK.  Businesses need to understand the ethical principles that will guard against unintentional harm to individuals or society, and be able to apply them cost-effectively in practice. They need more support to understand ethical implications at the outset of a project.

The UK’s governance and regulatory regimes must balance the fast-changing demands of AI against safety, security and citizens’ rights. This is on top of targeting financial support and creating the conditions in which artificial intelligence can flourish.

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