AI Use Cases and Case Studies
by Industry Sector

Mining and agriculture are not industries traditionally associated with digitisation but the deployment of artificial intelligence technologies offers the opportunity to transform our production of basic materials. Two key areas are increasing productivity and protecting the environment. In a world of declining resources and growing population pressure AI may help to alleviate some of humanity’s most pressing problems.

Some of the most AI-savvy companies work in the consumer sector - Google, Amazon, Facebook and Apple to name four. As data-native companies they are increasingly seeing themselves as AI-centric organisations able to break historic trade-offs between speed, focus and scale. Other companies in this space are either playing catch-up or are at risk of becoming simply operators on these companies’ platforms. In China a similar dynamic is playing out, albeit with a different set of core actors.

The need to capture more of the available energy - whether fossil or renewable - as such assets become harder to reach will drive take-up of AI. Whether it is for crunching drilling data to optimise investment or better positioning wind turbine blades, AI should help meet the world’s insatiable demand for power and alleviate the threat of climate change. Shifting traditional capital-intensive engineering organisations towards the new opportunities can be a challenge - especially to support mankind’s transition to renewable sources of energy.

At the end of the day financial services is a flow of information - albeit one heavily hedged with regulatory, security and legal safeguards. Whilst some financial service firms are investing heavily in transformation - even going so far as to rebrand themselves as “technology firms” - the industry largely remains tied to legacy data systems and historic approaches to business. Multiple new players are emerging in this space - and AI is a key underlying technology driving this.

AI is already changing healthcare in multiple ways. Most eye-catchingly it is delivering physician-level diagnoses - the potential of scaling this may be especially transformative in the huge areas where doctors are unavailable. But it also offers the potential to jump start stalling medical research, offer personalised treatment and lifestyle plans and to optimise provider service delivery. In an ageing world where there is a limit to the resources deployable against an unlimited demand artificial intelligence will be a key weapon in the struggle to bring netter health to all.

Artificial intelligence offers the potential to shave further productivity out of existing manufacturing processes whilst helping design and power new and better products. The potential impact on employment from the increased deployment of robots is a concern but not necessarily a new one by historic standards. AI sits at the heart of a series of technologies - 3D printing, the Internet of Things - that may have a huge impact on global supply chains and trade. The broader geo-economic and political outcomes from this may be a significant factor in the 21st Century.

The lurid headlines suggest that traditionally white collar jobs in professional services are especially at risk from AI. Whilst there is currently limited evidence to suggest that the impact in the foreseeable future will be any greater than that of the spreadsheet on the late 20th Century the automation of key information processing will impact on professional services. Those jobs that require judgement will flourish - the challenge may be for the apprenticeship processes that currently deliver the trained judgement makers. Should AI in professional service really take off then the likely impact of lowering costs, and prices, should lead to greater consumption of the product offered. A number of start-ups are already exploiting this opportunity in legal services for example.

Often traditionally slow to implement new technology the public sector offers huge scope for the resource allocation optimisation offered by AI. Defence and security are frequently ahead of the curve - and this appears to be true for AI, whether deployed in drones over war zones or being used to identify potential terrorist networks. Increasingly nation states are identifying AI as a key component of 21st Century great power politics - all of which raises significant ethical and political questions. If US and Chinese AI-powered software platforms become ubiquitous (with huge returns to scale) where does this leave other nations?

Different players are adopting different strategies but the roll out of cloud services, and the mapping AI tools offered, looks set to be a key area for financial returns for investors in AI in the coming years. Currently its a scale game from players like Microsoft and AWS but the growing differentiation of data chips offers new opportunities. Meanwhile, AI is emerging as the apex, organising technology enabling the next wave of innovation - blockchain, IoT and so on. Concerns that the pace of growth of compute power necessary for the current emerging generation of artificial intelligence tools is slowing (Moore’s Law) are likely to prove unfounded.

Increasing numbers of data-intensive services powered by AI will help power demand for the next generation of telecoms services. The heaviest users of data services - for example, video streaming services - are typically heavy users of AI - and new AI-powered consumer or transportation devices will remain heavily bandwidth-reliant, whatever the final state of the edge / cloud computing mix. Meanwhile, infrastructure investment will be further optimised by AI tools.

Be in no doubt that self-driving transportation is a hard-problem to solve and this is the area where the AI hype may prove most over-played. There will be work-arounds - non-AI vehicles may end up being banned from certain cities or roadways - but the self-driving car may take longer to be in your life than expected. However, mobility will be quietly transformed - whether the proliferation of drones, the roll-out of driver-support features and the mapping and optimisation of transport flows across urban centres. Thinking through the economic and social impact of a transport revolution is just beginning.

The need to optimise complex supply and demand networks and empower end users, whilst finding the resources to invest to meet the world’s insatiable demand for power and alleviate the threat of climate change are driving growing investment in artificial intelligence.Shifting traditional risk-averse and capital-intensive investment mind-sets towards the new opportunities remains a challenge.