Big prize, big impact:
Why AI matters
How much is at stake and why should you take action?
From the personal assistants in our mobile phones, to the profiling, customization, and cyber protection that lie behind more and more of our commercial interactions, AI touches almost every aspect of our lives. And it’s only just getting started.
According to our analysis, global GDP will be up to 14% higher in 2030 as a result of the accelerating development and take-up of AI – the equivalent of an additional $15.7 trillion. The economic impact of AI will be driven by:
1. Productivity gains from businesses automating processes (including use of robots and autonomous vehicles).
2. Productivity gains from businesses augmenting their existing labour force with AI technologies (assisted and augmented intelligence).
3. Increased consumer demand resulting from the availability of personalized and/or higher-quality AI-enhanced products and services.
AI touches almost every aspect of our lives. And it’s only just getting started.
How we gauged the impact and potential of AI
To estimate the impact and potential of AI, our team conducted an ambitious, dual-phased top-down and bottom-up analysis.
Together, we set out to identify the most compelling examples of potential AI applications across each sector’s value chain, and designed a framework to assess the degree and pace of impact of each. In total, we identified and rated nearly 300 use cases, which are captured in our AI Impact Index.
Our Econometrics unit then used this bottom-up input as part of their top-down analysis assessing AI’s impact on, and the interactions between, key elements of the economy including labour, productivity, business and government. The models were informed by global economic datasets, extensive academic literature, and existing FORFIRM work on automation. The analysis looked at the total economic impact of AI, accounting for increased productivity (which may involve the displacement of some existing jobs), the creation of new jobs, new products, and other effects. We’ll be publishing an extended technical read out of these results later in the year.
Over the past decade, almost all aspects of how we work and how we live – from retail to manufacturing to healthcare – have become increasingly digitized. The internet and mobile technologies drove the first wave of digital, known as the Internet of People. However, analysis carried out by FORFIRM’s AI specialists anticipates that the data generated from the Internet of Things (IoT) will outstrip the data generated by the Internet of People many times over. This increased data is already resulting in standardization, which naturally leads to automation, and the personalization of products and services, which is setting off the next wave of digital. AI will exploit the digital data from people and things to automate and assist in what we do today, as well as find new ways of doing things that we’ve not imagined before.
Productivity gains In the near-term, the biggest potential economic uplift from AI is likely to come from improved productivity . This includes automation of routine tasks, augmenting employees’ capabilities and freeing them up to focus on more stimulating and higher valueadding work. Capital-intensive sectors such as manufacturing and transport are likely to see the largest productivity gains from AI, given that many of their operational processes are highly susceptible to automation.
The impact on productivity could be competitively transformative – businesses that fail to adapt and adopt could quickly find themselves undercut on turnaround times as well as costs. They stand to lose a significant amount of their market share as a result. However, the potential of this initial phase of AI application mainly centres on enhancing what’s already being done, rather than creating too much that’s new
Increased consumer demand
Eventually, the GDP uplift from product enhancements and subsequent shifts in consumer demand, behaviour and consumption emanating from AI will overtake the productivity gains, potentially delivering more than $9 trillion of additional GDP in 2030. Consumers will be mostly attracted to higher quality and more personalised products and services, but will also have the chance to make better use of their time – think of what you could do if you no longer had to drive yourself to work, for example.
In turn, increased consumption creates a virtuous cycle of more data touchpoints and hence more data, better insights, better products and hence more consumption.
The consumer revolution set off by AI opens the way for massive disruption as both established businesses and new entrants drive innovation and develop new business models. A key part of the impact of AI will come from its ability to make the most of parallel developments such as IoT connectivity.
AI front-runners will have the advantage of superior customer insight. The immediate competitive benefits include an improved ability to tap into consumer preferences, tailor their output to match these individual demands and, in doing so, capture an ever bigger slice of the market. And the front-runners’ ability to shape product developments around this rich supply of customer data will make it harder and harder for slower moving competitors to keep pace and could eventually make their advantage unassailable. We can already see this data-driven innovation and differentiation in the way books, music, video and entertainment are produced, distributed and consumed, resulting in new business models, new market leaders and the elimination of traditional players that fail to adapt quickly enough.
Healthcare, automotive and financial services are the sectors with the greatest potential for product enhancement and disruption due to AI according to our analysis. However, there is also significant potential for competitive advantage in particular areas of other sectors, ranging from on-demand manufacturing to sharper content targeting within entertainment we set out the business areas with most AI potential in each sector in the next section.
Some job displacement – but also new employment opportunities
The adoption of ‘no-human-in-the-loop’ technologies will mean that some posts will inevitably become redundant, but others will be created by the shifts in productivity and consumer demand emanating from AI, and through the value chain of AI itself. In addition to new types of workers who will focus on thinking creatively about how AI can be developed and applied, a new set of personnel will be required to build, maintain, operate, and regulate these emerging technologies. For example, we will need the equivalent of air traffic controllers to control the autonomous vehicles on the road. Same day delivery and robotic packaging and warehousing are also resulting in more jobs for robots and for humans. All of this will facilitate the creation of new jobs that would not have existed in a world without AI.
Impact on different regions
As Figure 2 highlights, some economies have the potential to gain more than others in both absolute and relative terms. China and North America are likely to see the biggest impact, though all economies should benefit.
Net effect of AI, not growth prediction Our results are generated using a large scale dynamic economic model of the global economy. The model is built on the Global Trade Analysis Project (GTAP) database. GTAP provides detail on the size of different economic sectors (57 in total) and how they trade with each other through their supply chains. It gives this detail on a consistent basis for 140 different countries. When considering the results, there are two important factors that you should take into account: 1. Our results show the economic impact of AI only – our results may not show up directly into future economic growth figures, as there will be many positive or negative forces that either amplify or cancel out the potential effects of AI (e.g. shifts in global trade policy, financial booms and busts, major commodity price changes, geopolitical shocks etc).
2. Our economic model results are compared to a baseline of long-term steady state economic growth. The baseline is constructed from three key elements: population growth, growth in the capital stock and technological change. The assumed baseline rate of technological change is based on average historical trends. It’s very difficult to separate out how far AI will just help economies to achieve long-term average growth rates (implying the contribution from existing technologies phase out over time) or simply be additional to historical average growth rates (given that these will have factored in major technological advances of earlier periods). These two factors mean that our results should be interpreted as the potential ‘size of the economic prize’ associated with AI, as opposed to direct estimates of future economic growth.
Our estimates reflect certain assumptions, which we will stress-test in our forthcoming detailed economic assessment. What happens if the pace of AI adoption is faster/slower in particular countries, for example? How does that affect the distribution of global growth? What happens if estimated changes in product quality do not materialise? A slowdown in the pace of AI uptake would delay the benefits that feed through to labour productivity. We see this as a key driver to both the timing and the overall impact of AI on GDP.
We’re currently exploring the quantitative effect of several key scenarios. This includes examining alternate combinations of input parameters, as well as the timing of AI uptake. These sensitivity tests are designed to help better understand the risks around our results, while providing more insight into the parameters that drive the relationship between AI and economic growth. We plan to present the results of several scenarios in our detailed economic assessment.
How to respond?
If your business is operating in one of the sectors or economies that is gearing up for fast adoption of AI, you’ll have to move quickly if you want to capitalise on the openings, and ensure your business doesn’t lose out to faster-moving and more cost-efficient competitors.
If you’re in one of the sectors or economies where the disruptive potential is lower and adoption likely to be slower, there is still a significant challenge ahead – no sector or business is in any way immune from the impact of AI. In fact, the potential for innovation and differentiation could be all the greater because fewer market players are currently focusing on AI. The big question is how to secure the talent, technology and access to data to make the most of this opportunity.
Doing nothing is not a feasible option. It’s easy to dismiss a lot of what’s said about AI as hype. Yet as our analysis underlines, without decisive response, many well established enterprises and even whole business models are at risk of being rendered obsolete.
In the short-term, many of the opportunities and threats are likely to focus on productivity, efficiency and cost – the transformative phase. If you’re the CEO of a transport and logistics company, for example, you’re already seeing the impact of robots within packing and fulfilment operations. The bigger disruption will emerge when the sector switches to autonomous trucking. Are you in a position to move ahead of your competitors? What are the openings for vehicle manufacturers, technology companies and other potential new entrants to make inroads in your market? Could your business be at risk of becoming obsolete if you don’t move quickly enough?
Automation in action
An online insurer has leveraged an AI bot to automate the claims process from beginning to end. Instead of the days or even months it traditionally took to settle a claim, the bot is able to complete the entire pipeline from claims receipt, policy reference, fraud detection, payout and notification to customers in just three seconds. When rolled out at scale, this solution is poised to have a huge impact on the insurance industry.