AI's Potential To Boost GDP
After the 2008 crisis, like most developed countries, the UK saw a large fall in its real GDP growth rate (-2%), by 2010 Q2 it had nearly returned to its pre-crisis growth rate of 1.2%.
However, something this data(above) doesn’t show is that it was only until 5 years later(2015) that real GDP per capita caught up to its pre-crisis level(below). Unemployment has also recently pre 2008 levels, however, a common criticism of these figures is that they do not include underemployment (workers in jobs that are not using their full skill sets, i.e. a lawyer working at McDonald's) or workers working part-time but wishing to be in full employment. From this and recent fears of recession spreading from the United States (Bond Yield Inversion) our economy would benefit from a boost in Aggregate Demand and GDP.
In a recent McKinsey report in collaboration with one of their most recent acquisitions (4th acquisition in 2015), QuantumBlack ( London-based firm with beginnings in Formula 1 racing that is pioneering the use of big data and advanced analytics to improve organizational performance) some interesting conclusions were drawn in regards to the effect of AI on the economy.
To summarise some of the most interesting figures of the report, McKinsey concluded that:
The report found similar results for most developed nations and China in the range of 20% - 25% boosts in GDP. At the firm level, the report splits firms into two categories: “Front-runners” and “Laggards”. Front-runners refer to companies that fully implement AI systems into their infrastructures in the next five to seven years. The report states these companies pioneering the rise of AI in their respective industries could see growth by around 120% by 2030 (or about 6% growth a year for the next 12 years). Laggards, on the other hand, are firms who do not adopt AI at all or are late in doing so. The report states these firms could lose around 20% of cash flow as more efficient competition will enter their markets with lower average costs. In the simulations, Laggards reduce their employment and investment more than other businesses.
An interesting result from McKinsey’s simulations is the nonlinearity of results throughout industries. For example the difference between Laggards and Front-runners in terms of growth in financial services are 30% while in high tech it is 80%.
The report goes into detail about the UK’s position in being able to compete in the AI sector in the future. According to the report the United Kingdom is in a strong position to compete relative to other European countries however when compared to the US and China it falls short(below).
In order to compete at the highest level, the report proposes some solutions for the UK. One of these is the idea that although there are large “pockets of innovation” in the country the benefits are received by all firms, in order to correct this the report suggests an increase in investment on AI, as in recent years investment has lagged behind the US and EU firms. Another idea is that although the United Kingdom has a large pool of AI talent it lacks enough specialists to make the same amount of progress as its foreign rivals. This can be solved in the long run through implementation of supply-side policies such as more widespread access to AI training courses.
In conclusion, AI could help boost the economy in the face of dire economic conditions, however as it stands the UK is not prepared to fully benefit from the AI boom. The report recommends government intervention to ensure there won't be shortages of specialised labour in the sector as well as increasing investment into the sector as a whole.If these policies are implemented policies the UK could potentially see large benefits.
The report sums up the UK’s situation perfectly: