AI could exaggerate economic divide - McKinsey

Research from the McKinsey Global Institute (MGI) has suggested artificial intelligence could create an additional $13 trillion for the global economy, but it might make the gap between the haves and have nots impossibly wide.

The potential of AI has been much-hyped, though it will be sometime before the rewards are actually realised. The first few years of implementing the technology might yield benefits, though the real fortunes will be made towards the end of the next decade. Initially, companies will have to absorb some experimentation costs as well as those of failure.

“As a result, AI’s contribution to growth may be three or more times higher by 2030 than it is over the next five years,” the report states. “Initial investment, ongoing refinement of techniques and applications, and significant transition costs might limit adoption by smaller firms.”

Companies like Google or Amazon who are already seeing the benefits of AI can contribute more R&D funds due to the vast amount of profit which is returned to the engineering teams. Massive enterprise organizations can absorb the initial costs due to institutional investors having an eye on the bigger prize down the road; profitability can often be sacrificed in lieu of greater rewards tomorrow. But the smaller organizations, those who are reliant on profitability month-on-month, year-on-year, to continue trading will not be able to play patiently with AI applications and processes.

Whether the organization is a ‘producer-user’ of AI or ‘user-only’ type firm, the technology offers a competitive advantage. This might not be visible in the first couple of years, but the profits will be more visible as we get closer to 2030. By 2030, MGI predicts early-adopters of AI will see economic value (economic output minus AI-related investments and transition costs) increase by 122%, while followers (those who adopt AI by 20130) will grab a 10% net gain. This is an incredibly broad group considering the adoption criteria is spread over a ten year period, though those who do not adopt AI by 2030 will see their own economic value decrease by 23%. MGI estimates the final group, the ‘laggards’, accounts for 60-70% of firms worldwide.

The same could be said for countries and regions as well. Developed nations in Europe or Asia for example, are investing heavily in AI, whereas the likes of South America or Africa are not. The longer it takes for a country or company to implement the technology, the lesser the benefits in the long-run. MGI estimates those economies which embrace AI and establish themselves as frontrunners could capture an additional 20-25% in economic benefits compared with today. However, those who are slower to snatch at the trend will experience only up to half of these economic benefits.

In assessing the progress of various countries worldwide, China and US are the only countries which sit in the top group of ‘active global leaders’. A wide variety of countries sit in the second group of ‘economies with strong comparative strengths’ including the UK. This comparison might come as a slight dampener for the UK Government which believes AI is a central pillar of the country’s future economic prosperity. Investments in AI, human capital (i.e. those with STEM qualifications) and labour-market structure are three factors holding back the UK, though much of the story made for positive reading across the board.

The divide between those which would be considered leaders and laggards is growing. This is certainly the case in terms of countries around the world, but also companies in those countries themselves.

“As absorption rates diverge, so does the potential economic impact of AI,” the report states. “Because economic gains combine and compound over time, the simulated gap in net economic impact between the country groups with the highest economic gains and those with the least is likely to become larger.”

With the majority of companies around the world ignoring the AI craze, those who fight their way into the early adopter category could see extraordinary benefits. The risk however is the creation of an economic class system, with wide verges between the haves and have nots which will become increasingly difficult to overcome. Those who find themselves in the ‘lower class’ tier might adopt AI from an efficiency perspective to reverse the damage done through inaction, though this has the potential to compound the damage.