A.I. 2030 | $13 trillion boost to economy, deepening disparity: McKinsey

A.I. 2030 | $13 trillion boost to economy, deepening disparity: McKinsey

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Artificial intelligence (AI) could create a $13 trillion uptick in the world economy by 2030, boosting GDP by 16 percent, according to a new report from management consulting firm, McKinsey.

However, the technology will widen disparity between countries, between companies, and between citizens in both economic and opportunity terms, it warns.

The new research from the McKinsey Global Institute simulates the impact of AI on the world economy, taking into account the likely disruptions that countries, companies, and workers experience as organisations adopt the technology.

McKinsey looked at the impacts of five different type of AI: computer vision; natural language processing; virtual assistants; robotic process automation (RPA); and advanced machine learning. As such, the results can’t be interpreted as a pure investigation of AI adoption, as not all RPA is AI based.

That aside, McKinsey’s simulation shows around 70 percent of companies adopting at least one type of AI by 2030, but less than half of large enterprises using “the full range” – the five technologies McKinsey has selected – across their organisations.

Taking into account competition effects and transition costs, AI could potentially deliver additional economic output of about 1.2 percent a year over the next 12 years – a cumulative emergence of benefits, adding up to $13 trillion by 2030.

The report says, “Our simulation suggests that the adoption of AI by firms may follow an S-curve pattern – a slow start, given the investment associated with learning and deploying the technology, and then acceleration driven by competition and improvements in complementary capabilities.”

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.

However, initial investment, ongoing refinement of techniques and applications, and significant transition costs may limit adoption by smaller firms.

This is one reason why the key policy and management challenge in the next decade will be AI’s potential to widen gaps between countries, companies, and workers, says McKinsey.

The international perspective

“AI may widen performance gaps between countries,” says the report. “Those that establish themselves as AI leaders (mostly developed economies) could capture an additional 20 to 25 percent in economic benefits compared with today, while emerging economies may capture only half their upside.”

Many developed countries will have no choice but to push AI adoption to capture higher productivity growth as GDP growth slows – partly as a result of ageing populations, explains McKinsey. Wage rates in these economies are high, which means that there is more incentive than in low-wage, developing countries to substitute labour with machines.

Developing countries tend to have other ways to improve their productivity, including catching up with best practices and restructuring their industries. As a result, they may have less incentive to push for AI – which, in any case, may offer them fewer economic benefits, says the report.

However, this doesn’t mean that developing economies are destined to lose out. Countries can choose to strengthen the foundations, enablers, and capabilities needed to reap the potential of AI, and be proactive in accelerating adoption, says McKinsey – as China is doing, for example.

The company of adopters

There could also be a widening gap between companies, with frontrunners potentially doubling their returns by 2030 and companies that delay adoption falling behind, says McKinsey. Front-runners will tend to have a strong digital base, a higher propensity to invest in AI, and positive views of the business case for the technology.

However, this category is not a homogeneous group of winners, cautions McKinsey. “Some current AI innovators and creators have big starting endowments of data, computing power, and specialised talent,” says the report. “Other early adopters may not engage in creating these technologies, but may be innovative in how they deploy them.”

At the other end of the spectrum is a long tail of laggards that have either failed to adopt AI, or have not fully absorbed them by 2030. This group may experience a “20 percent decline in their cash flow from today’s levels, assuming the same cost and revenue model as today”. That’s a big assumption, however.

Winners and losers

Workforces will be impacted by the same challenges, warns McKinsey. “For individual workers, too, demand and wages may grow for those with digital and cognitive skills and with expertise in tasks that are hard to automate, but shrink for workers performing repetitive tasks.”

This overall finding that, far from being a global equalising force, AI may divide nations, companies, and workers into winners and losers is troubling.

However, many of the McKinsey findings broadly echo recent reports from the World Economic Forum (WEF) and professional services giant PwC, among others.

Earlier this month, for example, the WEF published a global study of the potential employment impacts of AI and other Industry 4.0 technologies. That report predicts widespread disruption to established industries and employment patterns, leading to massive job displacement. However, there will be a net increase of 58 million jobs worldwide by 2022, it says.

The WEF found that in many economies, including the US, UK, and China, AI, machine learning, analytics, and the IoT are now regarded as the most strategically important technologies by business leaders – ahead of even cloud computing.

Most organisations plan to automate increasing numbers of jobs, added the WEF – which observed that traditional middle-class careers such as accountancy, law, auditing, and banking are as much under threat as manual labour and driving – but fewer organisations plan to invest in retraining and up-skilling any sidelined staff.

As a result, an influx of new, expert workers will benefit from their AI, data analysis, robotics, change management, and Industry 4.0 skills, while others may find themselves adrift in an increasingly automated economy.

How companies and countries choose to embrace AI will impact on these outcomes, says the new McKinsey report. “The pace of AI adoption and the extent to which companies choose to use AI for innovation rather than efficiency gains alone are likely to have a large impact on economic outcomes,” it says.

This is a critical point. A number of recent studies have revealed that many organisations are adopting AI and related technologies to slash internal costs, rather than invest in making their businesses smarter. As a result, many of these programmes will fail, as organisations ignore vendors’ advice that cognitive services should augment human skills, not replace them.

In the long term, these trends – observed by several recent reports – suggest that the real battleground will be skills and education. Are employers prepared to invest in re-skilling their workforce – either for a new age of automation augmented by human skills, or of human skills augmented by technology?

Either way, the race is on, says McKinsey. “In all cases, there are trade-offs that need to be understood and managed appropriately in order to capture the potential of AI for the world economy.”

The results “reinforce our perception of the imperative for businesses, government, and society to address the challenges that lie ahead for skills and the world of work,” concludes McKinsey.