For the past few years, McKinsey has been conducting a yearly online survey to help assess the state of AI adoption. The 2019 survey garnered responses from over 2,300 companies, and found that AI was becoming more mainstream, with nearly 80% of the responding companies using AI in some capacity. Most of these companies saw measurable benefits from their AI deployment, with 63% reporting year-over-year (YOY) revenue increase, while 44% reported YOY cost savings. However, much work was still necessary to scale the use of AI across the company, manage the risks, and retrain their workforce.
The most recent survey, took place in June of 2020 and received responses from almost 2,400 participants from different regions, industries, company sizes and functions. The State of AI in 2020, published in November, found that revenue increases had become a bit more common (66%) compared to the previous year, while cost decreases were now somewhat less common (40%). The biggest year-over-year increases were found in the strategy and finance functions (73% vs 59%), risk management (68% vs 57%), manufacturing (71% vs 61%), and supply-chain management (72% vs 63%). The biggest YOY cost decreases were found in strategy and finance (32% vs 50%), risk management (38% vs 54%), manufacturing (50% vs 64%), human resources (43% vs 55%), and product and/or service development (21% vs 29%).
What accounts for these (relatively small) differences between the two most recent surveys? “What we’ve said in the past about ‘following the money’ to find where AI adds value in organizations still holds true,” explained the report. “And, overall, many companies focused on growth in 2019 …; for that reason, it’s likely that we saw more companies driving revenues with AI rather than decreasing their costs - not because AI can’t effectively reduce costs.”
As was the case in 2019, the high-tech sector leads the way in AI adoption, followed by the telecom and the automative and assembly sectors. The survey also found that 70% of respondents had started to see the impact of AI on their 2019 enterprise-wide earnings before interest and taxes (EBIT), with 22% attributing more that 5% of their EBIT to AI, and 48% attributing less that 5%. “It’s also clear that we’re still in the early days of AI use in business, with less than a quarter of respondents seeing significant bottom-line impact. This isn’t surprising - achieving impact at scale is still elusive for many companies not only because of the technical challenges but also because of the organizational changes required.”
The 2019 survey found that a small share of high performers, around 3% of companies, were achieving outsize business results. Similarly, the 2020 survey found that a small contingent of companies attribute 20% or more of their EBIT to AI. These high performing companies are not just from the high-tech sector, suggesting that any company can get a good amount of value from AI if the technology is applied effectively.
“These companies plan to invest even more in AI in response to the COVID-19 pandemic and its acceleration of all things digital. This could create a wider divide between AI leaders and the majority of companies still struggling to capitalize on the technology; however, these leaders engage in a number of practices that could offer helpful hints for success.” Three specific practices separate the best from the rest:
Better overall performance. The highest performing AI companies are also those with better overall YOY growth. “Respondents at high-performing companies are nearly twice as likely as others to report EBIT growth in 2019 of 10 percent or more.” This is not surprising. For example, 43% of high performing companies have a clearly defined AI vision, compare to 17% of all others, and 53% have aligned their AI strategy with their enterprise-wide strategy compared to 42% for all others. A critical success factor for AI is a company’s progress along its digitization journey. The same players who’ve been leaders in earlier waves of digitization are now leading the AI wave.
Better overall leadership. “Respondents at AI high performers rate their C-suite as very effective more often than other respondents do. They also are much more likely than others to say that their AI initiatives have an engaged and knowledgeable champion in the C-suite.” 60% of AI high performers said that their senior management is fully committed to the AI strategy, compared to 34% for all other companies, and 52% said that there’s strong AI leadership guiding the initiative, compared to 32% of all others.
Resource commitment to AI. “AI high performers invest more of their digital budgets in AI than their counterparts and are more likely to increase their AI investments in the next three years. In addition, high performers have the ability to develop AI solutions in-house - as opposed to purchasing solutions - and they typically employ more AI-related talent, such as data engineers, data architects, and translators, than do their counterparts.” For example, 40% of high performing companies have programs to develop AI skills among their tech professionals compared to 15% of all others, and 36% have effective programs to recruit AI talent compared to 21% of all others.
Finally, the pandemic has now accelerated the digital transformations that companies made to help them cope with the crisis. “The COVID-19 crisis seemingly provides a sudden glimpse into a future world, one in which digital has become central to every interaction,” said a McKinsey article in April, 2020.
“Despite the economic challenges that pandemic-mitigation measures have caused for many companies, those seeing the most value from AI are doubling down on the technology,” notes the McKinsey survey. “The companies seeing significant value from AI are continuing to invest in it during the pandemic.” 61% of high performing companies increased their AI investments amid the Covid crisis, while 25% of other respondents did so. Companies in the health care and pharmaceutical sectors led the way in increasing their AI investments.
“Throughout the pandemic, we’ve seen organizations across sectors adopting and scaling AI and analytics much more rapidly than they previously thought possible. Many organizations have worked with their analytics teams to update demand patterns, reconsider supply chains, build scenario plans around resource needs, and enable automation in factories and other industry settings where workers may need to distance and have fewer people on-site.”
“Many companies are now turning to longer-term opportunities. With more data from digital channels available, improved recommender systems, for example, can enable better customer experience, more personalized content, and automated digital customer service. So it’s not surprising that the pandemic has spurred more investment in AI capabilities. The companies currently underperforming in AI clearly aren’t investing as much and risk falling further behind AI leaders.”
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