New study debunks key myths regarding Artificial Intelligence

27 September 2018 7 min. read

A new study has sought to dispel a number of key myths which currently stand in the way of AI adoption among businesses. Among the key findings, researchers note that almost three quarters of AI leaders are focusing on the technology’s ability to deliver revenue increases, while gearing it toward job reductions and cost cutting are seen as missing out on AI’s true potential.

The continued march of innovative new Artificial Intelligence (AI) technologies have brought with them the potential for improved efficiency of resources, heightened productivity in manufacturing, and even the potential for low-cost medical care in the developing world. However, while the promises of the innovative new technology continues to attract large amounts of investment from both businesses and governments keen to harness its potential, multiple misconceptions regarding AI persist.

Many business leaders still believe that AI is merely a tool for reducing costs, or expect it to allow them to reduce workforce numbers. At the same time, a number of executives still see AI as a medium of tomorrow, which only requires minor experimentation in the here and now, while highly developed technologies can be leveraged later on to level the playing field with current AI leaders. However, a new report has set out to challenge these perceptions, with MIT Sloan Management Review and the Boston Consulting Group (BCG) collaborating to analyse a global survey of 3,076 business executives and 36 in-depth interviews, to uncover the dying myths an emerging realities of this unique moment in industrial history.

Common and uncommon barriers to AI

The researchers classified the organisations polled into four groups. This quartet consists of Pioneers (enterprises that have extensive understanding of AI and significant levels of AI adoption); Investigators (who understand AI but have limited adoption); Experimenters (having adopted AI but with limited understanding of it) and Passives (both limited adoption and understanding of AI). According to the findings, Pioneers are deepening their commitments to AI, as they look to scale AI throughout their enterprise, enabling them to prioritise the leveraging of AI for revenue-generating applications over cost-saving ones.

A recent study from the McKinsey Global Institute warned that this could lead to a significant gap between leaders on AI adoption and those looking to make up ground later. Leaders could see business performance boosted cumulatively by as much as 122%, compared to just 10% among followers, or -23% among the non-adopters, and that while front-runners will have to bear with some initial issues, they will eventually enjoy an overall output gain by 135%. Despite cautionary predictions such as this, however, MIT Sloan Management Review and BCG still found that many executives still kowtow to a number of myths which will likely see their companies left in the dust by Pioneers.

Lagging behind

More than 60% of Passives still believe there is an unclear business case – or a total absence of one – for AI applications within their company. Close to 50% of the same category also told researchers they have limited or no general technology capabilities such as analytics, data, or adequate IT infrastructure, while a growing number on 2017’s figures also suggested they encountered cultural resistance to changing their AI approaches.

This may well relate to three of the myths which the analysts believe it is important to debunk. First, there is an idea shared by some executives slow to adopt AI, that the benefits of AI are perpetually “just out of reach”. In reality, though, MIT Sloan Management Review and BCG assert that AI is currently providing real value in real organisations, not just lab demonstrations in technology organisations.

Pioneers focus on revenue-generating opportunities

At the same time, later adopters suggest that many companies that see success with AI are flourishing via small-scale experiments. This downplays the need for a long-term strategy on the front of AI adoption and innovation, and suggests that slower movers in the sector can make up ground by dabbling on an ad-hoc basis. In actual fact, though, AI leaders are, and have been for some time, creating strategies for taking it to industrial scale. According to the survey, 85% of pioneers agree they have an urgent need for an AI strategy, and 90% say they have a strategy in place already.

Relatedly, another assertion by slow adopters tends to be that later in the game, widely available sophisticated AI tools will level the playing field, essentially making early adoption pointless and costly. However, the researchers counter this by pointing out that 88% of Pioneers invested more in AI than in the previous year, compared with 62% of other groups, meaning Pioneers are widening a gap with others that late adoption will render insurmountable.

Long-term planning

This is because Pioneers are gearing AI toward long-term value creation, rather than simply using it to trim the fat. While a majority of firms among Passives, Experimenters, Investigators and Pioneers have sought to use AI to this end in the past three years, Pioneers are the most committed to this as a permanent tactic, with 72% still looking at this avenue of AI usage in the next five years. This is compared to 52% of Passives, who are more likely to use it for cost reduction exercises over that same period.

A large part of the belief that AI can drive ‘cost reductions’ is that many senior managers still view AI as a tool that will help them achieve workforce reductions. This can be seen in a range of contemporary workplace examples, where bosses determined to undermine the efforts of staff to win better pay and workplace rights prime AI solutions to outflank the workforce. In reality, though, the alleged potential of AI in this area remains less clear-cut. While 47% of respondents told researchers they expect workforce reductions due to AI, far fewer CEOs, at 38% of those surveyed, said they have that expectation.

Workforce uncertainty endures

This is largely because AI does not seem capable of replacing human labour, and furthermore does not seem designed to. Rather, the primarily function of AI is currently to complement human talent, and free it up to add value elsewhere. In this respect, while it is commonly cited that over 60% of all work activities could be automated by 2055, fewer than 5% of jobs could be completely replaced by technology in that same time-frame. Indeed, AI is likely to lead to a modest rise in jobs created, reallocating labour into different aspects of a business, while working populations across the world’s largest economies begin to age rapidly, adding to a shortage of available talent.

In conclusion, the study states that executives in companies around the world are increasingly looking to AI to create new sources of business value, which is key if they are to get the most out of it. At the same time, if latecomers are looking to make up for lost time, they will need to emulate the Pioneers who have made long-term plans, while focusing sparingly on the defensive uses of AI such as cost-reduction and staff cuts.

Summarising this neatly, Bill Braun, CIO of Chevron told the researchers, “It’s springtime for AI, and we’re anticipating a long summer.”