Executives have high hopes for AI and recognise its business case, but adoption remains sluggish and a “large gap” is emerging between passive and pioneering organisations, according to a report from MIT Sloan Management Review.
While 84 per cent of executives believe AI can provide a competitive advantage, most aren’t putting their money where their mouth is — just 23 per cent of organisations have incorporated AI beyond pilot programs, according to the research.
The report, Reshaping Business With Artificial Intelligence, was produced in collaboration with The Boston Consulting Group and surveyed more than 3000 executives, managers, and analysts across 112 countries. It found that, despite high expectations and a sense of urgency, few organisations were committing to AI.
The report classified 19 per cent of organisations as “pioneers” — businesses that understood AI and have incorporated it into the processes and offerings. But the majority of organisations (36 per cent) were classified as “passive” — businesses with “no adoption or much understanding of AI”. The remainder fell in between as either “experimenters” (13 per cent) or “investigators” (32 per cent).
The reasons for slow AI implementation “are less about technological limitations and much more about business,” the authors wrote.
“In aggregate, respondents ranked competing investment priorities and unclear business cases as more significant barriers to AI implementation than technology capabilities.”
Leading AI organisations were overcoming these issues by generating understanding across the organisation and demonstrating a business case, according to the report. In other words, AI makes sense when it solves a business problem, and senior executive leadership is a big factor in AI adoption.
Pioneers also have a better understanding of the technology. According to the report, “Compared to passives, pioneers are 12 times more likely to understand the process for training algorithms, ten times more likely to understand the development costs of AI-based products and services, and eight times more likely to understand the data that’s needed for training AI algorithms.”
The last point is particularly significant, according to the research. Using AI to capture business value is “directly connected to effective training of AI algorithms” — something many organisations are yet to understand.
“Naked” AI needs to be trained on company data, meaning AI technology can’t simply be bought or outsourced, the authors said.
“Generating value from AI is more complex than simply making or buying AI for a business process. Training AI algorithms involves a variety of skills, including understanding how to build algorithms, how to collect and integrate the relevant data for training purposes, and how to supervise the training of the algorithm.
“Many pioneers already have robust data and analytics infrastructures along with a broad understanding of what it takes to develop the data for training AI algorithms.”
In contrast, passive organisations have minimal investment in the data and processes required for algorithm training, according to the research.
It is still early days for most organisations when it comes to AI — just 15 per cent of those surveyed reported a “large effect” on current processes. But most remain bullish on the technology’s potential. Over 59 per cent expect to see a large effect from AI within five years. There is also an understanding that the AI benefit won’t be restricted to large organisations and its use will become more commonplace.
“Respondents expect that both new entrants and incumbents would similarly see the potential for benefits,” the authors said.
“Three quarters of respondents foresee new competitors using AI to enter their markets while 69 per cent expect current competitors to adopt AI in their businesses. Furthermore, they realise that suppliers and customers in their business ecosystem will increasingly expect them to use AI.”