A global survey of more than 3,000 managers, as well as interviews with executives and scholars, has reported that a majority of companies are developing artificial intelligence (AI) capabilities but have yet to gain significant financial benefits from their efforts.
The survey, published in the Expanding AI’s impact with organisational learning study from Boston Consulting Group in partnership with MIT Sloan Management Review, found that just one in 10 companies generates significant financial benefits from AI.
The study notes that the adoption of AI across industries is increasing, and more companies perceive that AI drives both strategic opportunity and risk.
The researchers found that 57% of companies report having AI pilots or have deployed AI. This is a significant increase from 2018, when 44% of companies said they were piloting or deploying AI. More than half of respondents (59%) now say they have an AI strategy, up from 39% in 2017.
One company cited in the report is German sports car manufacturer Porsche, which has used AI to make complicated region-specific production decisions to match inventory with local demand in cities around the world. In the report, Porsche CIO Mattias Ulbrich described how the car maker was using AI to continuously learn how to better tailor the precise mix of configurations of cars, out of millions of potential options, that the company delivers to each market.
The report’s authors note that shifts in market demand and regulatory environments intensify the need for accurate and continually adjusted predictions. For example, they said the need for Porsche to improve its ability to allocate the right products to the right market is an ongoing motivation to learn with AI.
While supervised AI training requires humans to help the system produce more accurate answers, the report’s authors suggest that AI can also offer alternatives that humans have not yet considered. This tends to happen after initial supervised training, when the AI begins to learn autonomously.
For example, the report discussed how the engineers developing taxi app Lyft designed an algorithm to maximise revenue by matching driver supply and customer demand. In the report, Elizabeth Stone, former vice-president of science at Lyft, said the algorithm assessed the ride being requested, where the driver was located and all of the system dynamics in order to maximise revenue.
During further tests, said Stone, the data scientists at Lyft found that the AI had identified a better algorithm, based on optimising the conversion rate of users who actually order a ride after opening the app. She said that having humans in the loop who could think through and test possible objectives for the machine learning algorithms was critical.
Combining human knowledge about the business with AI’s computation power enabled Lyft to improve a key strategic metric. The change influenced an array of business activities, including operations, revenue targets, performance management and marketing.
The study also asked companies about responsible AI. More than two-thirds (72%) of firms that have a responsible AI strategy said they experienced financial benefits from using AI, and 62% said using AI enabled them to decrease operational risk.
Read more about AI training
- Encompassing ethics, transparency and human centricity, responsible AI is an effective approach to deploying machine learning models and achieving actionable insights.
- To drive business value from AI, business managers need to distinguish between the various AI techniques, starting with the many flavours of machine learning.