The top developments of the last five years

Enterprise adoption of artificial intelligence has more than doubled over the past five years, with companies that spend more on the technology likely to receive more financial rewards, according to a McKinsey study.

According to a survey by the global consulting firm, the number of companies that reported using AI in at least one business area rose to 50 percent from 20 percent in 2017.

This reflects companies’ growing awareness of the importance of technology to their strategy. The number peaked in 2019 at 58 percent.

What was once an “AI winter” has turned into an “AI spring” as more enterprise technology leaders recognize the value of technology and seek to successfully integrate it into their businesses, wrote Michael Chui, Partner at McKinsey Global Institute. in the report.

“They’re not only investing more, they’re investing more wisely, with the goal of creating a true AI factory that will allow them to integrate more AI into more areas of the business,” he said.

“This is an emerging formula at a high level to get the maximum benefit from AI…it’s paying off in terms of actual bottom line impact at significant levels.”

AI is a key enabler of the digital transformation the world is currently experiencing as it can streamline business operations and user engagement.

According to data from Grand View Research, the global AI market is expected to exceed US$1.7 trillion in 2030, up from US$93.5 billion in 2021, and will grow at a compound annual growth rate of more than 38 percent.

The bottom line is high

About a quarter of respondents said at least 5 percent of their earnings before interest and taxes are due to AI, consistent with the past two years, according to the McKinsey study.

Going forward, spending on AI is expected to increase, with about two-thirds of companies planning to increase their technology investments to keep up with growing adoption, the survey found.

Currently, half of respondents using AI say more than 5 percent of their digital budget goes to AI, compared to 40 percent five years ago.

“What we may be seeing is the reality of the scale of organizational change required to successfully embed this technology in some organizations,” Mr. Chui said.

Focus on optimizing operations

Optimizing service operations was the most popular use case — and has remained so over the past four years — with nearly a quarter of respondents saying they have used AI in this industry, according to the McKinsey survey.

Service operations as a whole was among the most focused areas in the top 10 use cases in the study, accounting for three, linked to marketing and sales and product and marketing development.

The creation of new AI-based products, which falls under product and service development, ranked second at 20 percent, while customer service analysis ranked third under marketing and sales at 19 percent.

Reducing the environmental impact of AI

Technology’s impact on the environment is well known, and companies are incorporating AI into their sustainability efforts while trying to mitigate its impact, the study showed.

About 43 percent of companies said they are using AI to fuel their sustainability initiatives, while 40 percent said they are working to reduce environmental impact, it said.

Geographically, Greater China has the most companies using AI for sustainability (61 percent), followed by Asia Pacific (54 percent), developing markets (44 percent), Europe (39 percent), and North America (30 percent).

On the other hand, developing markets lead with 53 percent of companies when it comes to minimizing the impact of AI on the environment, followed by Asia Pacific (47 percent), Greater China (46 percent), Europe (36 percent) and North America (31 percent).

The race for talent is heating up

But companies face challenges in recruiting top talent for AI, even though jobs in this tech space are considered “hot roles,” according to the survey.

Software engineers were the top hires at 39 percent of companies last year, even surpassing data engineers (35 percent), AI data scientists (33 percent), machine learning engineers (30 percent), and data architects (28 percent). cents), it said.

This is a “clear sign” that companies have made a significant transition from experimenting with AI to actively using it in enterprise applications, it said.

However, the majority of organizations said they were struggling to hire talent for these roles — AI scientists remain scarce, the study found — which could threaten faster AI adoption.

An alternative, the report says, is to retrain or upskill existing employees to keep up with advances and competition.

“As the business value became clear, companies recognized the need to deliver insights from AI to a front end where people can consume and apply them to make an impact,” said Helen Mayhew, partner at McKinsey.

Updated December 06, 2022 5:07 am