IDC study: Businesses report a massive 250% return on AI investments 

A survey of 2,100 global business leaders and decision makers by research firm IDC suggests a new level of momentum around AI investments by businesses, driven by perceived value and excitement around generative AI.

The report, which was commissioned by Microsoft, but independently conducted by IDC, found that respondents report an average 3.5x return on their AI investments. In other words, they say they are reaping $3.5 in returned value for every $1 invested. 

Put yet another way, that’s a whopping 250% return. And that’s significant, when compared to other reports conducted on monetization of AI. IBM reported an average ROI of only 5.9%, based on a May survey of 2,500 global executives. That return is below the typical 10% cost of capital, and so from that perspective, AI could be deemed a risky investment choice. Other reports have shown even lower average returns, or have discussed how difficult it is to estimate ROI and that companies often make big mistakes when calculating ROI.

One of the first reports on AI monetization since generative AI’s watershed moment last year

The IDC report was conducted in September, and so is one of the first reports to look at monetization since the hype started around generative AI late last year. Among other highlights, the report found that 71% of respondents say their companies are already using AI, with 22% planning to do so within the next 12 months. It found that 92% of AI deployments are taking 12 months or less, which is faster than the deployment rates seen for previous technologies.

However, It was the first time IDC has explicitly sought to have respondents quantify their returns on investments, according to Ritu Jyoti, GVP AI and Automation for IDC, who leads the firm’s AI research efforts, in an interview with VentureBeat. 

When asked about IDC’s research methodology in calculating the ROIs, she said the firm relies on self-reported data from respondents. IDC also provided large buckets as choices for answers to the question about ROI: Respondents could answer with 2X, 3X, 4x 5x, no ROI and Not sure. (If their answer was over 5x, the respondent was asked to specify further).  

We’ll want to track ROI claims in future reports, to see if these ROI estimates hold up. On the one hand, if these numbers are anywhere close to accurate, there’s essentially very little to no risk for organizations to push ahead on an aggressive AI investment strategy, at least if it’s diversified and disciplined. On the other hand, there’s also a chance that these estimates simply reflect a generally bullish attitude about AI among many respondents, at a time of considerable hype around generative AI – and that respondents may not be taking the time or care to report experiments or projects that yield poor ROIs. Thus, caution should still be exercised around making AI investments.

Companies are steering money into AI by deprioritizing other initiatives

Indeed, Jyoti said there’s so much excitement around AI that companies are actually deprioritizing other initiatives to prioritize AI. “That is something that is new,” she said, not seen in her survey last year or other AI reports her team has done. This has been triggered specifically by heightened interest caused by generative AI, she said. Some 32% of organizations said they have reduced an average of 11% of spending on certain business areas, in order to invest more into AI, she said. The areas being reduced are outside of IT, and are in areas like administrative support and services. Administrative assistants for C-suite executives, for example, are on the chopping block. Other areas include operations, tech support, human resources and customer service, Jyoti said.

Generative AI has played such a big role this year, because traditional AI had been the domain of highly technical workers, often within IT or at lower levels in business units, and so was not that visible within an organization, she explained.  “Generative AI has changed that, because it became front and center.” Jyoti said. “The C-suite, the board of directors, they all have come along, and are investing in AI and prioritizing AI. What I have seen this time that is different is that there’s a lot more appetite and interest, and worldwide.”

Generative AI is still too early for reporting on monetization

Other recent reports have shown that the promise of generative AI is real. Employees at one elite consulting firm, BCG, got a 40 percent performance boost from using GPT-4 on a variety of tasks, according to a study released last month by Harvard, Wharton and MIT.

It should be noted that it is too early to report on monetization results from using generative AI, however. “Most people are at the early stage of either evaluating, or piloting,” Jyoti said of generative AI projects. The results reported in the IDC study are for traditional forms of AI, she confirmed.

On average, organizations reported a 18% increase in results across key areas like customer satisfaction, employee productivity, and market share, when using AI, Jyoti said.

Despite the positive results, companies also reported a heightened concern around areas like data or IP loss, risk management, and lack of AI governance. While there were already governance concerns around traditional AI, the arrival of generative AI has increased those concerns, Jyoti said.

In March, Jyoti and her group at IDC projected that generative AI will add nearly $10 trillion to global GDP over the next 10 years.

Microsoft exec: Generative AI is “sort of bending the innovation curve”

In  a separate interview, Alysa Taylor, corporate vice president at Microsoft, said the company had commissioned the report in order to understand the potential for AI, and where companies were realizing the most benefit. She said the companies were using AI to tackle some of their largest challenges, and see generative AI as particularly transformative: “Generative AI is sort of bending the innovation curve,” she said. It’s allowing organizations not to have to modernize underlying technologies, but really kind of leapfrog in a faster way to time to market, time to value.”

She also called generative AI a catalyst, in particular because its simple form factor allows more people to access AI. The use cases abound, but she cited examples like healthcare, where physicians are suffering a burnout rate at 53 percent in the U.S., and where ambient AI and generative AI can help reduce the need for manual clinical documentation. In software development, AI can help assist and accelerate development. And in retail, AI can help companies more deeply understand a customer and to precisely target them, she said.

Here are other key findings and facts from the report:

• Organizations are realizing a return on their AI investments within 14 months, on average
• Copywriting, running simulations and automating business processes and workflows are the top three uses cases organizations are planning to monetize
• For every $1 a company invests in AI, it is realizing an average of $3.5X in return
• 62% of companies are already using generative AI, and 24 percent said they plan to use or invest in AI within the next 24 months
• 52% reported that their biggest barrier is a lack of skilled workers needed to scale AI initiatives
• Respondents were roughly evenly split between leaders in IT and line of business
• 66% of respondents were in upper-level management roles and 63% were responsible for decision making regarding the use of AI at their organization

Microsoft’s Taylor said Microsoft is trying to address that skills barrier by engaging more than six million people globally with its Learn program, and training 400,000 partners.