Even AI laggards can see triple return on investment

Wednesday at 01:05 PM

Boosting employee productivity is regarded as one of the big wins when deploying generative artificial intelligence (GenAI) technology, a survey has reported.

However, in the next 24 months, a greater focus will be placed on functional and industry use cases.

The study from IDC based on a poll of 3,476 people reported that 43% believe the productivity use case currently delivers the greatest return on investment. The survey, commissioned by Microsoft, found that for every $1 invested in GenAI, organisations, on average, achieved a 3.7-fold return on that investment.

IDC defines an AI leader as an organisation whose enterprise-wide AI strategy is aligned to business goals and whose reimagined business models repeatedly create business value.

The analyst reported that respondents who identified as leading the way with GenAI say they are seeing a 10-fold return on their initial investment.

On average, AI deployments are taking less than eight months, and organisations are realising value within 13 months. But when looking at the speed with which an AI initiative generates value, 29% of the AI leaders polled implement AI in less than three months versus laggards at 6%.

Yet even in those organisations that are classed as AI laggards, the return on investment is, on average, almost three times the initial outlay. When broken down by region, IDC reported that North America had the least number of AI laggards (16%), while the proportion of AI laggards in Western Europe (31%) and Asia-Pacific (32%) is almost double.

Moody’s Analytics, one of the Microsoft customers quoted in the report accompanying the survey results, has used Microsoft Azure OpenAI to help democratise access to market data.

“Moody’s provides information on financial markets to help customers make informed investment decisions,” said Nick Reed, chief product officer at Moody’s Analytics.

“With GenAI, we are democratising access to that content in a powerful way for our customers. For example, Moody’s Research Assistant, built on Microsoft Azure OpenAI, helps customers generate insights from our credit research, data and analytics. The tool has saved users up to 25% of the time typically spent on tasks performed by financial analysts.”

While the use of a pre-built AI such as Microsoft Copilot is predominant today, the IDC poll reported that organisations are planning to either customise a pre-built AI or use a custom-built AI in the next 24 months. In fact, while 43% of survey respondents say they are currently using pre-built AI today, this figure drops by 18% when asked about their plans over the next 24 months.

The survey shows that while just under a fifth (19%) of the people polled say their organisations are building custom AI today, when asked about their plans over the next 24 months, there is a significant jump (to 36%) in the proportion of organisations planning to go down the custom AI route.

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