Early adopters of generative AI see high returns, MIT reports

A recent report published by MIT, in collaboration with ThoughtSpot, reveals substantial benefits for early adopters of generative AI (GenAI) in data and analytics.

The report, titled "Generative AI for Data and Analytics: How Early Adopters are Reaping the Rewards," outlines how these companies are leveraging GenAI to enhance their data strategies, achieve significant returns on investment (ROI), and gain competitive advantages.

Surveying 1,000 business and data leaders across North America, Europe, and Asia-Pacific, the findings demonstrate that 67% of respondents are actively using GenAI for an analytics use case, with an additional 26% planning to implement it soon. Moreover, 44% of early adopters report that GenAI has notably improved the speed of their data-driven decision-making processes and the quality of their products and services.

The study's findings spotlight the financial benefits associated with GenAI adoption. Nearly half (48%) of early adopters expect to achieve an ROI of 100% or more within three years, and approximately 12% anticipate their ROI to surpass 300% in the same timeframe. These expectations are reinforced by the positive results that many companies have already witnessed.

One of the key advantages identified is the ability of GenAI to facilitate quicker and more accurate data-driven decisions. This capability has placed over a third (37%) of early adopters ahead of their market competitors. The report reveals that aligning business and data teams, developing essential technical skills, and collaborating with experts are critical to mastering GenAI for analytics.

The success of GenAI also hinges on the collaboration between business and data teams. The majority of early adopters (75%) report strong partnerships and a centralised strategy that aligns their business objectives with their data analytics capabilities. In comparison, less than half (47%) of those still planning to adopt GenAI have attained similar alignment, emphasising the competitive edge enjoyed by the early adopters.

Technical skills such as data modelling are cited as crucial, with 49% of respondents acknowledging its importance. There is also a significant recognition of the value of natural language processing (NLP), with 41% of early adopters prioritising it, compared to only 28% of those still in planning stages. This suggests that early adopters are not only deploying GenAI but also understanding how to make the most of it through advanced capabilities like NLP.

The report also underscores the benefits of using third-party generative AI tools. Over half (52%) of successful early adopters are utilising external tools for analytics, compared to 32% of those still planning. This strategic decision allows companies to optimise their internal resources and leverage external expertise to scale their deployments effectively.

However, the report stresses the importance of human oversight in GenAI implementations. Experts highlight the necessity of having humans in the loop to monitor AI outputs, correct errors, and mitigate unintended biases. This human intervention is vital in fostering trust in AI systems and ensuring the quality and accuracy of AI-generated insights.

Cindi Howson, Chief Data Strategy Officer at ThoughtSpot, commented on the findings: "For decades, data has been locked away in the hands of the expert analysts, and the wider industry has had a $100 billion price to pay for this annually. Now, the gap between those who are adopting generative AI for analytics and those who aren't is stark. With generative AI, organizations have the opportunity to deliver a data strategy more focused on business outcomes that delivers unprecedented value. Yet, success isn't guaranteed. It's a fast-evolving era, I encourage organizations to leverage lessons from early adopters that include both technology and people considerations."

The MIT SMR Connections report, conducted in the spring of 2024, concludes that the integration of GenAI into data and analytics processes is not just beneficial but essential for businesses aiming to remain competitive in their respective markets. The researchers gathered data through a global online survey and supplemented their findings with insights from interviews with experts, providing a comprehensive overview of current trends and future priorities in the use of generative AI.