A recent report from the Massachusetts Institute of Technology (MIT), in collaboration with analytics firm ThoughtSpot, highlights the significant advantages that businesses adopting generative AI (GenAI) for data and analytics have realized. Titled “Generative AI for Data and Analytics: How Early Adopters are Reaping the Rewards,” this comprehensive study uncovers how these companies are leveraging GenAI to increase efficiency, drive higher returns on investment (ROI), and secure a competitive position in their respective markets.
The report surveyed 1,000 business and data leaders across North America, Europe, and Asia-Pacific. The results are enlightening: 67% of respondents are currently using GenAI for analytics purposes, while an additional 26% are planning to implement it shortly. The survey found that 44% of early adopters reported improvements in the speed of their data-driven decision-making processes and the quality of their products and services, thanks to GenAI.
Financial benefits are particularly noteworthy. Nearly half of early adopters (48%) anticipate achieving an ROI of 100% or more within three years, with around 12% expecting their returns to exceed 300% in the same period. This level of confidence is supported by the positive outcomes many companies have already observed.
One of the most compelling benefits of GenAI revolves around its ability to streamline decision-making. The report indicates that 37% of early adopters feel they are ahead of their competitors due to improved analytics. These businesses highlight that effective collaboration between business and data teams is paramount to realizing such advantages. A staggering 75% of early adopters report strong partnerships alongside a centralized strategy that aligns their business objectives with data analytics capabilities. In contrast, less than half (47%) of organizations still in the adoption planning stage have cultivated similar alignment, underscoring the competitive edge enjoyed by early implementers.
The importance of technical skills cannot be overstated in this context. Data modeling skills are deemed critical by 49% of respondents, while natural language processing (NLP) is prioritized by 41% of early adopters, compared to only 28% of those still in preliminary planning stages. This suggests that early adopters not only leverage GenAI but also strive to exploit advanced features like NLP effectively.
Furthermore, the report emphasizes the role of third-party generative AI tools. Over half (52%) of successful early adopters use external tools for their analytics, compared to just 32% among those still contemplating adoption. This strategic approach allows organizations to optimize internal resources while tapping into external expertise, which can significantly enhance their deployment capabilities.
It is essential, however, to note that human oversight remains critical within GenAI implementations. Experts underscore the necessity of human involvement to monitor AI outputs, rectify errors, and mitigate biases. This level of oversight is crucial to fostering trust in AI systems and ensuring the reliability and accuracy of AI-generated insights.
Cindi Howson, Chief Data Strategy Officer at ThoughtSpot, emphasized the report’s key findings by stating, “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, and 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, reaches a clear conclusion: integrating GenAI into data and analytics processes is not only beneficial but essential for businesses that wish to remain competitive. Through a global online survey and insights from expert interviews, the report presents a cohesive picture of the current trends in generative AI usage and its future priorities.
In summary, the findings suggest that businesses willing to adopt generative AI technologies early can expect considerable financial rewards. Enhanced collaboration between teams, the application of advanced skills, and the strategic use of external AI tools further contribute to creating a robust data-driven culture. As competitors look to innovate and transform, the question remains: will your organization seize the opportunity or watch from the sidelines?
