A recent MIT report in collaboration with ThoughtSpot highlights the notable advantages for early adopters of generative AI (GenAI) in data and analytics. This research is crucial for businesses keen on leveraging AI to improve their operations and prevents falling behind in this fast-paced environment.
Titled “Generative AI for Data and Analytics: How Early Adopters are Reaping the Rewards,” the report explores how businesses are effectively utilizing GenAI to enhance their data strategies, achieve significant returns on investment (ROI), and gain a competitive edge in their markets. Surveying 1,000 business and data leaders across different regions, including North America, Europe, and Asia-Pacific, the findings reveal that 67% are currently using GenAI for analytics purposes, with an additional 26% planning to implement it shortly.
One of the most compelling insights from the report is the impact of GenAI on decision-making processes. About 44% of early adopters have noted that GenAI has significantly expedited their data-driven decision-making and improved the quality of their products and services. This improved efficiency can be critical in today’s fast-paced market, where timely, accurate decisions can differentiate successful companies from their competitors.
The financial implications of adopting GenAI are particularly noteworthy. Nearly half (48%) of the early adopters forecast an ROI of 100% or more within three years. Remarkably, around 12% of these businesses project their ROI could exceed 300%. These figures are not mere estimates; many companies have already started experiencing positive results from their GenAI initiatives.
One crucial advantage of GenAI is its capability to facilitate faster and more precise decision-making. More than a third (37%) of early adopters feel that this technology has provided them with a competitive upper hand in their respective markets. Key to mastering GenAI for analytics, according to the report, is the alignment of business and data teams, enhancing technical skills, and collaborating with experts in the field.
This necessity for collaboration is further emphasized in the report, which found that 75% of early adopters have established robust partnerships and a centralized strategy that aligns their business objectives with their data capabilities. In stark contrast, less than half (47%) of those still planning to adopt GenAI have managed to achieve similar cohesion, highlighting the competitive advantage of the early adopters.
Technical skills are paramount in maximizing the potential of GenAI. The report outlines that 49% of respondents underscored the importance of data modeling, while 41% prioritized natural language processing (NLP). In contrast, only 28% of those in the planning stages recognize the significance of NLP. This indicates that not only are early adopters deploying GenAI, but they are also harnessing advanced capabilities such as NLP to derive more value from their analytics.
Utilizing third-party generative AI tools also plays a critical role in the success of early adopters. Over half (52%) of these organizations are leveraging external tools for their analytics needs, compared to only 32% among businesses still in the planning phase. This strategic move allows companies to optimize their internal resources and tap into external expertise to effectively scale their AI deployments.
Despite the numerous advantages, the report cautions against overlooking the necessity of human oversight in GenAI implementations. Experts advocate for maintaining human involvement to monitor AI outputs, correct potential errors, and address unintended biases. Such oversight is essential for fostering trust in AI systems, ensuring the quality and accuracy of AI-generated insights.
Cindi Howson, Chief Data Strategy Officer at ThoughtSpot, commented on the report’s findings: “For decades, data has been locked away in the hands of 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.”
In conclusion, the integration of generative AI into data and analytics processes is no longer optional for businesses keen on maintaining competitiveness. The MIT report underscores the remarkable returns that early adopters are realizing and the strategies that contribute to their success. The insights gathered from the study not only spotlight the tangible benefits of GenAI but also offer a roadmap for organizations preparing to embark on their AI journey.
