TRENDING similar alignment , underscoring the competitive edge that early adopters gain through prioritizing collaboration across the organization .
Both early adopters and planners recognize the importance of key technical skills for creating or customizing generative AI solutions – with data modeling cited as the most critical ( 49 %) by all respondents .
However , a notable difference emerges in their prioritization of natural language processing ( NLP ): many ( 41 %) of the early adopters view NLP as a top priority , compared to just a limited share ( 28 %) of planners . This divergence suggests that early adopters , having already deployed the technology , understand NLP ’ s potential to accelerate data-driven decisionmaking , positioning them to better attract and develop talent for effective use of GenAI .
The findings of the report also highlight the value of choosing the right tools and collaborating with external experts to enhance business outcomes .
Over half ( 52 %) of successful early adopters are leveraging third-party GenAI tools for analytics , compared with a smaller share ( 32 %) of planners . By relying on strategic partnerships and external expertise , early adopters are optimizing their resources , while minimizing the time and effort required from their internal teams as they scale their deployments .
Finally , as GenAI is a new technology , experts interviewed in the report emphasize that it ’ s important to keep humans in the loop to monitor its output and make necessary changes . Having humans review AI-generated content provides opportunities to correct the technology ’ s mistakes and avoid problematic use cases or unintended biases . In turn , this helps train the models , promotes trust and enables humans to correct errors or misinterpretations closer to the source .
Thoughts from the Top Methodology
“ 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 GenAI for analytics and those who aren ’ t is stark ,” said Cindi Howson , Chief Data Strategy Officer , ThoughtSpot .
“ With GenAI , 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 includes both technology and people considerations .”
MIT SMR Connections conducted a global online survey , sponsored by ThoughtSpot , that drew responses from 1,000 data and business leaders from companies of various sizes in a broad range of industries and locations . Kadence International fielded the survey in the spring of 2024 . The data was examined based on respondents ’ roles , geographical locations , company size and other factors . To provide a rich context for discussion of the quantitative research results , MIT SMR Connections interviewed several authors , academics , consultants and industry practitioners . These individuals provided insight into current trends and future priorities about the use of GenAI for data and analytics . p
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