Wavestone Survey Shows GenAI is Having a Major Impact on Data Culture
While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to derive any substantial value from it. However, the GenAI hype has had a surprising effect on the organizations’ data and analytical culture.
In its 12th annual edition Data and AI Leadership Executive Survey, Wavestone has uncovered key findings about how GenAI is making companies more data-oriented. This year, 95.3 percent of the survey respondents included leaders from several Fortune 1000 companies, such as senior executives who hold the title of Chief Data and Analytics Officer (CDAO) or Chief Data Officer (CDO).
The Wavestone survey highlights that a high percentage of companies are doing research and development on GenAI, and this has had a significant positive impact on the attitude of the leadership toward data, analytics, and AI.
In the Foreword to this year’s survey Randy Bean, Innovation Fellow at Wavestone and Founder of NewVantage Partners, and Thomas H. Davenport, author of the landmark study Competing on Analytic, wrote ” Generative AI seems to have catalyzed more positive change in organizations’ data and analytical cultures than in any time since the inception of this survey.”
Wavestone is a business and digital consulting firm that supports organizations in delivering their most critical transformations. The Data and AI Leadership Executive Survey by Wavestone is widely recognized as the longest-running survey of Fortune 1000 and global data, analytics, and AI leaders.
In previous surveys by Wavestone, organizations reported a decline in data and analytics culture. However, in 2024, the percentage of data leaders saying their organizations had “established a data and analytics culture” went from 21 percent to 43 percent. This stunning change is the biggest improvement in the history of the Wavestone surveys.
The only major change between the 2023 and 2024 survey is the emergence of GenAI and this makes it the likely cause of the leap in positive response about data culture.
In previous years, the primary reasons for the decline in data and analytics culture include the failure to nurture data culture and the preference for investing in technology rather than culture. However, that has changed now as data leaders recognize the importance of culture and are realizing the return on investment in data culture.
Based on the survey, one of the most anticipated benefits of using GenAI is “exponential gains in personal productivity”. This exploration of how data and AI can be applied to work could be one of the reasons for the cultural change. Other reasons could be that the GenAI hype allowed people to believe that digital transformation is within reach and that data leaders’ enthusiasm and optimism about GenAI spread through the organization.
The findings of the survey also show that data leaders are aware of the challenges and risks posed by GenAI. They understand that safeguards and guardrails are needed to govern the use of GenAI. More than three in five (63 percent) of respondents shared that their organization has already established mechanisms to govern the use of GenAI.
There is also a threat that if GenAI is going through a “hype cycle” as predicted by Gartner, then we could through a “trough of disillusionment.” This means that the positive impact on data culture could start to subside.
To ensure this momentum doesn’t go away, organizations must continue to experiment with GenAI at an individual level. The companies also need to ensure they conduct organizational-level experiments on how to best use GenAI.
For a more lasting cultural change, organizations must be quick to put the GenAI system into production deployment. The Wavestone survey shows that only 5 percent of GenAI projects have reached the production phase. Another important step is to educate employees at all levels about GenAI to help foster an in-depth understanding of how to derive maximum value from the technology.
Much work needs to be done, however, if organizations are able to achieve some of these objectives, then we can expect to see more dramatic and permanent transformation in data culture.