Generative AI is having a significant impact on businesses, transforming them in ways that lead to impressive returns on investment (ROI), according to a joint survey by Dataiku and Databricks. The survey, titled AI, Today, reveals that over 70% of senior AI professionals have reported positive ROI for their data science, analytics, and AI initiatives. In fact, more than half of them reported a return of at least 2 times their investment, while 5% claimed returns exceeding 10 times.
The arrival of OpenAI’s ChatGPT has propelled generative AI into the mainstream, sparking enthusiasm among professionals in the data and AI fields. Dataiku and Databricks sought to understand the extent of this enthusiasm and gain insights into the broader AI landscape. The survey explores various aspects such as tech stacks, AI tools and services spending, and the reach of generative AI use cases.
The report highlights that the leaders in data, analytics, and IT functions will be instrumental in integrating generative AI as a routine technology in the workplace. Three out of five survey respondents believe that companies need AI to fully unlock the value of their data.
Notably, the survey indicates that businesses are embracing generative AI, with 64% of respondents planning to utilize generative AI or large language models within the next year. Additionally, 45% of those surveyed stated that they are already experimenting with generative AI. The survey also reveals heavy investment in AI resources, with 47% of respondents reporting budgets of over $5 million for AI tools in the coming year. Furthermore, 17% of respondents anticipate AI budgets exceeding $20 million.
Jepson Taylor, Chief AI Strategist at Dataiku, emphasizes that AI and data science are delivering tangible results, even amid high expectations and extensive market attention. Taylor notes that AI pioneers are achieving clear bottom-line results that would impress any CFO. However, Taylor also points out that these pioneers seek the right AI tools and platforms to rapidly turn their vast amounts of data into game-changing outcomes, while considering potential risks.
The survey identifies data quality and deployment speed as the top barriers to AI adoption, as cited by the respondents. Surprisingly, cost and a lack of business use cases were considered the least significant obstacles to extracting greater value from AI.
The report draws interesting comparisons between AI pioneers, who have successfully implemented AI and acquired substantial returns, and AI laggards, who are still experimenting or experiencing lower returns. It reveals that AI pioneers are 62% more likely to have at least one data leader in their C-suite (70% versus 43% in nascent organizations). Additionally, AI laggards are 43% more likely to lack clear owners responsible for data quality, with 56% of laggards reporting unclear ownership compared to 39% of pioneers.
While the rapid proliferation of generative AI brings numerous benefits, it also raises concerns. AI models can generate text and images that are inaccurate, biased, or even harmful. The survey findings show that 55% of AI leaders believe that fears surrounding AI are justified, expressing more concern than excitement about AI’s future. Similarly, 55% of respondents called for official regulation of AI.
The results of the survey underscore the significant interest in generative AI alongside the challenges it presents, such as data access, privacy, and regulation. Prem Prakash, Head of AI Marketing at Databricks, emphasizes the shared mission of Dataiku and Databricks to democratize data and AI in a secure and cost-effective manner as they navigate these challenges.
In conclusion, generative AI is driving transformative change in businesses, delivering positive ROI for data science, analytics, and AI initiatives. Companies are increasingly adopting generative AI and investing heavily in AI resources. However, challenges related to data quality, deployment speed, and potential risks remain. As the technology advances, striking the right balance between innovation and responsibility will be crucial to harnessing the full potential of generative AI.
