While the pace of GenAI development across organizations in every sector is unquestionably rapid, you only have to look at the announcements from the Cloud Wars Top 10 to see the enthusiasm for and commitment to the technology; determining implementation statistics takes a little more digging. As does the ROI of the still relatively new technology category.
However, implementation and ROI are intrinsically linked. If the ROI of GenAI investment proves to be as good as is expected, then implementation will no doubt soar, helping justify the billions of dollars plowed into development.
Now, we are a step closer to understanding the ROI of GenAI with the significant findings from new research by Snowflake. “The Radical ROI of Generative AI” global research report has found that 92% of early adopters have seen ROI from their AI investments, but that’s just the tip of the iceberg.
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What Does the Research Reveal?
The report, developed in collaboration with the Enterprise Strategy Group, includes responses from 1,900 global business and IT leaders. While there is a consensus that GenAI tools benefit businesses, the nuances of this perspective vary depending on the respondents’ geographic locations.
The research revealed a strong correlation between an organization’s focus on AI efforts, the ROI, and their nation’s AI maturity. For instance, German respondents reported a 34% ROI on their AI investments, citing infrastructure issues as a key hurdle. In contrast, U.S. respondents reported a 43% ROI and described themselves as “very successful” in operationalizing AI technologies.
Key findings include:
93% of respondents say AI initiatives have been very or mostly successful
92% say AI investments are paying for themselves
98% will invest more in AI in 2025.
Two-thirds see returns of $1.41 on the dollar
Despite the positive figures, stumbling blocks were identified, particularly in finding proper use cases. For example, 71% of early adopters report having more potential use cases than they can afford to pursue. The pressure to select the right ones is significant too, as 59% of interviewees believe supporting the wrong use cases could lead to being laid off.
Closing Thoughts
The Snowflake report highlighted the crucial role of data in the AI boom, revealing that 80% of respondents were fine-tuning models using proprietary data. However, many surveyed encountered significant barriers in key areas such as data integration, governance, data quality, data preparation, and storage.
“The rapid pace of AI is only accelerating the need for organizations to consolidate all of their data in a well-governed fashion,” said Artin Avanes, head of core data platform, Snowflake, and Snowflake provides a platform that has been tailor-made for organizations to do just this.
However, from a broader perspective, this report reveals even more opportunities. Snowflake has clearly outlined the ROI of GenAI investment, which isn’t always easy to articulate, while also focusing on the challenges related to unified data necessary to achieve this ROI.
There are other obstacles and challenges that can be addressed with enterprise-grade solutions—not only in data but also in infrastructure, security, and beyond. Organizations should adopt a two-pronged approach to assess the impact of GenAI, asking not only what the potential return is but also what obstacles are preventing progress and, crucially, how they can assist in overcoming these challenges.
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