Education, government and healthcare lag behind all other industries in Gen AI deployment
Hakkoda, a cloud data engineering consultancy specializing in Snowflake, released its 2024 Generative AI State of Data Report. The findings show 50% of organizations are already using AI for automation, but sophisticated use cases like AI copilots, ETL/ELT, and schema matching and integration are significantly less common. The use of AI to automate decision-making was identified as a top challenge for 45% of organizations.
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The Generative AI State of Data report surveyed 500 data leaders from large organizations across major industries. Respondents hold director-level or higher positions in IT and analytics roles at US companies with 1,000 or more employees in the following sectors: Distribution/Supply Chain, Education, Entertainment, Financial Services, Government, Healthcare, Manufacturing, Retail, and Telecommunications.
The manufacturing sector is consistently outperforming other industries when it comes to Generative AI deployments. Manufacturing organizations ranked first in nearly every Generative AI application, with high confidence levels in their use cases and internal capabilities to match. With an overall Generative AI deployment rate of 50%, manufacturing orgs were also the most likely to be using Generative AI tools for data cleaning and processing (71%) and for cataloging (59%). Education, government, and healthcare organizations came in behind other industries in their Generative AI deployments and reported the lowest rates of confidence in having implementable Generative AI use cases.
Among the Generative AI State of Data 2024 report findings:
- 74% of organizations intend to implement a centralized cloud platform in 2024
- 79% of organizations indicate the need for a “moderate” to “large” amount of outside help to modernize
- 48% of organizations said enabling Generative AI capabilities was a top reason for transitioning to a centralized cloud platform
- 56% of the most data-mature organizations have implemented Generative AI use cases
- 32% of executives report that they felt “extremely confident” in the ability of their organizations to build necessary Generative AI capabilities internally
A whopping 95% of surveyed organizations say Generative AI will be critically important to their success by 2027, and 85% expect to have implemented Generative AI tools by the end of 2024.
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Hakkoda’s 2024 Generative AI State of Data Report also indicates that:
- Gen AI Is a Top Driver of Modernization in 2024 — 94% of companies said they need to modernize their data stack. Only 29% of organizations report they have transitioned to a centralized data cloud platform and just 42% indicate they are already using Generative AI tools. As organizations look to close that gap in 2024, 45% of companies plan to begin using a primary cloud platform this year, with another 23% predicted to join them in 2025. Only 3% of organizations have no plan to make the transition. Of those who had already made the jump to a centralized cloud platform in 2023, 48% said enabling Gen AI capabilities was a top reason for transitioning.
- Top Gen AI Performers Are Large Enough to Invest, but Small Enough to Stay Agile — $10B organizations demonstrate higher AI usage rates than other orgs, but also report higher rates of dependence on legacy technology. Organizations with less than $500 million in revenue surprisingly reported higher usage rates than much larger companies. Organizations with 10,000 to 24,999 employees represent the sweet spot of AI deployment, outpacing larger and smaller organizations alike with a 49% usage rate. These organizations were 33% more likely to be deploying Gen AI than their larger peers, leading all organizations of any size in that capacity.
- Organizational Dissonance is the Biggest Threat to Gen AI Success — Executive and C-level team members were 32% more likely to report that they felt “extremely confident” in their internal data teams’ ability to build necessary Gen AI capabilities than lower levels of leadership. Executive and C-level team members were much more likely than lower-level leadership to report that their data teams frequently developed creative ideas for automating processes—a crucial factor to ensure successful implementation of Generative AI tools. Only 4 in 10 organizations strongly agreed that they have the skills and expertise to support the use of Gen AI.
- Gen AI Tools Can Build Upon Consistent ROI on Investments — More than half of the most data-mature organizations had already begun using AI tools in 2023, and this year 84% of all orgs are set to begin deploying them. Organizations across industries reported an average ROI of 126% on data tech investments in 2023—a number that jumped to 164% among data-mature orgs. While 50% of orgs are already using AI for automation, far fewer are tapping into the potential of more sophisticated functions like AI copilots, ETL/ELT, and schema matching and integration. While companies are more likely to be using AI for automation, applying AI to automate decision-making was a top challenge for 45% of organizations in 2023, trailing only data quality and governance.
“The Generative AI State of Data 2024 report shows that the true winners of generative AI will be organizations that take a strategic approach to implementation, investing in both the modernization and the long-term data strategy that will allow their business to radically alter day-to-day operations,” said Erik Duffield, CEO at Hakkoda. “A data strategy that aligns everyone from the C-suite to the most granular engineering functions around a clear set of goals, investment requirements, and well-defined obstacles is essential to continuing to grow and expand with generative AI in the years ahead.”
The Generative AI State of Data report was drawn from a study conducted on behalf of Hakkoda by Lawless Research in December 2023 as a blind survey of 500 director to CEO level data leaders from large organizations across major industries. 20% of respondents came from organizations with less than $500M annual revenue; 29% with $500M to $999.9M annual revenue; 37% with $1B to $9.9B annual revenue; 14% with $10B or more annual revenue.
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