AI and generative AI (GenAI) cannot function—let alone deliver trustworthy analysis—without well-vetted, quality data. Data executives across many leading organizations recognize that data has become the Achilles’ heel of AI. Yet, as far as they are concerned, AI is too important to pass up, and it’s still full speed ahead for AI and GenAI investments—despite near-term headwinds incurred by any lack of readiness of organizations’ data infrastructure and assets.
That’s the word from a recent survey of 600 data executives, which reveals that nearly all global data leaders show no signs of slowing down their AI initiatives, despite difficulties in demonstrating business value and overcoming data complexities.
The survey, conducted by Wakefield Research on behalf of Informatica, finds most organizations grappling with the existing challenges of data management while they press on with AI and GenAI.
For more than 4 in 10 executives (43%), data issues present an obstacle for moving AI projects into production.
Data challenges remain a top roadblock, with additional obstacles emerging as well, resulting in two-thirds (67%) being unable to successfully transition even half their GenAI pilots to production, the survey shows. “The innovation battlefield is littered with stalled or abandoned GenAI projects affected by a lack of AI fluency and data literacy among staff, difficulty demonstrating value and regulatory issues, as well as a lack of maturity and interoperability in some of the AI tech itself,” the survey’s authors write.
Once in production, demonstrating the value of AI to the business becomes another challenge. This stems from concerns with AI around its cybersecurity implications, responsible use, the reliability of results, and data quality, according to the survey. In response, 86% expect increased data management investment in the year ahead, with 44% citing data readiness for GenAI as primary driver of these investments. Data executives in the survey are also gearing up to enhance data governance, with 47% emphasizing data privacy and improving their workforce’s data maturity to use data and AI technology effectively and responsibly, the survey found.
Still, among 9 in 10 organizations that have adopted or plan to adopt GenAI, investments in the technology will continue on the upswing. The goals of such investments include improved operational efficiency (43%) and a better experience for customers (43%) and employees (39%).
Another challenge results from the bewildering variety of solutions now on the market to address data quality—from legacy data management vendors to a new generation of digital native startups.
In their efforts to prepare and boost data for the AI future ahead, data executives “are facing the daunting task of using many disparate tools and vendors, which could make the path forward more complicated,” the survey’s authors state. More than half of data executives (51%) anticipate needing 10 or more separate tools to support their 2025 data management priorities, the survey shows. More than a third (35%) will need 15 or more tools for this.
The survey notes, “A majority (59%) have pushed steadily forward with AI or even faced pressure to move faster with these projects.”
“[D]espite potential red flags, it’s full speed ahead for many companies on their journey to AI readiness,” the study’s authors conclude. “For data leaders, the hope is that the road ahead in 2025 leads to resolving a host of GenAI challenges—from overcoming AI’s inherent risks and navigating a hazy regulatory horizon to upskilling staff and doubling down on data privacy and quality to address critical roadblocks. Yet as investments in these technologies increase, so do expectations. Data leaders must temper exuberance from the top offices where the C-suite executives are expecting faster ROI from AI than what’s likely to happen.”