Dive Brief:
- Enterprise AI projects hinge on good data practices, but IT leaders still run up against challenges and the complexity is only increasing, according to an Ocient report published Wednesday, which surveyed more than 500 IT and data leaders.
- Technology chiefs point to data quality and the scalability of existing solutions as critical barriers to tapping into AI’s potential in their organization. More than 4 in 5 of IT leaders say ongoing AI efforts have significantly increased the complexity of their data processing requirements.
- Data estate expansion is also a pain point. Nearly half of leaders surveyed said their data estates were growing too fast, and 46% said the cost accompanying initiatives is a primary challenge. One-third of technology leaders don’t feel fully prepared for the increased scale and complexity introduced by AI.
Dive Insight:
CIOs would like to bulldoze through roadblocks to AI success, but some challenges are more arduous than others. The complexity accompanying widescale, comprehensive data strategies is one of the more stubborn barriers to success.
“Enterprises really need to ensure their data foundations are strong,” Eden Zoller, chief analyst of applied AI at Omdia, told CIO Dive. “A lot of enterprises still have fragmented data across different departments and functions, stored in inconsistent formats prone to inaccuracies.”
Data has been a critical topic for the C-suite for years, but challenges have been amplified by the rush to adopt AI. CIOs who can help their enterprise avoid wasted resources and failed pilots by identifying and addressing critical gaps are invaluable in the pursuit of AI gains.
“You cannot make full use of AI within your enterprise if you don’t … understand your data, contextualize your data and have a strategy in place around unstructured data,” said Leo Gergs, principal analyst at ABI Research. “It will define the success of every company.”
To chart a path forward, CIOs need to take stock of where processes are currently. C-suite leaders can collaborate to define desired outcomes and set their teams on the right track.
Understanding where fragmentation is occurring can be a valuable place to start, Gergs said.
“There’s some of the less advanced methods, like pen and paper,” Gergs said. “Some data is still stored on floppy disks. That gives you an idea of how fragmented this landscape is at the moment.”
CIOs must also recognize the cost-driven nature of conversations to get other C-suite and board members to support with the level of investment needed.
“If you can prove the business case and a reliable return on investment, that is worth a lot with many of these enterprises operating in harsh environments,” Gergs said.
Getting C-suite alignment on improving data processes won’t be hard for most organizations, despite the economic conditions. Appetite for AI has only increased over the past few years, and leaders see the technology as a way to alleviate pressure and drive efficiencies.
“It’s important, as well, to take your workforce on that journey,” Gergs said. “It needs to be a combination of a top-down, bottom-up approach … because you need buy-in from both directions.”
Businesses have begun to reap the rewards of sustained focus on data governance and strategy. American Honda, Expedia Group and CarMax have all touted AI-related benefits as a result of their efforts to strengthen data processes.
Disclosure: Informa, which owns a controlling stake in Informa TechTarget, the publisher behind CIO Dive, is also invested in Omdia. Informa has no influence over CIO Dive’s coverage.
