Dive Brief:
- As enterprises plan to expand AI adoption, leaders have a renewed focus on how data is managed and governed, according to a Harris Poll survey published Wednesday. The market research company surveyed more than 300 technology decision-makers earlier this year on behalf of data intelligence platform provider Collibra.
- Nearly 90% of leaders surveyed said protecting data privacy was their top concern with AI initiatives. More than 4 in 5 decision-makers said data ownership has shifted over the last year as AI efforts increased.
- “Previously, maybe you had data responsibility sitting at a domain level,” Stijn Christiaens, co-founder and chief data citizen at Collibra, told CIO Dive. “Whereas now, because of AI, it is getting more executive visibility.”
Dive Insight:
Data had enterprise prominence before the recent AI wave, but business leaders now have a sense of urgency to get governance on the right track. Executives don’t want their AI efforts to go to waste, and bad data management can put AI goals further out of reach.
Implementation roadblocks are already impeding progress. Two-thirds of businesses say they are stuck in generative AI pilot phases, unable to transition experiments into production, according to an Informatica report published earlier this year. Around 3 in 5 leaders said they face pressure to move projects along faster.
“A lot of the risks associated with AI are data risks: bad quality, ownership, privacy,” Christiaens said. “If you only focus on the opportunity… and don’t take into account the risks, you’re making a big mistake.”
CIOs can help their organizations upgrade data processes before wasted spend accumulates and pilots gather dust by leading an assessment of existing practices and identifying areas of improvement. Technology leaders should also engage other c-suite members to underline the importance of data lineage, diversity and quality, analysts have told CIO Dive.
Enterprises must consider compliance and legal implications when updating data practices. High-risk use cases will require more guardrails than their lower-risk counterparts, for example. Businesses, such as The Wendy’s Company and EY, have also turned to synthetic data for more privacy protection.