According to a new report, 60 percent of respondents claim that their organization is failing to keep pace with data changes resulting from AI demands.
In addition, the study from Immuta shows that traditional data architecture challenges persist, with nearly half of organizations identifying compliance and privacy as primary data concerns, and 64 percent citing significant challenges in providing timely and secure access to data for authorized users.
“Legacy systems for provisioning data access are broken,” says Matthew Carroll, co-founder and CEO at Immuta. “The core issue revolves around change management focused on three factors: people, processes, and technology. But as the number of users — both human and non-human — continues to grow, and as they ask more questions and demand more access than ever before, enterprises are struggling to keep pace. Manual processes can no longer scale to meet the need for secure, timely access to data. The only way to enable faster decision-making — which could be the catalyst for a new life-saving drug discovery, preventing costly fraud scams, or even saving lives on the battlefield — is by putting an emphasis on establishing proven best practices for how data is provisioned as a core part of IT and business strategy.”
The report also finds that 64 percent of data leaders say that data access challenges have significantly impacted the ROI of their organization’s platforms. Data access issues create tangible downstream effects on business performance, including missed internal goals (31 percent), lost revenue (30 percent), and an inability to collaborate with other lines of business or external partners (30 percent) as the biggest impacts.
Three-quarters of organizations are likely to implement AI/ML applications in the next 12 months and 47 percent believe that this AI/ML integration will have a high impact on business outcomes. Despite this optimism surrounding AI deployments, 55 percent of data leaders believe their data security strategy is failing to keep pace with the evolution of AI, up from 50 percent reported in last year’s report. These factors, including difficulty integrating AI into existing systems (46 percent), a shortage of skills necessary to manage AI systems (39 percent), and overly complex data access controls (29 percent) are slowing AI adoption cycles and putting organizations at a significant competitive disadvantage.
You can read more on the Immuta site.
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