Dive Brief:
- Enterprises want to level hurdles that stand in the way of generative AI ambitions, starting with security, costs and data, according to Enterprise Strategy Group research sponsored by Hitachi Vantara.
- More than 3 in 5 organizations have significant gaps in AI readiness when it comes to infrastructure and data ecosystems, the survey of 800 IT decision-makers published Tuesday found.
- Nearly three-quarters agreed their infrastructure needs modernization before pursuing generative AI projects.
Dive Insight:
Organizations are bullish on what AI can do for their operations long-term, but most aren’t ready for widescale adoption just yet.
More than half of AI decision-makers are worried about IT teams’ keeping up with the pace of innovation driven by generative AI, according to the Hitachi Vantara report. Enterprises have a lengthy list of to-do’s, from improving data processes and strengthening infrastructure to adapting risk mitigation frameworks.
Even so, nearly two-thirds say they have identified at least one use case for generative AI.
“Enterprises are clearly jumping on the GenAI bandwagon, which is not surprising, but it’s also clear that the foundation for successful GenAI is not yet fully built to fit the purpose and its full potential cannot be realized,” said Ayman Abouelwafa, CTO at Hitachi Vantara, in the report.
For tech leaders and organizations that are moving forward on projects, measuring success isn’t uniform.
Around 2 in 5 enterprises track progress based on a qualitative impact analysis, accuracy of generative AI responses or user/process quantitative benefits. Slightly less — 38% — are looking at cost savings as a success marker.
The push for ROI is expected to grow as AI initiatives command a larger percentage of enterprise budgets.
