Hitachi Vantara: Enterprises Still Struggling with AI Adoption
Enterprises are looking for ways to smooth out the hurdles that stand in the way of generative AI ambitions, starting with security, costs and data, according to a report led by Hitachi Vantara.
According to the survey of 800 IT decision makers, more than three out of five organizations have significant gaps in AI readiness when it comes to infrastructure and data ecosystems. Nearly three-quarters agreed their infrastructure needs modernization before pursuing generative AI projects.
More than half of AI decision-makers are worried about whether their IT teams can keep up with the pace of innovation driven by generative AI, especially given the fact that enterprises have a lengthy list of action items, ranging 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.
Around 40% of 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.
Channel Impact®
Channel partners need to help their customers establish better security, quality and flexibility from their data foundations to meet generative AI goals. While organizations are bullish on what AI can do for their operations long-term, most are not yet ready for widescale adoption.
Stay in the Know
Keep tabs on what’s happening in the channel and the impact it will have on the partner community by subscribing to Channel Impact communications.
Recent News
Search Buzz
Buzz Categories