Solely 12% of organizations really feel prepared for agentic AI workflows, regardless of vital investments, underscoring crucial information and infrastructure challenges
Qlik, a worldwide chief in information integration, information high quality, analytics, and synthetic intelligence, at the moment introduced findings from an IDC survey exploring the challenges and alternatives in adopting superior AI applied sciences. The research highlights a major hole between ambition and execution: whereas 89% of organizations have revamped information methods to embrace Generative AI, solely 26% have deployed options at scale. These outcomes underscore the pressing want for improved information governance, scalable infrastructure, and analytics readiness to completely unlock AI’s transformative potential.
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The findings, printed in an IDC InfoBrief sponsored by Qlik, arrive as companies worldwide race to embed AI into workflows, with AI projected to contribute $19.9 trillion to the worldwide financial system by 2030. But, readiness gaps threaten to derail progress. Organizations are shifting their focus from AI fashions to constructing the foundational information ecosystems needed for long-term success.
Stewart Bond, Analysis VP for Knowledge Integration and Intelligence at IDC, emphasised: “Generative AI has sparked widespread pleasure, however our findings reveal a major readiness hole. Companies should tackle core challenges like information accuracy and governance to make sure AI workflows ship sustainable, scalable worth.”
With out addressing these foundational points, companies danger falling into an “AI scramble,” the place ambition outpaces the power to execute successfully, leaving potential worth unrealized.
“AI’s potential hinges on how successfully organizations handle and combine their AI worth chain,” mentioned James Fisher, Chief Technique Officer at Qlik. “This analysis highlights a pointy divide between ambition and execution. Companies that fail to construct methods for delivering trusted, actionable insights will rapidly fall behind opponents shifting to scalable AI-driven innovation.”
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The IDC survey uncovered a number of crucial statistics illustrating the promise and challenges of AI adoption:
- Agentic AI Adoption vs. Readiness: 80% of organizations are investing in Agentic AI workflows, but solely 12% really feel assured their infrastructure can help autonomous decision-making.
- “Knowledge as a Product” Momentum: Organizations proficient in treating information as a product are 7x extra prone to deploy Generative AI options at scale, emphasizing the transformative potential of curated and accountable information ecosystems.
- Embedded Analytics on the Rise: 94% of organizations are embedding or planning to embed analytics into enterprise purposes, but solely 23% have achieved integration into most of their enterprise purposes.
- Generative AI’s Strategic Affect: 89% of organizations have revamped their information methods in response to Generative AI, demonstrating its transformative impression.
- AI Readiness Bottleneck: Regardless of 73% of organizations integrating Generative AI into analytics options, solely 29% have totally deployed these capabilities.
These findings stress the urgency for firms to bridge the hole between ambition and execution, with a transparent give attention to governance, infrastructure, and leveraging information as a strategic asset.
The IDC survey findings spotlight an pressing want for companies to maneuver past experimentation and tackle the foundational gaps in AI readiness. By specializing in governance, infrastructure, and information integration, organizations can notice the complete potential of AI applied sciences and drive long-term success.
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