AI readiness falls short of ambitions: Research highlights key gaps that threaten the success of generative AI

A Qlik(IA), a global company in data integration, data quality, analytics and artificial intelligence, announced the results of an IDC survey exploring the challenges and opportunities in adopting advanced AI technologies. The study highlights a significant gap between ambition and execution: while 89% of organizations have renewed data strategies to embrace generative AI, only 26% have implemented solutions at scale. These results underscore the urgent need to improve data governance, scalable infrastructure and analytics readiness to fully unlock the transformative potential of AI.

The findings, published in a Qlik-sponsored IDC InfoBrief, come at a time when companies around the world are racing to incorporate AI into workflows, with the projection that AI will contribute US$ 19.9 trillion to the global economy by 2030. However, readiness gaps threaten to derail progress.

“A Generative AI has sparked widespread enthusiasm, but our findings reveal a significant gap in readiness. Enterprises must address key challenges such as data accuracy and governance to ensure that AI workflows generate sustainable and scalable value”, said Stewart Bond, Research Vice President for Data Integration and Intelligence at IDC.

Without addressing these basic issues, companies risk falling into a frenetic “race by the” AI, in which ambition outperforms the ability to execute effectively without potential value being achieved.

“The potential of AI depends on how effectively organizations manage and integrate their AI value chain”, says James Fisher, Chief Strategy Officer at Qlik.“This research highlights a clear divide between ambition and execution.Companies that fail to build systems to deliver reliable and actionable insights will quickly lag behind competitors that are migrating to AI-driven scalable innovation.”

IDC research has revealed several key statistics illustrating the promise and challenges of AI adoption:

^Ado de Agentic AI X Readiness: 80% of organizations are investing in Agentic AI workflows, but only 12% feel confident that their infrastructure can support autonomous decision making.

“dados' “momentum” as product”: Organizations proficient in treating data as a product are seven times more likely to implement generative AI solutions at scale, emphasizing the transformative potential of curated and accountable data ecosystems.

^embedded Analytics on the rise: 94% of organizations are incorporating or planning to incorporate analytics into enterprise applications, but only 23% have achieved integration into most of their applications.

^'Strategic influence of generative AI: 89% of organizations have reshaped their data strategies in response to generative AI, demonstrating its transformative impact.

^Gargalo of AI readiness: Although 73% of organizations integrate generative AI with analytics solutions, only 29% have fully implemented these capabilities.

These findings emphasize the urgency for companies to bridge the gap between ambition and execution, with a clear focus on governance, infrastructure, and leveraging data as a strategic asset.

IDC survey results highlight a critical need for companies to move beyond experimentation and address the basic gaps for AI readiness. By focusing on governance, infrastructure and data integration, organizations can harness the full potential of AI technologies and achieve long-term success.

To access the full results and insights from IDC InfoBrief “Priorities and Challenges of Data and Analytics in the Midst of AI Momentum”, sponsored by Qlik, sign up for the webinar and view the full report here.