A Qlik®, global company in data integration, data quality, analytics and artificial intelligence (AI), announced the results of an IDC survey that explores the challenges and opportunities in the adoption of advanced AI technologies. The study highlights a significant gap between ambition and execution: although 89% of organizations have renewed their data strategies to adopt generative AI, only 26% implemented solutions at scale. These results highlight the urgent need to improve data governance, scalable infrastructure and readiness for analytics to fully unlock the transformative potential of AI
The results, published in an IDC InfoBrief sponsored by Qlik, they arrive at a time when companies around the world are rushing to incorporate AI into workflows, with the projection that AI will contribute US$ 19,9 trillion for the global economy by 2030. However, the readiness gaps threaten to undermine progress. Organizations are shifting their focus from AI models to the creation of necessary foundational data ecosystems for long-term success
"Generative AI has sparked widespread enthusiasm", but our findings reveal a significant gap in readiness. Companies must face the main challenges, how data accuracy and governance, to ensure that AI workflows generate sustainable and scalable value, says Stewart Bond, Vice President of Research for Data Integration and Intelligence at IDC
Without addressing these basic issues, companies run the risk of falling into a "frenzied race for AI", in which ambition surpasses the ability for effective execution, without the potential value being reached
"The potential of AI depends on the effectiveness with which organizations manage and integrate their AI value chain", says James Fisher, Strategy Director of Qlik. This research highlights a clear divide between ambition and execution. Companies that fail to create systems to provide reliable and actionable insights will quickly fall behind competitors that are moving towards scalable AI-driven innovation.”
IDC's research revealed several important statistics that illustrate the promise and challenges of AI adoption
– Adoption of Agentic AI X Readiness80% of organizations are investing in Agentic AI workflows, but only 12% feel confident that their infrastructure can support autonomous decision-making
– The "momentum" of "data as a 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 responsible data ecosystems
– Embedded Analytics on the rise94% of organizations are incorporating or planning to incorporate analytics into corporate applications, but only 23% achieved integration in most of their applications
– Strategic influence of generative AI89% of organizations have restructured their data strategies in response to generative AI, demonstrating its transformative impact
– Bottleneck of AI readinessDespite 73% of organizations integrating generative AI into analytics solutions, only 29% fully implemented these features
These findings emphasize the urgency for companies to bridge the gap between ambition and execution, with a clear focus on governance, infrastructure and data utilization as a strategic asset
The results of the IDC research highlight a critical need for companies to go beyond experimentation and address the basic gaps for AI readiness. By focusing on governance, infrastructure and data integration, organizations can leverage the full potential of AI technologies and achieve long-term success
To access the complete results and insights of the IDC InfoBrief "Priorities and Challenges of Data and Analytics in the Midst of AI Momentum", sponsored by Qlik, register for the webinar and see the full reporthere.
