A Qlik®, a 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 adopting 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% have implemented solutions at scale. These results highlight the urgent need to enhance data governance, scalable infrastructure, and analytics readiness to fully unlock the transformative potential of AI.
The results, published in an IDC InfoBrief sponsored by Qlik, come at a time when companies worldwide are rushing to incorporate AI into their workflows, with projections that AI will contribute $19.9 trillion to the global economy by 2030. However, readiness gaps threaten to undermine progress. Organizations are shifting their focus from AI models to creating foundational data ecosystems necessary for long-term success.
"Generative AI has sparked widespread enthusiasm, but our findings reveal a significant gap in readiness. Companies must address key challenges such as data accuracy and governance to ensure AI workflows deliver sustainable and scalable value," says Stewart Bond, Vice President of Research for Data Integration and Intelligence at IDC.
By not addressing these basic issues, companies risk falling into a "frenzied race for AI," where ambition surpasses effective execution capacity, without achieving the potential value.
"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 create systems to provide reliable and actionable insights will quickly fall behind their competitors who are migrating to 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 Readiness:80% 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 large-scale generative AI solutions, emphasizing the transformative potential of curated and responsible data ecosystems.
- Embedded Analytics in growth:94% of organizations are incorporating or planning to incorporate analytics into corporate 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.
- AI readiness bottleneck:Although 73% of organizations integrate generative AI into analytics solutions, only 29% have 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.
IDC research results highlight a critical need for companies to go beyond experimentation and address the fundamental gaps in 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 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 view the full report.here.
