A Qlik®, a global company in data integration, data quality, analytics, and artificial intelligence (AI), 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: although 89% of organizations have renewed their data strategies to adopt 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 AI’s transformative potential.
The results, published in an IDC InfoBrief sponsored by Qlik, arrive at a time when companies worldwide are racing to incorporate AI into workflows, with projections that AI will contribute $19.9 trillion to the global economy by 2030. However, readiness gaps threaten to derail progress. Organizations are shifting their focus from AI models to building the foundational data ecosystems necessary for long-term success.
“Generative AI has sparked widespread excitement, but our findings reveal a significant gap in readiness. Companies must address key challenges, such as data accuracy and governance, to ensure that AI workflows generate sustainable and scalable value,” says Stewart Bond, Vice President of Data Integration and Intelligence Research at IDC.
Without addressing these foundational issues, companies risk falling into a ‘frantic AI race,’ where ambition outstrips the capacity for effective execution, failing to realize potential value.
“AI’s potential depends on how effectively organizations manage and integrate their AI value chain,” says James Fisher, Qlik’s Chief Strategy Officer. “This research highlights a clear divide between ambition and execution. Companies that fail to build systems to deliver reliable, actionable insights will quickly fall behind competitors moving toward scalable, AI-driven innovation.”
The IDC survey revealed several key statistics illustrating the promise and challenges of AI adoption:
– Agentic AI Adoption vs. Readiness: 80% of organizations are investing in Agentic AI workflows, but only 12% feel confident their infrastructure can support autonomous decision-making.
– The ‘Data as a Product’ Momentum: Organizations proficient at treating data as a product are seven times more likely to implement generative AI solutions at scale, highlighting the transformative potential of curated, responsible data ecosystems.
– Growing Embedded Analytics: 94% of organizations are embedding or planning to embed analytics into business applications, but only 23% have achieved integration in most of their applications.
– Generative AI’s Strategic Influence: 89% of organizations have reshaped their data strategies in response to generative AI, demonstrating its transformative impact.
– AI Readiness Bottleneck: Despite 73% of organizations integrating generative AI into analytics solutions, only 29% have fully implemented these capabilities.
These findings emphasize the urgency for businesses to bridge the gap between ambition and execution, with a clear focus on governance, infrastructure, and leveraging data as a strategic asset.
The IDC survey results highlight a critical need for companies to move beyond experimentation and address foundational AI readiness gaps. By focusing on governance, infrastructure, and data integration, organizations can harness AI technologies’ full potential and achieve long-term success.
To access the full results and insights from the 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.
