A significant gap between AI ambitions and companies’ execution has been identified in a new survey. The study, published in an IDC InfoBrief sponsored by Qlik, shows that, while 89% of organisations have revamped data strategies to embrace Generative AI, only 26% have deployed solutions at scale.
These results underscore the urgent need for improved data governance, scalable infrastructure and analytics readiness to fully unlock AI’s transformative potential, according to Qlik, a global leader in data integration, data quality, analytics and artificial intelligence.
The findings arrive as businesses worldwide race to embed AI into workflows, with AI projected to contribute $19.9-trillion to the global economy by 2030. Yet, readiness gaps threaten to derail progress.
Organisations 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 readiness gap,” says Stewart Bond, research VP for data integration and intelligence at IDC. “Businesses must address core challenges like data accuracy and governance to ensure AI workflows deliver sustainable, scalable value.”
James Fisher, chief strategy officer at Qlik. Photo supplied.
Without addressing these foundational issues, businesses risk falling into an “AI scramble,” where ambition outpaces the ability to execute effectively, leaving potential value unrealised.
James Fisher, chief strategy officer at Qlik, says AI’s potential hinges on how effectively organisations manage and integrate their AI value chain.
“This research highlights a sharp divide between ambition and execution,” he says. “Businesses that fail to build systems for delivering trusted, actionable insights will quickly fall behind competitors moving to scalable AI-driven innovation.”
The IDC survey uncovered several critical statistics illustrating the promise and challenges of AI adoption:
- Agentic AI Adoption vs. Readiness: 80% of organisations are investing in Agentic AI workflows, yet only 12% feel confident their infrastructure can support autonomous decision-making.
- “Data as a Product” Momentum: Organisations proficient in treating data as a product are 7x more likely to deploy Generative AI solutions at scale, emphasising the transformative potential of curated and accountable data ecosystems.
- Embedded Analytics on the Rise: 94% of organisations are embedding or planning to embed analytics into enterprise applications, yet only 23% have achieved integration into most of their enterprise applications.
- Generative AI’s Strategic Influence: 89% of organisations have revamped their data strategies in response to Generative AI, demonstrating its transformative impact.
- AI Readiness Bottleneck: Despite 73% of organisations integrating Generative AI into analytics solutions, only 29% have fully deployed these capabilities.
These findings stress 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.
The IDC survey findings highlight an urgent need for businesses to move beyond experimentation and address the foundational gaps in AI readiness. By focusing on governance, infrastructure, and data integration, organisations can realise the full potential of AI technologies and drive long-term success.
- For the complete findings 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.