As the landscape of artificial intelligence (AI) evolves with the rise of Agentic AI, new research from Sinequa in collaboration with ChapsVision highlights a critical shift in priorities for Chief Information Officers (CIOs) and IT teams. Traditionally, cost was seen as the primary barrier to AI adoption; however, it now ranks low on the list of concerns, with only 10% of respondents citing it as a significant issue. Instead, the focus has shifted to more complex challenges around data accuracy and quality, now highlighted by 19% of decision-makers.
The study surveyed 100 enterprise leaders across the UK and US, revealing that 66% of organisations anticipate realising returns on their Agentic AI investments within the next five years. A noteworthy 82% believe AI is enhancing their operational intelligence and efficiency, while 62% feel prepared for the implementation of Agentic AI. However, this sense of readiness is undermined by a stark reality: nearly 61% of organisations acknowledge that their data readiness still needs substantial improvement.
Data readiness: A core focus for IT teams
For Agentic AI to function effectively, it must access trustworthy, contextual insights in real-time. This necessity places immense pressure on IT teams to ensure that data is not only accurate but also readily accessible. The study highlights several key challenges that organisations face in this area:
- Data security and compliance concerns (67%)
- Interdepartmental data silos (47%)
- Managing the volume and velocity of data (37%)
These issues prevent organisations from fully leveraging AI technologies at scale, making data management a top priority for CIOs tasked with the successful adoption of Agentic AI.
The importance of Intelligent Retrieval Systems
In this context, enterprise search capabilities, or intelligent retrieval systems, are becoming increasingly relevant. These tools enable IT teams to extract and surface knowledge from disparate data sources, facilitating the seamless integration of AI technologies. The research indicates that 66% of respondents consider intelligent retrieval expertise crucial for overcoming the obstacles to Agentic AI implementation.
Respondents noted several benefits of intelligent retrieval systems, including:
- Enhancing data accessibility across the organisation (46%)
- Improving AI model training processes (43%)
- Supporting high-volume data processing (42%)
Jeff Evernham, Chief Product Officer at Sinequa by ChapsVision, pointed out the urgency of addressing these data challenges. “While organisations strive to achieve quick returns on investment, genuine transformation will necessitate ongoing investment in data readiness and intelligent retrieval systems,” he said.
As CIOs and their IT teams navigate the complexities of AI adoption, prioritising data quality and accessibility will be essential for maximising the potential of Agentic AI. The path forward requires a strategic focus on building robust data infrastructures that empower organisations to fully harness the capabilities of AI in an increasingly competitive landscape.
