65% of enterprises race to build reliable agentic capabilities as poor data foundations cause project delays and compliance issues
As AI investment soars, the race for agentic capabilities is outpacing the modern data infrastructure required to support it, according to a new Semarchy survey of 1,000 global C-level executives across the United Kingdom, United States, and France. The research shows data management is now viewed as the single most pressing challenge for 51 percent of leaders, surpassing both cost and talent concerns. With half of leaders currently implementing AI initiatives without Master Data Management foundations, and a third without enforcing data quality standards, many are at risk of rendering their new agentic capabilities fundamentally unreliable, increasingly costly, and impossible to scale.
Significant investment in AI has tripled compared to the previous year, with half of organizations now committing more than 20 percent of their total technology budget to scaling AI initiatives. Despite acknowledged skills and strategy gaps, optimism around reaching AI goals has nearly doubled to 92 percent from 46 percent in 2025, while nearly two-thirds of leaders are pushing to develop agentic data management capabilities this year.
Key Insights at a Glance
- Data Management Tops Challenges: 51 percent of executives cite data management as the most pressing AI challenge, surpassing both cost and talent constraints.
- Agentic Race Accelerates: 65 percent of leaders are pushing to develop agentic data management capabilities in 2026, even as foundational gaps persist.
- Investment Surge: Significant AI investment has tripled year-over-year, with 50 percent of organizations now dedicating over 20 percent of tech budgets to AI initiatives.
- Consequences Already Visible: 22 percent experienced AI project delays due to data quality concerns, 21 percent faced operational inefficiencies from unreliable data, and 19 percent encountered compliance issues linked to data protection regulations.
The Data Foundation Gap Threatens AI Reliability
The Semarchy survey reveals a concerning disconnect between AI ambition and data readiness. Half of leaders are implementing AI initiatives without Master Data Management foundations, while 38 percent are proceeding without enforcing data quality standards. This approach creates what Semarchy terms “AI technical debt” — a compounding liability that could do significant long-term harm to business operations. “We are seeing a stark divide,” said Craig Gravina, Chief Technology Officer at Semarchy. “One half of leaders building on strong MDM foundations are positioning themselves to deliver trusted data products – the essential building blocks for scaling agentic AI reliably. The other half aren’t just lagging behind; they are actively accumulating AI technical debt. Trying to scale agentic AI on top of fragmented data foundations and a disjointed strategy isn’t just inefficient – it creates a compounding liability that could do significant long-term harm to the business.”
Compliance Concerns Drive Governance Retrofit
The survey shows a dramatic shift in governance priorities over the past year. While only 50 percent of leaders had prioritized ethics and regulation of AI use in their organization in 2025, that focus has rapidly formalized, with 77 percent now having fully integrated AI considerations into their data governance policies. This suggests many organizations are retrofitting compliance under pressure rather than building it proactively from the start. The consequences of inadequate data foundations are already manifesting: 22 percent of leaders experienced AI project delays due to data quality concerns, 21 percent faced operational inefficiencies from unreliable data, and 19 percent encountered compliance issues linked to data protection regulations. These outcomes validate that data governance cannot be an afterthought in AI deployment.
Data Leaders Sidelined From AI Strategy
The report highlights a structural problem in how organizations approach AI governance. Despite data management being identified as the single biggest hurdle to AI success, only 7 percent of Chief Data Officers and 18 percent of Chief Information Officers are viewed as holding a chief role in their organization’s AI strategy. This disconnect between the architects of data infrastructure and the strategists driving AI initiatives creates predictable execution gaps. “The disconnect between ambition and reality often starts at the top,” Gravina added. “It’s alarming that while data management is the single biggest hurdle, only 7% of CDOs and 18% of CIOs are viewed as holding a chief role in their organization’s AI strategy. You simply cannot separate the AI vision from the data reality. When the architects of your data infrastructure are sidelined from the strategy room, execution gaps are inevitable.” To bridge these gaps, 48 percent of leaders are investing in a DataOps approach this year, applying software engineering discipline to data delivery with the aim of ensuring rapid, reliable delivery of high-quality data products.
Future Outlook
The Semarchy survey paints a picture of an AI market at a critical inflection point. Investment continues to surge, with half of organizations now dedicating over 20 percent of technology budgets to AI initiatives. Optimism has doubled despite acknowledged skills and strategy gaps, suggesting leaders believe they can overcome challenges through increased investment and focus. However, the structural disconnect between data leaders and AI strategy, combined with the absence of foundational MDM and data quality practices in many organizations, creates significant risk that current AI investments will fail to deliver expected returns. The 65 percent of leaders pursuing agentic capabilities face particular exposure, as autonomous AI systems amplify the consequences of poor data foundations. Organizations that address data management proactively will likely pull ahead of competitors forced to retrofit governance under pressure.
Conclusion
Semarchy’s 2026 survey of global executives reveals that data management has overtaken cost and talent as the primary AI challenge, with 51 percent of leaders citing it as their most pressing concern. Despite surging investment and optimism, many organizations are implementing AI without the Master Data Management foundations and data quality standards needed for reliable, scalable deployment. For enterprises racing to build agentic capabilities, the message is clear: data foundations cannot be an afterthought.
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About Semarchy
Semarchy is the modern data management company. The Semarchy Data Platform (SDP) – our AI-driven MDM and governance platform built for DataOps – ensures the rapid delivery of trusted, governed data products at scale, so businesses can easily find, understand, and consume the data they need.
With a proven record of customer success, Semarchy helps customers meet the growing demand for accurate, trusted data and drive the success of data-focused initiatives like AI, Customer 360, and more.
SDP is available as SaaS, as a self-managed (on-premises, private cloud) deployment, or as the only MDM platform offered as a native Snowflake application. It’s also available through major cloud marketplaces, including Snowflake, Microsoft Azure, AWS, and Google Cloud Platform.
Semarchy is headquartered in Phoenix, USA, with offices in London (UK), Lyon (France), and New Delhi (India). For more information, visit www.semarchy.com.
About the research
The 2026 research was conducted by Censuswide, among a sample of 1,000 C-suite (Aged 21 or over), employed and work in an organization with annual turnover of $200 million+ at companies that use AI. Across the UK, USA & France. The data was collected between January 29, 2026 and February 9, 2026. Censuswide is a member of the Market Research Society (MRS) and the British Polling Council (BPC), and a signatory of the Global Data Quality Pledge. We adhere to the MRS Code of Conduct and ESOMAR principles.
The 2025 research was conducted by Censuswide, among a sample of 1,050 Full time working respondents, in companies that currently use/are involved with AI. Roles include heads of data, CDOs, CIOs and equivalents, as well as standard C-suite level. Across the UK, USA and France. The data was collected between February 6, 2025 and February 12, 2025. Censuswide abides by and employs members of the Market Research Society and follows the MRS code of conduct and ESOMAR principles. Censuswide is also a member of the British Polling Council.
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