A Qlik®, a global company in data integration, data quality, analytics, and artificial intelligence (AI), announces the results of a new study conducted with Enterprise Strategy Group (ESG), exposing a critical disconnect between AI investment and execution.
The ESG research report, “Data Readiness for Impactful Generative AI”, reveals that companies are aggressively moving to scale AI, but many lack a structured plan to build the necessary data foundations for long-term success. While 94% are increasing spending on products and services to enable AI data readiness, only 21% have fully integrated AI into their operations. Although most organizations recognize that data quality is crucial, governance, compliance, and bias detection remain key gaps, preventing companies from fully unlocking AI’s potential.
“Companies are rushing to adopt AI by investing heavily without a cohesive strategy,” says Drew Clarke, Executive Vice President and General Manager of Qlik’s Data Business Unit. “AI is not a temporary solution—it’s a permanent transformation that requires structure, governance, and transparency. Without a clear plan and solid data foundations, companies are increasing their risks rather than generating value.”
The new Qlik and ESG study highlights a strong misalignment between AI adoption and the necessary precautions to ensure its success:
– AI adoption is accelerating, but many companies lack a clear implementation strategy: 94% of organizations are increasing spending on products and services that enable AI data readiness, but only 21% have fully integrated it into their operations.
– Companies are collecting more data but struggle to make it usable for AI: 64% of organizations collect data from 100 to 499 sources daily, highlighting the scale of data complexity.
– Operational efficiency is the primary metric, but AI’s full impact remains uncertain: 57% measure AI success based on operational efficiency, while fewer track its strategic business impact.
– Gaps in bias, governance, and compliance are generating significant risks: 48% of organizations attempt to address AI bias through transparency in model-related decisions and data sources.
– Data quality is critical, but governance remains a challenge: Only 47% strongly agree that their governance policies are consistently enforced, highlighting gaps in oversight and compliance.
“AI is not a technology problem—it’s an execution problem,” says Stephen Catanzano, Senior Analyst at ESG. “Organizations across industries are rapidly scaling AI, but without proper precautions, they risk regulatory, financial, and reputational consequences. While they recognize the importance of data quality, most still lack the governance needed to ensure AI models are safe and unbiased. This execution gap explains why so many AI projects stall or fail to deliver tangible ROI.”
The Qlik and ESG report AI Readiness identifies the most urgent challenges in AI execution and provides strategies to ensure long-term success. For deeper insights and expert recommendations, access the eBook here: https://www.qlik.com/us/resource-library/data-readiness-for-impactful-generative-ai
