A Qlik®, a global leader 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 moving aggressively to scale AI, but many do not have a structured plan to build the necessary databases for long-term success. While 94% are increasing spending on products and services to enable data readiness for AI, only 21% have fully integrated AI into their operations. Although most organizations recognize that data quality is crucial, governance, compliance, and bias detection remain the main gaps, preventing companies from fully harnessing the potential of AI.
"Companies are rushing to adopt AI, 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 is a permanent transformation that requires structure, governance, and transparency. Without a clear plan and solid databases, companies are increasing their risks instead of creating value.
New research from Qlik and ESG highlights a stark misalignment between AI adoption and the precautions needed 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 data readiness for AI, but only 21% have fully integrated AI into their operations.
– Companies are collecting more data, but are struggling to make it usable for AI:64% of organizations collect data from 100 to 499 sources daily, highlighting the extent of data complexity.
– Operational efficiency is the key metric, but the full impact of AI remains unclear:57% measure AI success based on operational efficiency, while fewer track its strategic impact on the business.
– Gaps in bias, governance and compliance are creating significant risks:48% of organizations attempt to address bias in AI through transparency into model-related decisions and data sources.
– Data quality is critical, but governance remains a challenge:Only 47% strongly agree that their governance policies are applied consistently, highlighting gaps in oversight and compliance.
"AI is not a technology problem — it's an execution problem," says Stephen Catanzano, Senior ESG Analyst. Organizations across all sectors are moving quickly to scale AI, but without proper precautions, they risk facing regulatory, financial, and reputational consequences. While they recognize the importance of data quality, most still lack the governance needed to ensure that AI models are safe and unbiased. This execution gap explains why so many AI projects are stalled or fail to deliver tangible ROI.
Qlik and ESG Report AI ReadinessIdentify the most urgent challenges in AI implementation and provide 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
