Qlik and ESG research shows that 94% companies are investing more in AI, but only 21% have successfully operationalized it.

THE Qlik'''Global data integration, data quality, analytics, and artificial intelligence (AI) company, [Company Name], announces the results of a new study conducted with the Enterprise Strategy Group (ESG), revealing a critical disconnect between AI investment and execution.

The ESG research report, “Data Readiness for Impactful Generative AIThe report reveals that companies are aggressively scaling AI, but many lack a structured plan to build the necessary datasets for long-term success. While 94% are increasing spending on products and services to enable AI-ready data, only 21% have fully integrated AI into their operations. Although most organizations recognize the critical importance of data quality, governance, compliance, and bias detection remain significant gaps, preventing companies from fully realizing 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 the Data Business Unit at Qlik. "AI is not a temporary solution—it's a permanent transformation requiring structure, governance, and transparency. Without a clear plan and robust data foundations, companies are increasing their risks instead of generating value."

Qlik and ESG's new study highlights a significant misalignment between AI adoption and the precautions needed for successful implementation.

– AI adoption is accelerating, but many companies lack a clear implementation strategy: 94% organizations are increasing spending on products and services that enable data readiness for AI, but only 21% have fully integrated it into their operations.

– Companies are collecting more data, but are struggling to make it usable for AI. 64% organizations collect data from 100 to 499 sources daily, highlighting the sheer complexity of the data.

Operational efficiency is the primary metric, but the full impact of AI remains uncertain. 57% measures AI success based on operational efficiency, while a smaller number tracks its strategic business impact.

– Gaps in bias, governance, and compliance are creating significant risks: 48% organizations are trying to address biases in AI through transparency in model decisions and data sources.

Data quality is crucial, but governance remains a challenge. Only 47% strongly agree that their governance policies are applied consistently, highlighting gaps in supervision and compliance.

"AI isn't a technology problem—it's an execution problem," says Stephen Catanzano, Senior ESG Analyst. "Organizations across all sectors are rapidly moving to scale AI, but without proper precautions, they risk regulatory, financial, and reputational consequences. While recognizing the importance of data quality, most still lack the necessary governance to ensure AI models are both safe and unbiased. This execution gap explains why so many AI projects are stalled or fail to deliver tangible ROI."

The Qlik and ESG report AI Readiness Identify the most pressing challenges in AI execution and provide strategies for long-term success. For deeper insights and expert recommendations, access the eBook here: https://www.qlik.com/us/resource-library/data-Please provide the full Portuguese text. "readiness-for-impactful-" is not a complete sentence or phrase. I need the context to translate it accurately.Generative AI