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

THE Qlik'''(IA), a global company in data integration, data quality, analytics and artificial intelligence, announces the results of a new study conducted with the 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 lack a structured plan to build the databases needed for long-term success. While 94% is increasing spending on products and services to enable data readiness for AI, only 21% have been able to fully integrate AI into their operations.

“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 AI is not a temporary solution & IS a permanent transformation that requires structure, governance and transparency. Without a clear plan and solid databases, companies are increasing their risks rather than generating value

The new Qlik and ESG study highlights a strong misalignment between AI adoption and the precautions needed to ensure its success:

2 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 it into their operations.

2 Companies are collecting more data, but have difficulty making it usable for AI: 64% of organizations collect data from 100 to 499 sources daily, highlighting the size of data complexity.

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

^gaps in bias, governance and compliance are generating significant risks: 48% of organizations attempt to address biases in AI through transparency in model-related decisions and data sources.

(Data quality is key, but governance remains a challenge: Only 47% strongly agree that their governance policies are consistently enforced, highlighting gaps in oversight and compliance.

“A AI is not a technology problem & IS is a execution problem”, says Stephen Catanzano, Senior Analyst at ESG.“Organizations across industries are moving quickly to scale AI, but without the proper precautions, they are at risk of suffering regulatory, financial and reputational consequences. While recognizing the importance of data quality, most still lack the governance needed to ensure AI models are safe and unbiased.

The Qlik and ESG report AI Readiness identifies the most pressing challenges in AI execution and provides strategies to ensure long-term success.For deeper insights and expert recommendations, visit the eBook here: https://www.qlik.com/us/resource-library/date-libraryreadiness-for-impactfulgenerative-ai