PHILADELPHIA, PA — Qlik is signaling a shift in how executives should judge artificial intelligence returns, with Chief Executive Officer Mike Capone arguing that most companies already generate real AI value but fail to see, govern, or scale it.
In a preview of Qlik’s 2026 outlook on data, analytics, and AI, Capone said the persistent debate over whether AI “delivers value” misses the point. He said the larger issue is widespread underperformance, with isolated pockets of productivity gains buried inside organizations and disconnected from formal metrics, controls, and decision-making systems.
Capone said employees across large enterprises already rely on AI tools in documents, code, and analysis, quietly boosting productivity. But that work often operates outside governed data environments and never reaches financial reporting, risk models, or executive dashboards, leaving leadership blind to its cumulative impact.
Recent research from Boston Consulting Group shows only about 5 percent of enterprises are structurally prepared for large-scale AI adoption, even as generative tools spread informally throughout businesses. Qlik’s own customer analysis reflects the same contradiction: growing “stealth AI value” that improves outcomes locally but fails to translate into enterprise-level accountability or durable advantage.
Capone said 2026 will be the year leading organizations begin closing that gap. Rather than anchoring strategy to a single AI model, cloud provider, or platform, he said companies should expect constant change and design architectures that allow tools and models to be swapped without disrupting core business logic or losing control of data.
He also said the long-standing tension between centralized control and self-service experimentation is breaking down. Instead, Capone said successful organizations are adopting what he calls controlled decentralization, locking down governance, definitions, and data sovereignty while pushing automation and experimentation to teams closest to day-to-day decisions.
At the same time, Qlik expects intelligence itself to become more utility-like. As smaller models, local inference, and edge computing mature, more decisions will be made closer to where data is generated, including factories, retail locations, vehicles, and devices. Shared analytics and trusted context, Capone said, will remain critical in defining what good decisions look like across the enterprise.
Capone said the cost of intelligence per decision will continue to fall, while expectations for transparency and accountability rise. He said the companies that pull ahead will be those that turn informal, ad-hoc AI usage into explicit, governed decision systems built on trusted data and consistent analytics.
His remarks come ahead of Qlik’s 2026 Data, Analytics and AI Trends webinar scheduled for January, where the company plans to outline broader predictions and regional perspectives on how AI adoption will reshape enterprise operations.
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