Ahead of Qlik Connect® 2025, the Qlik® AI Council is aligning around a clear message to the industry: AI that can’t be trusted won’t scale—and AI that can’t scale is just theatre. Their perspectives converge on a critical shift in enterprise AI: the need to move beyond experimentation and toward execution, powered by transparency, governance, and trusted data at the core.

Despite record AI investment, most enterprises remain stuck in the lab. According to recent IDC research, while 80% plan to deploy agentic AI workflows, only 12% feel ready to support autonomous decision-making at scale. Trust in outputs is eroding amid growing concerns around hallucinations, bias, and regulatory scrutiny. And as models become commoditised, competitive advantage is shifting—not to those with the most advanced models, but to those who can operationalise AI with speed, integrity, and confidence.

The Qlik AI Council emphasises that trust must be designed in—not added later. Execution is the new differentiator, and it only works when the data, infrastructure, and outputs are verifiable, explainable, and actionable. In today’s environment, the companies that pull ahead won’t be the ones that test the most—they’ll be the ones that deliver.

“AI that operates without transparency and redress is fundamentally unscalable,” said Dr. Rumman Chowdhury, CEO of Humane Intelligence. “You cannot embed autonomy into systems without embedding accountability. Businesses that fail to treat governance as core infrastructure will find themselves unable to scale—not because of technology limits, but because of trust failures.”

“We’re entering a trust crisis in AI,” said Nina Schick, Founder of Tamang Ventures. “From deepfakes to manipulated content, public confidence is collapsing. If businesses want to build AI that scales, they must first build systems the public believes in. That requires authenticity, explainability, and a deep understanding of the geopolitical risks of unchecked automation.”

“The regulatory landscape is moving fast—and it’s not waiting for companies to catch up,” said Kelly Forbes, Executive Director of the AI Asia Pacific Institute. “Executives need to understand that compliance is no longer just a legal shield. It’s a competitive differentiator. Trust, auditability, and risk governance aren’t constraints—they’re what make enterprise-scale AI viable.”

“Last year’s Nobel Prizes have recognised the increasingly prominent role AI plays and will play in scientific discovery, from developing new drugs and materials to proving mathematical theorems,” said Dr. Michael Bronstein, DeepMind Professor of AI at the University of Oxford. “Data is the lifeblood of AI systems, and not only do we need new data sources that are designed specifically with AI models in mind, but we need to make sure that we can trust the data that any AI platform is built on.”

“The market is short on execution,” said Mike Capone, CEO of Qlik. “Companies aren’t losing ground because they lack access to powerful models. They’re losing because they haven’t embedded trusted AI into the fabric of their operations. That’s why at Qlik, we’ve built a platform focused on decisive, scalable action. If your data isn't trusted, your AI isn't either. And if your AI can’t be trusted, it won’t be used.”

The message from the Qlik AI Council is clear: AI is moving fast, but trust moves first. The time to act isn’t next quarter. It’s now. Businesses that fail to operationalise trusted intelligence will fall behind—not because of what they didn’t build, but because of what they couldn’t scale.