‘AI Strategy Without Execution Is Pointless’: CEO Mike Capone at Qlik Connect 2025
At Qlik Connect 2025, CEO Mike Capone delivered a clear message: massive AI investments won’t deliver value without solid execution. Despite the surge in AI strategies, many organisations struggle to move beyond planning to meaningful deployment.
“Tons and tons of money is being poured into AI, but we’re not seeing the results. Strategy is great, spending money is great, but without execution, it’s completely pointless,” Capone said during his keynote. The annual Qlik summit gathered industry leaders to discuss the state of AI adoption, revealing a troubling gap between ambition and action.
The Execution Gap in AI Deployment
Capone highlighted a stark contrast: while 86% of organisations have an AI strategy, only 26% have deployed AI at scale. This disconnect is a critical hurdle, especially as companies rush to embrace agentic AI—autonomous systems designed to perform tasks independently.
“80% of companies say they’re investing in agentic AI,” Capone noted. “But only 12% feel their data is ready for it. Everyone wants to jump in, but they forget the groundwork needed.”
Fixing the Data Foundation
Ritu Jyoti, group vice president and general manager of AI at IDC, joined the keynote to discuss barriers to AI adoption. She pointed out that fragmented and disjointed data across disparate systems severely limit AI’s effectiveness. Other issues include misaligned AI and corporate strategies, a lack of AI-ready talent, and cultural resistance driven by job security fears.
Jyoti distinguished agentic AI from generative AI, explaining that while generative AI enhances human productivity, agentic AI brings agility and autonomous execution. For example, a fully autonomous software engineer could receive a high-level goal—like building an app for logistics—and deliver it independently. This combination of human oversight and digital labor enables outcomes at speeds and scales unreachable by human teams alone.
Real-World Implementation Insights
Tom Mazzaferro, chief data, AI, and analytics officer at Truist, shared how his organisation tackles AI challenges. Operating in a hybrid environment of on-premises and cloud systems, Truist focuses on integrating these to meet business goals and serve customers effectively.
Mazzaferro emphasized partnerships as essential for AI success. “We can’t do it alone. We rely on partners and subject matter experts to deliver value to clients and employees.”
His advice for organisations starting AI initiatives is simple: define clear goals and ensure technology supports business outcomes. “Figure out what you want to achieve and how your AI efforts help clients succeed,” he said.
Despite challenges, some organisations are progressing. Jyoti cited Johnson & Johnson’s use of AI in drug discovery as an example of early adoption that balances risk with rapid learning.
Focus on Trusted Data, Not Just Models
Capone stressed that success depends on building a foundation of trusted, high-quality data rather than chasing specific AI models. “It’s about trusting your data and embedding AI where it drives real, measurable outcomes,” he said.
Addressing fears about AI replacing jobs, Capone noted, “People won’t lose jobs because of AI itself, but because someone else used AI better.” Jyoti added a personal perspective, comparing how her son’s engineering education included tools she never had, without diminishing intelligence.
A Call to Action for Executives
Capone concluded with a direct challenge: “The race isn’t coming. It’s already on. Winners are executing now. You are more important to your organisations than ever. The question is, are you moving fast enough—not just to keep up but to win?”
Executives must focus on closing the gap between AI strategy and execution. Success requires prioritising data readiness, aligning AI efforts with business goals, and embracing partnerships. Those who act decisively will set the pace in this critical moment.
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