The Real Challenge with AI: From Experiments to Everyday Business Solutions, According to Qlik CEO
Qlik CEO Mike Capone: The Future of AI is About Turning Data into Action
AI’s Potential Beyond the Hype
Artificial Intelligence (AI) has become one of the most talked-about topics in the business world. While the technology itself holds immense potential, Qlik CEO Mike Capone believes that AI is only as effective as the data it’s built upon. Capone, in a recent interview with IndianExpress.com, shared his thoughts on how businesses can truly harness the power of AI, what challenges they face, and how the future of AI will be shaped by practical, results-driven models.
AI Struggles: It’s Not About the Technology, It’s About the Application
Capone points out that many companies are not struggling with AI because of technological limitations. Rather, the real issue lies in connecting AI to meaningful business outcomes. According to Capone, companies often lack the infrastructure and organizational culture needed to make AI a core part of their decision-making processes. Without these foundational elements, AI models often remain isolated experiments rather than tools that drive business value.
“Many companies struggle with AI not because the technology isn’t available, but because they can’t connect it to business outcomes,” said Capone. This observation highlights a major roadblock for businesses aiming to successfully integrate AI into their daily operations. For AI to succeed, it must be operationalized—not just experimented with in a lab.
Smaller, More Efficient AI: The Future of Business Solutions
As AI evolves, Capone predicts that the focus will shift away from large, generalized AI models and toward smaller, purpose-built models that are tailored for specific business needs. Citing an IDC report, Capone explained that by 2026, 90% of AI use cases will move toward more practical, specialized solutions. This new wave of AI will be seamlessly integrated into workflows, helping businesses make better decisions in real-time. “The future of AI isn’t about model size; it’s about making AI actually work where it matters,” Capone said.
This shift toward specialized AI models is exemplified by companies like DeepSeek AI, a Chinese AI startup that is proving success in AI development doesn’t depend solely on big budgets. Instead, the key to AI’s future lies in how effectively businesses apply and execute AI solutions. Capone believes that companies should stop chasing after the "best" AI models and focus on implementing the right AI models for their unique needs.
AI Is No Longer Just for Big Spenders: Affordability and Accessibility
Capone also addressed the issue of AI affordability. In the past, building AI models required significant investments. However, with technological advancements and the rise of more accessible tools, AI is becoming more affordable and accessible to a wider range of businesses.
“Affordability isn’t just about making AI cheaper; it’s about making it useful and integrated into real business applications,” Capone explained. As AI becomes more cost-effective, businesses can move beyond experimentation and begin applying AI at scale. The winners will be those who use AI not just for tinkering but to automate decision-making, improve productivity, and drive business growth.
This is especially true for businesses in regions like India, where scalability and cost-effectiveness are critical. Capone believes that the true transformation will happen when AI moves beyond research and development and becomes an essential tool for businesses.
Operationalizing AI: From Experiment to Action
A key challenge businesses face when adopting AI is operationalizing it—turning AI from isolated pilots into integrated, everyday tools. Capone emphasizes that operationalizing AI requires businesses to embed AI in their decision-making processes. Many companies have invested in AI pilots but haven’t successfully scaled them across their entire organization.
“Operationalizing AI means moving from isolated experiments to embedding AI into everyday decision-making,” Capone explained. For AI to truly deliver value, it must be seamlessly integrated into existing workflows, enabling data-driven decisions in real time.
However, Capone also acknowledged the struggles companies face in making this transition. Fragmented data, lack of AI expertise, and resistance to AI-driven decision-making are some of the key barriers. “Many leaders still see AI as an IT project rather than a core business enabler,” he said.
Making AI Accessible to SMEs: Overcoming Barriers
For small and medium-sized enterprises (SMEs), building AI from scratch can be a daunting task. This is where Qlik comes in. Capone explained that Qlik’s solutions are designed to make AI accessible to businesses of all sizes. Through AI-powered automation and analytics, Qlik enables businesses to deploy machine learning models without the need for deep technical expertise.
Qlik’s AutoML and AI-driven analytics tools make it easier for businesses to implement AI, reducing their reliance on expensive data science teams. By embedding AI into tools businesses already use, Qlik helps SMEs unlock the potential of AI without the significant upfront costs associated with developing custom solutions.
Data Strategy: The Foundation of AI Success
Capone also stressed the importance of having a solid data strategy. For AI to work effectively, it must be built on high-quality, well-governed data. “Your AI is only as good as the data it’s built on. If your data is flawed, your AI will be too,” Capone warned.
Strong data governance, clear data access protocols, and seamless integration into business workflows are essential for generating real value from AI. Companies must prioritize data quality and ensure they have the right systems in place to manage and leverage their data effectively.
The Future of AI: Integration, Not Just Innovation
Looking ahead, Capone sees the future of AI being shaped by the companies that integrate AI effectively into their operations. "The AI arms race won’t be won by who builds the best models—it will be won by who integrates AI best," he said.
As AI continues to evolve, the real winners will be those that can operationalize AI and make it a core part of their decision-making processes. According to Gartner, by 2028, 40% of AI asset purchases will happen through marketplaces, signaling a shift toward a more collaborative, marketplace-driven AI ecosystem. Capone’s vision for AI is clear: the future of AI is about practical, actionable solutions that deliver measurable business outcomes.
Turning AI into Action for Business Success
Mike Capone’s insights into the future of AI highlight the shift from AI as an experimental technology to AI as an integral business tool. For AI to succeed, businesses must focus on practical, purpose-built solutions that are tailored to their unique needs. With more affordable AI tools and a greater emphasis on data quality and integration, companies can make AI a core part of their operations, driving better decision-making, automation, and productivity.
In the rapidly evolving world of AI, success will not be determined by who spends the most or who builds the biggest model—but by who can integrate AI into their business in a way that delivers real value.
