Kevin O'Leary's AI Business Advice: Focus on Implementation and Data Centers

Artificial intelligence is reshaping industries at an unprecedented pace, creating new opportunities for entrepreneurs and investors alike. As businesses increasingly adopt AI to streamline operations and improve productivity, demand for practical AI solutions and the infrastructure powering them continues to rise. Against this backdrop, Shark Tank investor Kevin O'Leary has shared where he believes aspiring entrepreneurs should focus if they were entering the market today. Rather than trying to build the next ChatGPT or compete with technology giants, O'Leary says success lies in solving real business challenges. Reflecting on what he would do if he were starting his career today, he highlighted two AI-related businesses with significant long-term potential.

Speaking in a video released earlier this year, O'Leary said his first choice would be helping small businesses adopt artificial intelligence. He believes millions of companies recognise AI's potential but lack the expertise to integrate it into their daily operations. Instead of creating new AI models, he sees greater opportunity in helping businesses organise their data, automate repetitive tasks and deploy existing AI tools effectively. According to the US Small Business Administration, the country has around 36 million small businesses, accounting for nearly half of US economic activity. While large corporations often have dedicated AI teams, many smaller firms need practical support to implement the technology. O'Leary argued that entrepreneurs who specialise in AI implementation and execution, rather than traditional consulting, could meet a growing demand as businesses seek to improve efficiency and remain competitive. "There’s going to be a massive amount of people wanting to use it that don’t know how to and they’re willing to pay to solve that pain point," O'Leary said.

The second opportunity O'Leary identified is data centre development, which he described as one of the biggest bottlenecks facing the AI industry. Modern AI systems require enormous computing power, with advanced data centres housing thousands of specialised processors that train and run complex AI models. As AI adoption accelerates, technology companies are racing to expand this infrastructure, creating strong demand for new facilities capable of supporting next-generation computing workloads. "The biggest pain point in AI is data centres," O'Leary said. "That's real-estate development." His investment strategy reflects that view. O'Leary has backed large-scale AI infrastructure projects, including a proposed 7.5-gigawatt data centre industrial park in Alberta, Canada, reportedly valued at around $70 billion. He has also supported a proposed $100 billion data centre project in Utah. Both developments have attracted attention because of their scale, construction timelines and concerns over energy use and local environmental impacts.

O'Leary's optimism is backed by broader industry forecasts. Goldman Sachs Research estimates that global data centre power demand could increase by around 165% by the end of the decade, largely because of artificial intelligence. At the same time, major technology companies including Amazon, Microsoft, Google and Meta continue investing billions of dollars in AI infrastructure, cloud computing and advanced processors. Analysts say the biggest constraints are no longer limited to AI chips alone. Electricity supply, grid connections, land availability and cooling systems have become critical challenges as companies work to build larger and more powerful data centres. The rapid pace of investment reflects expectations that AI demand will continue growing across industries, from healthcare and finance to manufacturing and retail.

Rather than encouraging young entrepreneurs to compete directly with established AI developers, O'Leary believes the smarter opportunity lies in supporting the broader AI ecosystem. Businesses across sectors are looking for practical ways to adopt artificial intelligence, while infrastructure providers are working to meet soaring demand for computing capacity. Although success is never guaranteed in a fast-moving industry, O'Leary argues that helping companies implement AI and expanding the infrastructure behind it address real market needs. As artificial intelligence becomes more deeply embedded in everyday business operations, these two areas could remain among the most promising opportunities for entrepreneurs looking to build long-term businesses.