AI is a Disruptive Force for Businesses
Much like the recent closing ceremonies of the Milano Cortina Winter Olympics, the initial, spectacular hype cycle of artificial intelligence is finally wrapping up. The fireworks have faded, and now global businesses have to go home, unpack, and figure out how to actually grind out results without the constant roar of the crowd. As we navigate the early months of 2026, our evaluation of AI has shifted from simple excitement to a more practical look at how this technology will actually impact company profits. While the life-changing potential of AI is widely accepted, the financial reality of this shift is proving to be a bit more complicated than the initial hype suggested.
Scoring Early Points on Cost and Capability
First and foremost, AI is already proving to be a powerful way to save money in certain areas. We are seeing immediate improvements to the bottom line in departments like customer service, basic software coding, graphics design, and translation. A great real-world example is the financial company Klarna, which recently reported that its AI assistant handles two-thirds of all customer service chats—doing the equivalent work of 700 full-time agents and saving the company tens of millions of dollars. Furthermore, their use of AI for generating images has cut their outside marketing costs by 25%. However, it is a stark reminder of the disconnect between using AI and overall financial health that Klarna itself remains unprofitable, with its stock price down roughly 50% year-to-date.
Beyond just cutting costs, AI is increasingly being used to give highly skilled workers a major boost. In the healthcare sector, AI is speeding up drug discovery by rapidly analyzing complex biology, effectively turning years of early-stage research into months. We are seeing similar leaps in global shipping, where AI constantly finds the fastest delivery routes, and in retail, where AI shopping assistants are creating highly personalized experiences for everyday consumers.
Looking forward, AI could also create entirely new streams of income for certain businesses. The biggest opportunities are popping up for companies that have their own unique, private data. Companies that own massive amounts of high-quality information can train specialized AI models that generic, off-the-shelf AI simply cannot copy.
The Olympic Village Hangover: Revenue vs. Reality
However, as investors, we have to recognize that this massive shift in the business world won’t happen overnight. As basic AI tools become more common, many of these services will just become standard expectations rather than special features. When these tools are available to everyone, the competitive edge they offer shrinks, making it harder for companies to make enough money to cover their initial investments. Make no mistake: there will be high-profile failures as the market separates the genuine innovators from the companies that just slapped the word “AI” onto their marketing brochures.
This brings us to the core financial reality check: the massive gap between what tech companies are spending and the actual business value they are creating. Reputable venture capital firms like Sequoia Capital have publicly warned of the “revenue gap”—often called the $600 billion question. Much like a host city waking up to realize they just spent $100 million on a state-of-the-art bobsled track that might only see occasional use, the tech industry is pouring hundreds of billions of dollars into AI data centers and computer chips. To justify this massive spending spree, the industry needs everyday users and businesses to buy an astronomical amount of AI software, a goal they are currently struggling to meet.
Furthermore, recent reports from major financial institutions like Goldman Sachs highlight that the market is starting to question the long-term survival and competitive advantages of traditional software companies. If a smart AI program ends up doing all the heavy lifting on top of standard software, those older programs might just become basic, easily replaceable utilities. Because of these big unknowns, it is simply too early to draw firm conclusions about the long-term financial impact of AI on entire industries until we see who ultimately holds the pricing power.
Sticking the Landing: Valuation and Diversification
The stock market is always looking ahead, constantly trying to guess what companies are worth today by predicting their future profits. But right now, we are at a stage where there just isn’t enough reliable information to know exactly what the future holds. As the legendary investor Howard Marks once said, navigating “imperfect information and uncertain outcomes” is exactly what good investors do. That advice is as relevant today as it has ever been.
Because of this high uncertainty, the ups and downs of individual stocks have been incredible this year—resembling a chaotic downhill slalom rather than a smooth cross-country ski run. While the overall market averages haven’t moved dramatically, we are seeing investors aggressively jump from one sector to another, turning last year’s losers into this year’s winners, and vice versa. The market is quickly adjusting stock prices as it becomes clearer which companies are actually making money from AI and which are just footing the bill for it.
Ultimately, this environment reinforces the core investment principles we consistently preach—diversification and risk management. Because it is impossible to predict exactly which companies will take home the gold medal in the AI revolution, it is vital to keep your investments broadly diversified across different industries. We strongly advise against chasing the latest craze or knee-jerk speculation. Instead, if you want to reach the podium, keep your portfolio disciplined and firmly aligned with your personal risk tolerance and long-term financial objectives.
Birthdays:
Actress Rashida Jones turns 50, actress Tea Leoni is 60, and talk show host Sally Jessy Raphael is 91 today.
Christopher Gildea 610-260-2235