AI Was Supposed to Save Companies Money. Instead, It’s Blowing Up Budgets in a Big Way

The refrain from executives amid the seemingly-continuous job cuts over the past few months has been a common one: AI can do the job at a lower cost than human workers. But a new report has issued a stark warning: That school of thought is wrong. Very wrong. A survey from KPMG finds business owners are aghast at their bills for AI, now that many AI companies have shifted to a usage-based model. The accounting firm spoke with 2,145 executives around the world, and one-third said they had a limited understanding of usage costs. AI companies used to charge corporate clients a flat rate, but as compute costs have increased, many major operators are switching to a different model to help control costs. That wasn’t factored into some executives’ decisions to go all-in on the technology. “AI is now as much a financial management priority as it is a technology one,” Rob Fisher, global head of advisory at KPMG, said in a statement. “The real risk isn’t investing in AI but doing so without cost visibility and an understanding of the economics of AI. Organizations that have visibility into their costs and maintain strong oversight are the ones translating AI investment into real, measurable value.” Making matters worse, the higher pricing model comes as many businesses are still figuring out how to use AI efficiently. Many did not realize, for instance, the need to build the capabilities required to forecast, monitor, and manage AI spending, the report says. There have been several examples of this in the past year. Uber blew through its entire 2026 AI budget in just four months. (The company has since set usage caps on various AI-powered tools used by its staff.) Another company, which remains unnamed, spent $500 million on AI in just one month, since its employees apparently had no limit on how many licenses they could use. AI companies acknowledge the rising prices but aren’t signaling things will change anytime soon. Last month, OpenAI CEO Sam Altman said in an interview: “People are really saying, ‘My company spent my entire 2026 budget in Q1. Can you make this more efficient?’” And since the start of the year, Altman continued, it went from being “an issue that never came up (people were totally happy with the amount they were spending) to, all of a sudden, a huge issue.” Part of the reason for that new urgency is the escalating cost of new models as AI companies battle for supremacy. Each new top-level release is “roughly twice as expensive per token as the one it replaced,” Arvind Jain, CEO of AI company Glean, told CNBC. Prioritizing people While there has been no slowdown in tech layoffs so far (though Gartner says half of those will be reversed by 2027), a growing number of executives say they’re focusing more on human-AI collaboration, utilizing the advantages of both, and choosing to upskill their remaining workforce. “By putting AI directly into the hands of their people, organizations are better positioned to translate adoption into real business value,” KPMG’s report says. Value is key, as just 7 percent of the executives surveyed said they were seeing a return on investment in AI. Nearly one-quarter of those executives, however, said they were facing pressure to prove the technology’s value to investors. Step one of that is getting a better handle on spending. Some 23 percent said they struggle with usage-based costs, and 42 percent said they only have partial visibility into AI spending. That’s making tools like monitoring dashboards, which track the cost of each employee’s AI usage, more common. And roughly half of the executives say cost reviews have become part of the AI approval process. Companies that take those steps, says KPMG, are five times more likely to report an established ROI. “We’re seeing a clear divide between organizations with leadership accountability at the top and those without,” said Steve Chase, KPMG’s global head of AI and digital innovation. BY CHRIS MORRIS @MORRISATLARGE

Research Says Leaders Are Overlooking 1 Simple Way to Accelerate AI Adoption

Almost every company is doing something with AI right now. Some are testing chatbots. Others are automating workflows, redesigning roles, or asking employees to “use AI more” without much direction. But embracing AI and scaling it well are two very different things. According to the 2025 McKinsey Global Survey on AI, only 38% have successfully begun scaling AI across their businesses. Enter the workforce readiness recession. Employees aren’t falling behind because they’re resistant to AI, but because they lack the confidence, clarity, and reinforcement to embrace it. As AI reshapes the workplace, leaders must become both advocates for change and trusted guides through it. According to Achievers Workforce Institute’s (AWI), leaders under pressure to demonstrate AI ROI may be overlooking one of the simplest ways to accelerate adoption: employee recognition. Recognition isn’t separate from an AI strategy—it’s a practical leadership tool for accelerating adoption. Stop readiness from falling behind AWI’s seventh annual State of Recognition Report finds that just 19% of workers feel confident using AI tools, and only 18% feel supported in adapting to AI. How can companies expect results when over 80% of employees haven’t been given the confidence or support to see where AI fits into their day-to-day work? “Those who create the conditions for employee change readiness will separate the winners from the losers, both in the race to realize AI’s potential and in building a great workplace culture,” said David Bator, Managing Director of AWI. “Employees aren’t going to wake up one day ready to do their best work with AI. Change on that scale is never automatic. Confidence is built brick by brick through everyday leadership behaviors. Leaders who embrace recognition will be the ones who create the confidence, trust, and advocacy needed for AI to scale across their businesses.” AWI’s research shows recognition is most effective when it reinforces learning, adaptability, and progress rather than perfection. Closing the recognition gap closes the readiness gap Leaders have long fallen short on recognition. The first thing AWI advises is to get right is frequency. Every employee should receive meaningful recognition at least monthly to feel supported through change, yet just 19% of workers say they are regularly recognized by their manager. Leaders need to make regular recognition a management requirement, not an afterthought. Then focus on one keyword: meaningful. In the AI era, meaningful recognition isn’t about celebrating AI for AI’s sake. It’s about recognizing the human capabilities behind successful AI adoption. If an employee uses AI to uncover new sales opportunities, don’t recognize the technology, but the creativity, initiative, and business impact behind its use. “A common misconception is that recognition does nothing beyond making people feel good,” added Bator. “While celebrating your people early and often is important, leaders should see appreciation as a change catalyst. When managers reinforce learning, adaptability, and responsible AI use, they recognize good work and help drive organizational progress as AI integrates into daily work.” AI raises the value of humane leadership There’s no denying it: AI is a force of disruption at work. But every major technology transformation has ultimately been about people. A great leader understands this and ensures employees experience change as something they can grow through, not something being done to them. Right now, there is a lot of ground to make up: just 18% of workers feel informed when changes affect their job, and only 23% say communication is clear during uncertainty. Employees are asking for clarity, coaching, and confidence, and leaders can’t delegate that responsibility to AI. Recognition is most powerful when it comes from another human being. In my book, Humane Leadership: Lead with Radical Love, Be a Kick-Ass Boss, I argue that humane leaders exhibit two essential qualities —trustworthiness and advocacy —that matter even more in the AI era. Leaders bring clarity to AI by using recognition to reinforce what good work and responsible behavior look like during rapid change. Done well, recognition helps employees trust themselves, trust their company, and understand what great work looks like in a workplace being reshaped by a technology we have never seen before. EXPERT OPINION BY MARCEL SCHWANTES, EXECUTIVE COACH, SPEAKER, AND AUTHOR @MARCELSCHWANTES

IBM’s CEO Has a Message for Founders: Treat AI as ‘Day Zero’

We’re fast approaching the fourth anniversary of the launch of ChatGPT, meaning artificial intelligence has been a part of the business conversation for quite some time now. Many companies have experimented with it or attempted slow roll-outs in select areas of their operations. But IBM CEO Arvind Krishna says the days of sticking your toes in the water are over. It’s time to jump in. The rollout of the technology, he says, should be treated as a “Day Zero” event, a chance to reset the competitive race among businesses. But to do that, your business needs to start implementing AI at scale. “It’s time to sit down and take it seriously,” Krishna said on the Masters of Scale podcast. “You’re not in the experimentation phase. Day Zero, the race is about to start. Put yourself in the blocks and start sprinting.” Krishna says he isn’t talking about incorporating AI in every aspect of your company or automating a large percentage of the workforce. Instead, he recommends fully embracing AI in some aspects of your business as a case study of sorts to help you better understand what it can do for you. From there, you can expand your use of AI. “Take three, four, five things—not 100—and learn how to do them at scale, because that’ll teach you how to get all your change management done,” he said. “How do you get your data organized? How do you really get people motivated to change a process? Do a few things at scale. Learn how to do that really well. Then do 10—and then give yourself the confidence to do the next 20.” Despite all the talk of AI, Krishna estimates that just 20 percent of businesses are utilizing it correctly. The rest, he says, are not getting a return on their investment or don’t quite know what to do with it. Incorporating AI might mean bringing on new staff in some cases. And while the instinct of some founders will be to search for an AI expert, Krishna says the smarter move is to find someone who understands the difference AI can make for your company. “Find that 20 or 30 percent who are motivated to say, ‘I want to learn a new way to do things,’” he said. “I think curiosity and willingness to adapt are more important.” When it comes to measuring the returns of AI on your business, that too is going to require a shift in mindset for business owners, Krishna said. Efficiencies and savings aren’t going to be immediate, he warned. In fact, there could be additional expenses. For the first six months to a year, he said, businesses will likely spend more than they save, as they dedicate engineers to implementation and pay for tokens. But as companies operate AI at scale for a use case, they learn how to implement the technology, making subsequent rollouts cheaper. IBM played its part in introducing the world to AI with Watson, which made headlines when it won on the TV show Jeopardy! But that awareness was also a wake-up call to other companies, which began to invest in AI very heavily while IBM did not, said Krishna. “As opposed to creating building blocks, we wanted to create solutions in verticals. That, I think, is a mistake, as technology shows,” he said. Today, the company isn’t trying to be OpenAI or Anthropic. Instead, it’s betting on AI orchestration—the coordination of multiple AI models into a single workflow. It’s also focused on Enterprise AI, providing businesses with tools to build, scale, and govern artificial intelligence. Lately, there has been growing consumer pushback to AI. One recent report from AI platform Parloa found that during automated customer-service calls 61 percent of respondents have screamed at automation to get routed to a human faster. A separate survey from WordPress VIP, which offers an enterprise version of the publishing platform, found that 60 percent of the people it polled found AI in a brand’s messaging to be a turnoff, not a feature. Meanwhile, some companies that went all-in on AI are starting to realize the real cost of the technology. Uber, for instance, exhausted its 2026 AI budget in just four months and was forced to cap employee use. And several companies that fired workers in favor of AI are bringing those employees back. Krishna argued that companies that don’t incorporate AI ultimately face even more potential problems. “The riskiest route is taking zero risk,” he said. “What happens in any business that takes no risk? It means you’re trying to extract profit—or what an economist would call rent—from what you already have. But that means you’re giving everybody else the opportunity to clone you or copy you, to innovate from the bottom, and pick off the most profitable parts of your business.” BY CHRIS MORRIS @MORRISATLARGE

Microsoft and LinkedIn Just Analyzed the Future of Work and AI. It All Points to 1 Key Skill Set

Algorithms can now write code, draft legal contracts, and generate entire marketing campaigns in seconds. As artificial intelligence automates increasingly complex work, it’s easy to assume technical expertise will become the defining trait of great leadership. The evidence points in the opposite direction. Recent data from Microsoft and LinkedIn reveals a fascinating reality. While AI is automating execution, leaders are aggressively prioritizing soft skills like emotional intelligence. As tools become more artificial, humans crave the authentic. The ultimate competitive moat is no longer technical execution. It is the ability to forge genuine human connection. If you are a founder or an executive, community building fueled by high emotional intelligence is the single most important leadership skill you must master. The isolation crisis A massive psychological shift is happening in the workplace. Gallup research confirms that employee stress remains at record highs, and loneliness is a massive factor. When you introduce generative models into your daily operations, your team members spend more time prompting machines and less time talking to each other. This creates a vacuum of trust. Humans are biologically wired for social connection. When people feel isolated, their brains enter a state of chronic stress. You can deploy the most advanced foundational models in the world, but if your team feels disconnected, your output will plummet. The smartest leaders recognize that their job is not to manage workflows. Their job is to manage energy and connection. The empathy premium When technical output becomes a commodity, what becomes scarce? The answer is human resonance. The American Psychological Association recently found that workers who are worried about artificial intelligence are significantly more likely to feel tense, stressed, and isolated. A machine can generate a flawless and sterile piece of text. A human brings vulnerability, shared struggle, and nuanced understanding. In a market flooded with synthetic perfection, people will pay a premium for authentic imperfection. The same principle applies to your internal culture. Your team doesn’t want a flawless manager who acts like an algorithm. They want a leader who understands their anxieties about the future of work. They want someone who can build a safe environment where it is acceptable to experiment, fail, and learn together. Empathy is the engine of psychological safety, and psychological safety is the engine of true innovation. Your blueprint for human connection How do you operationalize emotional intelligence and community building inside your company? It requires a deliberate approach to how you structure your daily operations. Optimize for unstructured connection. Don’t just schedule meetings for status updates—a machine can read a status update. Instead, create intentional spaces where your team can connect over shared interests, challenges, and ideas without a rigid agenda. Reward vulnerability over perfection. If you want your team to trust you, you must go first. Share your own challenges and uncertainties about navigating the new tech landscape. When leaders admit they don’t have all the answers, it gives the team permission to be honest and collaborative. Elevate human milestones. Algorithms don’t care about birthdays, work anniversaries, or personal triumphs. You must. Celebrate the unique human moments that machines cannot replicate. The future of leadership isn’t about competing with algorithms. It’s about doubling down on the things algorithms can’t do. Step away from the dashboard, look your team in the eye, and start building a culture rooted in genuine connection. EXPERT OPINION BY ASH KUMRA