What The Latest Read On Inflation Means For AI

In this article, I will explain how several macroeconomic factors (inflation and much more) are converging and how that impacts everything from AI jobs to the AI startup ecosystem. Understanding how the pieces fit together will help you skate to the biggest opportunities and avoid the layoff waves to come.

The US Federal Reserve's most important metrics are employment levels and inflation. Chairman Powell calls it ‘the Fed’s dual mandate’ to keep the job market strong and inflation at 2%. In less than a week, we saw the indicators of a cooling employment market and rising inflation. US interest rates will remain higher for longer, which has a powerful ripple effect on tech, especially AI.

AI Jobs Are Strong, But Companies Are Getting Weaker

Retail is the leading indicator of what’s to come as the renewed competition takes its toll on businesses with too much technical debt to remain competitive. Over 15,000 stores will close in 2025, spread across Macy's, Kohl's, JCPenney’s, 7-Eleven, Big Lots, and many more. It all comes down to pricing power, which is a company’s ability to raise prices to increase margins or pass along cost increases to consumers. The trend hit retail early. Store closures and bankruptcies are the late stages.

Consumer price sensitivity is rising in the US, and consumers are changing their behaviors. Businesses will soon follow, and the AI spending spree could be headed for a massive correction, but not for the reasons most predict.

The strongest signal on the health of the US consumer comes from McDonald’s recent earnings call. It reported growth in international store sales but a decline in the US. People here spend less per visit at McDonald’s. The company was forced to turn to price cuts to keep its restaurant traffic stable, especially with the E. coli outbreak it had last quarter.

Contrast that with Taco Bell, which posted a 5% same-store sales increase last quarter due to customers associating its menu with value and low prices. McDonald’s increased its menu prices significantly over the last 3 years, and customers are telling the company that it doesn’t have the pricing power to support them. The only response is discounting, which erodes profitability. Lower profits mean less money to spend on AI, and this isn’t just a fast food problem.

Consumer spending on streaming services shows the same signal. Between 2021 and January 2024, household spending on streaming services increased by 70%. In the last year, the amount spent on streaming has dropped by 23%. Companies like Netflix have proven their pricing power with multiple price hikes during the spending downturn, while others are resorting to bundling and price cuts to maintain subscriber levels. A shakeout is inevitable, leading to a few acquisitions and some companies going under. Acquisitions mean consolidating data and AI teams and infrastructure…and less money spent on AI.

Competition Is Back

The trend that’s already hit retail is spreading to an increasing number of industries. Consumers aren’t spending less. They’re moving their spending to companies that provide the greatest value. Competition is back because the US Federal Reserve has tightened interest rates, which reduces the monetary supply. Low interest rates create more money to be spent, and growth happens organically.

Higher for longer forces growth to come from competition or taking customers from other businesses. The “everyone wins” economy has been replaced by a return to the zero-sum game. As I have explained for 2 years, there will be clear winners and losers. Noncompetitive businesses will contract to match lower demand. If they can’t reverse the trend, they’ll fail. Both lead to less money spent on AI by laggards and lower AI demand caused by business failures.

The jobs report showed the leading indicator of job market health, job openings, is falling. Companies are spending less in some parts of the business to free up money for AI. If AI can’t quickly reverse the skid by generating growth and efficiency, the business will be forced to cut back on AI spending. Competitors are taking customers. Laggards lack pricing power. The pie isn’t growing organically.

Startups won’t be spared either. Many are a year or more away from profitability. They’re running out of cash as the AI arms race takes all the funding. Lower interest rates would pump cash back into the ecosystem, creating more demand for startup deal flow. This latest inflation report means that loose monetary policy won’t be coming to the rescue.

Competition for VC funding will force unprofitable startups to lower their valuations enough to attract a large incumbent to buy them. Others will fail outright and be sold for parts. Startups employ a lot of data and AI talent, so this will be a small but significant reduction in demand and AI spending.

The Great Business Dying & AI Spending

In my book, ‘From Data to Profit,’ I called this the Great Business Dying. Businesses are vulnerable, and it’s showing up in the data. Technical debt will be a key driver in determining the winners and losers. Over half of Taco Bell’s parent company (Yum Brands) sales are digital. That’s an area McDonald’s has struggled with so severely that I use the company as a case study in my courses for a worst-case scenario.

Amazon and Walmart are winning in retail on the strength of their technology platforms. Southwest Airlines is being throttled by more technically capable competitors. As it raised prices, customers abandoned Southwest Airlines for better-priced alternatives or more technically capable competitors.

The message is clear from retail to streaming, fast food, and air travel. Compete on price and watch your growth and margins collapse, or compete on value, with technology being a massive differentiator.

The problem is that even if business leaders realize they must improve their technology platform to survive, technical debt and lower margins often make this impossible. The business doesn’t have the free cash flow to invest in a technology platform makeover, and borrowing costs have risen significantly due to interest rates. Technical debt makes transforming and optimizing the technology platform more expensive, so years of pushing updates down the road are returning to haunt thousands of companies.

Three years ago, McDonald’s laid off, cut back, and sold off most of its technology organization. It invested heavily in modernization, but the ROI never materialized. Initiatives stalled due to cultural and strategic debt. I explain both in my book, and when you combine technical, cultural, and strategic debt, you get a massive drag on the business’s ability to adopt and effectively deploy AI.

Businesses hit a tipping point where their transformation rate is too slow to ever catch up with competitors. No matter how much they spend on AI, the business and operating models won’t transform fast enough to monetize the technology. At the same time, laggards face competitors who transform faster and are more effective at monetizing AI.

No matter what the primary cause (strategic, cultural, or technical debt) laggards can’t catch up to AI leaders and won’t be able to compete on value. The result is a loss of pricing power. Discounting and lower demand put the business into a downward spiral. While demand for AI will remain high, the number of companies with the free cash flow to spend on AI is dropping.

What Should You Do?

From a career perspective, find a safe haven company. Companies with low technical debt deliver products and features every quarter. Technical product and platform quality are high, and issues are resolved quickly. Outages are rare and many are resolved before the impacts are noticed.

Companies with low strategic debt are forward-looking and pragmatic. Strategy is actionable and prescriptive. What they announce during their earnings calls gets delivered with the promised features and functionality. They meet or exceed earnings targets and are investing in AI for growth, not just cost savings.

Companies with low cultural debt have growth and continuous improvement mindsets. High-maturity businesses have adopted disruptor and continuous transformation mindsets. People are open to new ideas, not afraid to fail, and care more about fixing than blaming.

From a business perspective, optimizing the business’s transformation rate is critical to survival. Adopting a technology model that augments and expands the business and operating models is equally crucial. It’s time to go all in on addressing the three sources of business debt to escape the downward spiral or managed decline.

Find opportunities to leverage data and AI to drive growth and make the business more efficient. Keep the focus on value and deliver quarterly. Make improvement a daily goal and transformation a quarterly deliverable. Become more competitive in every dimension.

For business and career success, start now. There was plenty of time to get this done when I first explained these trends. There isn’t enough time now to make a few wrong turns or to wait and see. Optimization is everything. Get the technical strategy and product frameworks right the first time.