Profit margins outside the tech sector so far show no sign of rising from AI, according to a June 30 analysis from Apollo Global Management chief economist Torsten Slok. He wrote that many industries need to reshape workforce operations before realizing returns from AI investments.
Pressure on leaders for AI ROI
An IBM study of CEOs found that only about 25% of AI initiatives deliver the ROI leaders expect, and just 16% have scaled across the enterprise. CEOs told IBM they are weighing pressure for near-term returns against longer-term innovation goals.
Slok’s note arrives amid increasing boardroom pressure to show outcomes from AI spending. He says stock prices reflect what investors expect a company to earn in the future and right now, and that stocks across the S&P 500 are priced as if AI is going to make all these companies meaningfully more profitable soon.
Sectors most impacted
Software and tech companies, including those providing platforms for HR and enterprise workforces, can fold AI into their own products almost immediately, and Slok says this makes them an exception.
Slok suggests most of the economy will move slower, and the slowest adopters will be industries built on expensive physical assets and close government oversight. Companies in these sectors first have to rebuild how work gets done, which involves retraining employees and redesigning workflows, and they have to clean up and secure the data the tech depends on, often under hefty legal constraints.
Slok expects those “deep process re-engineering and data governance requirements” to slow AI payoff across a big chunk of the economy. This includes healthcare, banking and insurance, energy and utilities, defense and aerospace, pharma and life sciences, manufacturing, transportation and logistics, construction and real estate, education, legal and the public sector.
He also warns that companies will pull back on AI spending if returns don’t show up quickly, and that the productivity curve could take years rather than months. “The bottom line is that a mismatch between current earnings expectations and the actual time firms need to generate ROI on AI investments could have significant implications for many AI company valuations today,” according to Slok.
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