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Franklin Templeton CEO Questioned AI Productivity Gains

Business owners should note that current productivity growth reflects older digital tools, not recent AI investment.

Updated on Sept. 24, 2026 in Economic Indicators

Isometric editorial illustration of a modular server hardware rack, representing established digital infrastructure in the U.S. economy.
Franklin Templeton CEO Jenny Johnson noted that current U.S. productivity growth is tied to existing digital infrastructure rather than recent AI-focused capital expenditures. AI Illustration. Upload story photo >

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Do you believe current heavy investment in AI is already delivering measurable improvements to the economy?

Franklin Templeton CEO Jenny Johnson reported that artificial intelligence has not yet meaningfully improved U.S. productivity, despite heavy capital spending by major tech firms. Current productivity gains are instead being attributed to earlier digital technology integrations and cloud computing.

Why it matters

While AI is a focal point in over 65% of S&P 500 earnings calls, businesses have yet to realize broad, systemic economic efficiency. Owners should be aware that the surge in capital spending on data centers and power has not yet translated into measurable output increases.

U.S. nonfarm-business productivity rose 2.2% year over year in Q2 2026, while 18% of U.S. businesses had adopted AI by year-end 2025. Major technology companies are expected to spend $630 billion on AI infrastructure in 2026.

The players

Jenny Johnson

The CEO of Franklin Templeton, a global investment firm managing nearly $1.8 trillion in assets.

PwC

A professional services network that conducts annual global surveys on executive sentiment and corporate strategy.

Federal Reserve

The central banking system of the United States that monitors economic health and sets monetary policy.

The details

Businesses typically prioritize upgrading existing workflows with mature technology before realizing the efficiency benefits of newer, experimental tools. Currently, companies are heavily funding capital-intensive AI requirements like data centers and power, but the systemic integration of these technologies into the broader economy is still in its infancy. Tight credit spreads of 65 basis points for Single-A corporate debt suggest that market confidence remains sustained by consumer spending and record earnings rather than AI-driven margin expansion.

Timeline

  1. 18% of U.S. businesses had adopted AI by the end of 2025.

  2. Quarterly annualized productivity growth was 0.8% in Q1 2026.

  3. Nonfarm-business productivity rose 2.2% year over year in Q2 2026.

  4. Single-A corporate spreads stood at 65 basis points on September 22, 2026.

  5. Major technology firms are expected to spend $630 billion on AI infrastructure throughout 2026.

Market Landscape

This development follows the trend documented in the 2026 PwC CEO survey on AI integration, which highlights a widespread lack of immediate financial realization from AI investments. It contradicts the high volume of AI-related discourse occurring during quarterly earnings calls.

Operators should view AI spending as a long-term capital expense rather than a source of immediate efficiency gains. Budgeting for 2027 should prioritize core operational stability while treating current AI infrastructure costs as speculative investments.

The takeaway

The data suggests that AI-driven productivity is not yet a reality for most businesses, meaning efficiency must come from optimizing existing processes. Monitor your upcoming quarterly earnings for concrete cost-saving metrics rather than qualitative mentions of AI adoption.

Further reading

For more on shifting macroeconomic trends, visit the Economic Indicators section.

Live Poll

Do you believe current heavy investment in AI is already delivering measurable improvements to the economy?