Stock Markets July 28, 2026 08:55 AM

Franklin Templeton: AI-Led Advance Not a Replay of the Dotcom Run

Firm highlights structural differences as the S&P 500’s AI-fueled rally lags the late-1990s internet cycle on length and magnitude

By Maya Rios
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Franklin Templeton’s Director of ETF Investment Strategy, Marcus Weyerer, says the current market upswing driven by artificial intelligence diverges from the late-1990s internet boom. While the S&P 500 has climbed 108% from its 2022 low through week 188 of the present rally, that gain is smaller than the 127% rise recorded in the equivalent stretch of the dotcom cycle. Weyerer points to stronger profitability, multi-layer business models and heavy infrastructure spending as distinguishing features of today’s leaders.

Franklin Templeton: AI-Led Advance Not a Replay of the Dotcom Run
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Key Points

  • The S&P 500 has risen 108% from its 2022 low through week 188 of the current rally, versus a 127% gain in the equivalent period of the late-1990s cycle - the current advance is shorter and smaller in magnitude.
  • Many modern AI leaders operate across multiple layers of the ecosystem - chips, cloud infrastructure, software platforms and proprietary data - which may support pricing power and margins; sectors impacted include semiconductors, cloud providers and software.
  • Capital-intensive AI infrastructure spending on semiconductors, memory, electricity and data centres is creating higher barriers to entry and drawing investor interest toward infrastructure suppliers - affecting data centre operators, utilities and hardware suppliers.

Franklin Templeton’s head of ETF investment strategy, Marcus Weyerer, cautions that while some observers liken today’s AI-fueled market surge to the late-1990s internet boom, important differences exist.

Measured from the 2022 low through week 188 of the current rally, the S&P 500 has risen 108%. By comparison, the index gained 127% over the same relative period during the late-1990s cycle. That means the present advance is both shorter in duration and smaller in magnitude than the dotcom-era rally at the comparable point.

Weyerer framed the comparison as incomplete, saying: "We understand the questions surrounding whether today’s AI rally resembles the late-1990s internet boom, but in our view the comparison is imperfect." He argued many of the most hyped names from the earlier era lacked profitability, free cash flow and lasting competitive advantages.

He contrasted that earlier cohort with many of today’s AI leaders, noting they tend to participate across several layers of the AI ecosystem. "Many of that era’s most hyped companies lacked profitability, cash flow and sustainable competitive advantages. By contrast, many of today’s leaders operate at multiple layers of the ecosystem - including chips, cloud infrastructure, software platforms and proprietary data - which may help preserve their pricing power and margins for considerably longer."

Weyerer also emphasized the capital intensity of AI infrastructure as a material differentiator. He pointed out that building and scaling AI requires significant investment across semiconductors, memory, electricity, data centres and other digital infrastructure, which raises barriers to entry relative to some previous technology cycles.

On shifting market focus, Weyerer observed: "Investor attention has shifted from the hyperscalers building AI applications towards the picks-and-shovels businesses supplying the infrastructure that makes them possible." He added, "To us, this signals a maturing of the AI investment cycle rather than a fading of the theme."

The commentary arrives as several major AI-related companies are scheduled to report earnings this week, providing fresh results that market participants will watch for confirmation of revenue, margin and capital expenditure trends.


Context and takeaway

  • The S&P 500’s 108% gain from the 2022 low through week 188 is less than the 127% increase recorded in the equivalent phase of the late-1990s cycle.
  • Franklin Templeton highlights stronger profitability and multi-layer exposure among current AI leaders versus many dotcom-era firms.
  • Heavy capital requirements for AI infrastructure - including semiconductors, memory, electricity and data centres - are cited as increasing barriers to entry and shifting investor attention toward suppliers of that infrastructure.

Risks

  • Upcoming earnings from major AI-related companies could alter market sentiment and influence sector valuations - this directly impacts technology and cloud-related equities.
  • The heavy capital requirements for AI infrastructure create execution and financing risks for companies across semiconductors, memory, and data-centre operations; these sectors could face margin or cash-flow pressure if spending or demand shifts.
  • Although Franklin Templeton views the comparison to the late-1990s boom as imperfect, ongoing valuation concerns remain a potential uncertainty for market participants monitoring AI-driven names.

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