How is META TikTok Disruption an Analog for GOOG vs GPT?

Investing.com -- Meta’s experience countering TikTok’s rapid rise is increasingly viewed as a parallel to Alphabet’s (NASDAQ:GOOGL) current efforts to address competition from generative AI platforms like OpenAI’s ChatGPT and Perplexity.

Morgan Stanley analysts point to clear analogs in market reaction, product response, and valuation recovery.

From Q1 2020 to Q4 2022, TikTok’s U.S. user base more than doubled, from about 50 million to 110 million, with average engagement hitting roughly 90 minutes per user per day. 

This surge drove concerns about Meta (NASDAQ:META)’s competitive positioning, contributing to a decline in its price-to-earnings (P/E) multiple to around 8x by late 2022, compared to a long-term average of 20x.

Meta responded with Reels, closely modeled on TikTok’s short-form video format. Reels leveraged Meta’s existing user reach and data infrastructure, shifted the company’s model from a social graph to an entertainment graph, and drew in more diverse content types. 

Crucially, Meta improved transparency by providing monetization and engagement disclosures. 

Over time, this helped slow TikTok’s growth and contributed to Reels reaching a $10 billion revenue run rate by mid-2023. 

By late 2023, Reels became net neutral to ad revenue and helped push Meta’s multiple to as high as 27x.

Alphabet’s P/E multiple similarly compressed to approximately 14x, down from a historical 20x, amid fears that new AI-powered entrants could erode its core search business. 

But Morgan Stanley notes Alphabet is now executing a similar playbook: accelerating generative AI product launches (e.g., Gemini and Bard), deploying them across its massive user base, and disclosing clearer signals of incremental value.

Despite competitive noise, Alphabet’s traffic remains dominant. In early 2025, its combined search and AI tools generated approximately nine times the traffic of ChatGPT, according to data cited by Morgan Stanley. 

Still, the brokerage highlights that investors will need further evidence that Google’s AI-driven offerings can produce durable revenue growth to justify a sustained rerating to 20x+.

Morgan Stanley maintains an “overweight” rating on Alphabet, with a price target of $185, implying ~10.9x 2026e EBITDA. Upside drivers include better-than-expected AI monetization, expense discipline, and continued search share gains. 

Risks include weaker-than-expected ad growth, AI monetization pressure, or rising costs. For Meta, Morgan Stanley’s $650 price target reflects a 12.2x 2026e EBITDA, citing improving Reels monetization and platform engagement as key strengths.