Perplexity CEO Says 2028 IPO Plan Remains on Track
Miles Bennett
Perplexity CEO Aravind Srinivas confirmed the company still plans to go public in 2028 — regardless of how Anthropic's and OpenAI's IPOs play out — but acknowledged their performance will shape fundraising sentiment across AI.
Why is Perplexity locking in 2028?
Srinivas told CNBC in an interview aired Tuesday that the 2028 listing timeline stands.
His earlier phrasing was softer — "no plans to go public before 2028." This time the signal is sharper: the target is 2028 itself.
This means → Perplexity is giving itself roughly three years to build revenue and product to IPO-grade scale.
Three giants filing at once — what does it mean for AI?
Anthropic filed its IPO confidentially last week; OpenAI filed Monday. SpaceX's listing this week will test the water first.
Srinivas was blunt: SpaceX's IPO will be a leading indicator of how much appetite investors have for mega-cap tech offerings.
In plain terms = these three IPOs are a chain test. If the first one lands well, the path clears for the rest. If it stumbles, the ripple effect hits the entire AI fundraising landscape.
Can these sky-high valuations hold?
Srinivas said Anthropic and OpenAI deserve their high valuations because they sit in the frontier-model tier — the most capable AI models available.
But he added a condition: investors will keep watching innovation velocity — "If for six straight months you don't see progress in model capabilities, that's a problem for them."
This means → a high valuation is not a permanent pass. It is essentially a bet on continuous breakthroughs. The moment progress stalls, the valuation logic weakens.
Is enterprise AI spending shifting?
Srinivas observed that customers are choosing models more selectively, not blindly ramping AI consumption.
His example: if an open-source model handles 90% of tasks at 10 to 20 times lower cost than a frontier model, customers will likely pick it.
Perplexity's own product runs on models from multiple providers, matching each task to the best model by capability and cost.
This reflects a broader shift — AI spending is moving from "throw money without judgment" toward deliberate allocation. The outlook for frontier models remains strong, but the era of indiscriminate spending is ending.
Content is for reference only, not financial advice.