Apple is reportedly contemplating acquiring Perplexity AI, an artificial intelligence startup known for its real-time web search engine. According to Bloomberg News, discussions are in the early stages, with Apple’s M&A chief Adrian Perica exploring the idea with key executives, including services head Eddy Cue and AI decision-makers.
While there’s no certainty the deal will proceed, such a move could help Apple improve its AI offerings, especially in search, vital as the company faces the potential end of its long-standing Google search partnership on Apple devices.
Perplexity’s search platform provides users with quick, current answers by pulling information directly from the web, handling around 780 million queries monthly, a figure that’s grown over 20% month-over-month. An acquisition could enable Apple to build its own AI-driven search engine, reducing reliance on Google and enhancing the user experience with more intelligent, real-time responses.
The timing of any potential deal might depend on the outcome of an ongoing antitrust trial involving Google, as Apple seeks clarity on whether its exclusive search deal could be terminated soon.
Perplexity stated to Bloomberg that there are no current or future acquisition talks. Apple has not provided an official comment, and PYMNTS has reached out for further details. The company’s approach to AI has traditionally been cautious and focused on narrow, integrated features like voice transcription, enhanced Spotlight search, call screening, and translation, rather than adopting large-scale language models or enterprise AI solutions that rivals like Google, Amazon, and Microsoft are actively pursuing.
Experts and observers are now questioning whether Apple’s slower, more conservative strategy might leave it behind in the rapidly evolving AI landscape. While competitors are developing powerful cloud-based AI platforms and APIs to enable advanced multimodal and customizable AI applications, Apple’s focus remains rooted in consumer hardware and tightly integrated experiences.
This cautious stance might be strategic, or it could risk strategic drift as the broader AI economy moves toward more open, cloud-based solutions that rely on flexible APIs and extensive datasets.
