AlphaSense

Interview with an industry expert on why every major retailer is now building its own shopping agent ($META, $WMT, $TGT, $AMZN): - The expert expects the usual e-commerce flow of searching, browsing a product list, and checking out to fade as shopping agents spread. Retailers are moving from chat-style assistants toward automated agents that know what a customer buys regularly and can suggest a restock and place the order for them. Every retailer is now building its own version. - According to the expert, even in-store purchases can be linked to an online profile when paid with a saved card or the retailer's own payment method. Customers who only shop in-store are harder to identify, so retailers try to bring them online, since more online customers means more agentic shopping. - The expert says everyone is still early in letting external personal agents shop their sites. $WMT lets Muse in, while $AMZN has restricted it. This raises the question of whether outside agents take usage away from a retailer's own agent, and the expert expects a world where agents talk to agents. $META and OpenAI both launched personal agents in the last three weeks, but so far only Muse is well understood. - The expert sees AI shifting from tools people use to do their work toward personal agents that automate recurring manual tasks, with shopping and ticket buying as clear examples. Productivity is rising at every level and in every industry. - The expert flags two open concerns. The first is safety and privacy, since people may be uneasy letting agents handle sensitive matters like health data, taxes, or bank details, particularly when account access is shared across multiple agents. The second is token economics, as companies with billions invested in CapEx still need to show a return from agent subscription plans.

Former $AAPL employee on why $AAPL could become the most trusted AI player ($META, $GOOGL, $AMZN): - The expert sees $AAPL as behind $GOOGL and OpenAI in reasoning capability but holding a structural advantage that is difficult to replicate, centered on personal context. Through its hardware ecosystem, $AAPL is continuously building a detailed profile of who the user is, in a way that no other AI player can match without the user actively feeding that data themselves. The expert sees this personal context layer as $AAPL's real competitive edge in AI, with Apple Intelligence positioned to tap into all of that data in a way that could meaningfully differentiate it from $GOOGL and OpenAI over time. - The expert sees privacy and security as $AAPL's most underappreciated competitive edge in AI, with on-device processing and data not being used to train other models positioning $AAPL as the most trusted player for users who are skeptical of the broader AI ecosystem. - According to the expert, wearables rather than Macs or laptops will be the most important AI hardware category over time, since always-on devices that travel with the user throughout the day are far better suited to proactive AI assistance than session-based devices. The shift toward wearables is seen as the direction the industry is heading, with this always-on form factor creating far stronger stickiness than anything a laptop or desktop can offer. - The expert sees proactive assistance as the capability users do not know they want until they experience it, pointing to an AI tool that, with permission, uses what it knows about a person's plans, calendar, and weather to push timely reminders and advice without being asked. The expert argues that if a tool holds that much personal context but does not act on it proactively, the companies that do push hard on proactive help will ultimately win. - The expert sees services as the biggest category to watch for $AAPL, with tiered subscriptions as a major long-term ecosystem play. A tiered Apple Intelligence offering could add meaningful recurring revenue, but the expert notes $AAPL would first need to make its free Apple Intelligence competitive with ChatGPT, Claude, and Gemini, where it currently falls short.