To build trust, users need Awareness (know when AI is active), Agency (have control over it), and Assurance (confidence in its outputs). This framework, from a former Google DeepMind PM, provides a clear model for designing trustworthy AI experiences by mimicking human trust signals.

Google's strategy of integrating its AI, Gemini, directly into its widely-used Chrome browser gives it a massive distribution advantage over standalone tools like ChatGPT. By making AI a seamless part of the user's existing workflow, Google can make its tool the default choice, which marketers must optimize for.

Contrary to popular narrative, Google's AI products have likely surpassed OpenAI in monthly users. By bundling AI into its existing ecosystem (2B users for AI Overviews, 650M for the Gemini app), Google leverages its massive distribution to win consumer adoption, even if user intent is less direct than visiting ChatGPT.

While ChatGPT is still the leader with 600-700 million monthly active users, Google's Gemini has quickly scaled to 400 million. This rapid adoption signals that the AI landscape is not a monopoly and that user preference is diversifying quickly between major platforms.

As consumers become wary of "AI," the winning strategy is integrating advanced capabilities into existing products seamlessly, like Google is doing with Gemini. The "AI" branding used for fundraising and recruiting will fade from consumer-facing marketing, making the technology feel like a natural product evolution.

While ChatGPT still dominates (90% usage), Google Gemini has surged from 33% to 51% adoption in just one year. This rapid growth is likely driven by its deep integration into the Google Workspace ecosystem that businesses already use and pay for.

In a future where Google can synthetically create content, the ultimate differentiator is brand. As Google co-founder Larry Page noted, "brands are the signal in the cesspool." Businesses must focus on building brands that people know, love, and visit directly. This creates a defensible moat that can't be replicated by AI-generated content.

Unlike consumer chatbots, AlphaSense's AI is designed for verification in high-stakes environments. The UI makes it easy to see the source documents for every claim in a generated summary. This focus on traceable citations is crucial for building the user confidence required for multi-billion dollar decisions.

Unlike chatbots that rely solely on their training data, Google's AI acts as a live researcher. For a single user query, the model executes a 'query fanout'—running multiple, targeted background searches to gather, synthesize, and cite fresh information from across the web in real-time.