Recent reports, which have been making significant headlines lately, indicate that Microsoft is lowering its sales quotas for AI software, which is quite intriguing. We’ll need to explore further to understand the full implications, but this suggests that if quotas are being reduced, the growth in AI software sales might be slowing down, which seems to have caused a slight dip in the company’s shares. It’s unclear whether this is due to a slowing adoption curve or increased competition; at this point, we don’t have enough information to be certain. Nonetheless, this situation highlights the competitive dynamics and jockeying for position among these companies. Moreover, the broader discussion around AI adoption remains ongoing. We frequently talk about what these companies are doing and the revenues they generate. For example, a significant portion of Microsoft’s revenue is tied to its partnership with OpenAI. Recently, they have expanded this agreement, allowing them to collaborate with other AI providers and offer cloud services to them. OpenAI, in turn, can seek cloud services from other providers who may have greater capacity currently. Still, Microsoft relies heavily on OpenAI’s capabilities.

They mention strong growth from software sales and consumer business customers increasingly adopting AI features. However, until we see concrete figures detailing user numbers, payment levels, and profit margins, much of this remains speculative regarding actual AI usage. When comparing OpenAI and its Sensor Tower data to Google and its Gemini platform, several questions arise: Are users engaging with the Gemini app directly?Are they utilizing Google’s Gemini-powered features?Are they using Gemini in Google search, Gmail, or applications like Docs?There remains considerable uncertainty about precisely which aspects are being used and to what extent. Another key issue is who is paying for these services. Many users of Gemini, especially through Gmail, do not pay directly for it. Similarly, ChatGPT operates on a freemium model. This raises important questions about monetization, which will be critical going forward as we try to understand the market impact and user adoption of AI technologies.