Microsoft (NASDAQ: MSFT) recently published a blog post about its new AI Agents, outlining what they are, how they work, and their potential applications. At first glance, this announcement sounds familiar because, in many ways, these Agents are a rebranding of Microsoft’s Copilot product.
Microsoft describes AI Agents as generative artificial intelligence tools that can be tailored to perform specific tasks by leveraging data from the Microsoft Office suite to execute multi-step processes autonomously. While Copilot already provides many of these capabilities, Agents expand on them by improving memory, integrating with external systems, and enabling more complex workflows.
The shift from Copilot to AI Agents seems to be more than a rebranding. It feels like Microsoft is addressing a gap in how its customers use AI. Many users haven’t fully tapped into Copilot’s potential, and the blog post reads like an early step in a broader re-education initiative. Microsoft appears to be laying the groundwork for helping users understand how to maximize their AI tools—not just within Office but as part of their daily workflows.
At nearly every opportunity I get, I mention how most people use AI as a glorified search engine rather than using it in ways to get the most out of the system. AI tools can have a significant impact on how we work and live, streamline many processes, save resources, and increase our overall efficiency. However, it seems like many users just haven’t dug deeper with AI or figured that out yet. From what I see, it does seem like many users need more guidance if they are looking to get the most out of their AI tools of choice. Microsoft’s move could be the start of a broader industry trend where companies invest more heavily in user education, providing step-by-step guides that allow their users to better integrate their AI into their personal and professional lives.
Meta’s push to monetize AI
Meanwhile, Meta (NASDAQ: META) has appointed former Salesforce (NASDAQ: CRM) CEO Clara Shih as its new “Head of Business AI.” According to Shih, “Our vision for this new product group is to make cutting-edge AI accessible to every business, empowering all to find success and own their future in the AI era… Meta’s global reach and leadership in AI represent a generational opportunity for businesses, and I couldn’t be more excited and grateful to help take this from zero to one to scale.”
The move signals Meta’s growing focus on profitability in AI. It’s no secret that many artificial intelligence companies struggle to profit. The infrastructure required to train and run advanced models comes at a massive cost. In contrast, the revenue they collect through subscription models that offer customers access to “better” AI tools recoups only a fraction of the companies’ expenses.
The purpose of Meta’s Business AI group seems to be to turn this around by productizing their AI offerings—packaging them into marketable products that attract paying customers and drive significant revenue growth for the business. This shift in strategy isn’t unique to Meta; it reflects a broader trend in the AI industry. It has become clear that many companies’ AI divisions are increasingly finding themselves under pressure to figure out monetization as investors start asking when they will see returns.
The narrative around AI seems to be shifting from “AI is revolutionary” to “Who’s making money from AI, and how soon can we expect returns on our investments?” It’s an important question because the industry could face a wave of business closures and mergers without a clear path to profitability. If companies can’t find a financially viable strategy for their AI divisions, we may soon see a consolidation of players in the AI space.
Nvidia’s overheating chips and strong earnings
A report said that Nvidia’s (NASDAQ: NVDA) Blackwell chips are prone to overheating when added to servers, creating significant challenges for data centers. To address the issue, service providers must redesign their racks, an expensive and time-consuming process.
Despite that negative press, Nvidia’s Q3 earnings report exceeded analyst expectations. The company posted adjusted earnings per share of $0.81, representing a net income of $19.3 billion, compared to predictions of $0.75 EPS and $17.4 billion net income.
However, even with these substantial numbers, Nvidia’s stock dropped by roughly 2% when the market opened the next day. This trend—where companies beat earnings expectations but experience a decline in share prices—has become increasingly common. This stems from the market’s perception that a company with strong current performance has less room for growth in the upcoming quarters. In Nvidia’s case, their Q4 guidance of $37.5 billion in revenue, only slightly above Wall Street’s $37 billion projection, reinforces this idea.
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