A key question is on everyone's mind: how are companies using GenAI? 
WSJ attempts to answer this question (see link below). Here's what I found relevant from the article:
Automating existing workflows: Companies are using AI to speed up processes that were already being streamlined with older automation tools. The big difference now is that AI can handle "unstructured data"—meaning it can read and extract information from things like emails, Word documents, and PDFs that older software couldn't easily process. This lets companies connect messy, human-written content to their existing automated systems.
Summarizing content: One of the most common uses is having AI condense large amounts of text—reports, documents, meeting notes, research—into shorter summaries. All this is widespread it's "not that exciting."
Research tasks: AI is handling what the reporters call "really boring research"—the kind of tedious information-gathering that used to eat up employee time. I've found DeepResearch to be an excellent tool to do a first pass at an exploratory research task. At a minimum, you get a list of links that can be a good starting.
Customer service: AI is answering customer calls and powering chatbots. The reporters note that while the technology has existed for years, companies were initially afraid to let AI talk directly to customers (worried about hallucinations, mistakes, or even hacking incidents where chatbots were manipulated into saying inappropriate things). For what can go wrong, check out Air Canada's experience.
Writing code: Developers are using tools like GitHub Copilot and Claude Code to help write software. One reporter mentioned that companies are rethinking hiring because of this—instead of hiring 100 engineers, they might only need five if AI handles some of the coding work.
WSJ attempts to answer this question (see link below). Here's what I found relevant from the article:
AI at Work: Big Promises, Small but Steady Gains
Despite bold claims from executives, corporate AI adoption is often quieter and more incremental than transformative. Companies are primarily using AI to automate existing workflows, summarize content, and support customer service rather than reinventing entire operations. While interest in autonomous “agentic” AI is growing, most organizations remain cautious, keeping humans in the loop due to concerns over reliability and trust. Leaders remain optimistic about AI’s long-term value, focusing on efficiency gains and future competitiveness rather than immediate financial returns.
Key Takeaways
- Most AI gains are incremental: Companies are seeing steady improvements in productivity without dramatic operational overhauls.
- Trust limits autonomy: Concerns about errors and hallucinations are preventing widespread deployment of fully autonomous AI agents.
- Leadership drives success: Organizations where top executives actively champion AI tend to see deeper and more effective adoption.
(Source: Wall Street Journal)
Inside Satya Nadella’s Plan to Reinvent Microsoft for the AI Era
Microsoft CEO Satya Nadella has launched a sweeping overhaul of the company’s senior leadership as he pushes to strengthen Microsoft’s artificial intelligence strategy beyond its once-exclusive partnership with OpenAI. Facing intensifying competition from rivals such as Alphabet and Amazon, Nadella has made high-profile external hires, reshuffled internal responsibilities, and adopted a more hands-on, “founder mode” leadership style to accelerate innovation. These changes aim to speed the development of Microsoft’s own AI models, coding tools, and applications while cutting internal bureaucracy. The move follows a restructuring of Microsoft’s relationship with OpenAI that will gradually reduce Microsoft’s privileged access to its partner’s models, forcing the company to build a more independent AI future.
Key Takeaways
- Leadership shake-up to boost speed: Nadella has restructured Microsoft’s senior leadership to reduce bureaucracy and accelerate decision-making around AI development.
- Preparing for life beyond OpenAI: With exclusive access to OpenAI’s models set to fade over time, Microsoft is investing heavily in building its own AI models and internal capabilities.
- Competition driving urgency: Increased pressure from rivals and AI start-ups is forcing Microsoft to move faster and rethink how it executes its AI strategy.
(Source: Financial Times)
No Slowdown Ahead: Why AI’s Momentum Will Carry Into 2026
The rapid expansion of artificial intelligence shows no signs of slowing as 2026 approaches, according to a Dalhousie University computer science professor. AI has become deeply integrated into everyday life, powering tools such as weather forecasting, medical diagnostics, and decision-support systems while dramatically reducing computational costs. However, the growing sophistication of AI also brings risks, including more advanced phishing attacks and potential psychological effects on users. Experts say stronger regulation and widespread education will be essential as AI becomes more personalized and embedded across society.
Key Takeaways
- AI adoption will continue accelerating: Experts expect AI tools to become more powerful, specialized, and widely used throughout 2026.
- Benefits are tangible and growing: AI is already delivering measurable improvements in efficiency, accuracy, and cost reduction across multiple industries.
- Risks must be addressed: Increased use of AI raises concerns around cybersecurity, mental health, and misinformation that require regulation and education.
(Source: BNN Bloomberg)
Meta’s AI Buying Spree Continues With Manus Acquisition
Meta Platforms has acquired Manus, a Singapore-based developer of general-purpose AI agents, as part of its aggressive push to expand automation across consumer and enterprise products. Manus experienced rapid growth after launching its AI agent earlier this year, claiming more than $100 million in annualized revenue within eight months. Meta plans to integrate Manus’s technology into products such as its Meta AI assistant while allowing the company to continue operating independently. The deal highlights Meta’s broader strategy of acquiring AI start-ups to secure talent and technology amid intensifying competition.
Key Takeaways
- Meta is betting big on AI agents: The acquisition strengthens Meta’s push to automate complex tasks across its consumer and business products.
- Manus scaled at extraordinary speed: The start-up’s rapid revenue growth underscores strong demand for AI agent technology.
- Talent acquisition remains critical: Meta continues to use acquisitions to secure AI expertise and stay competitive in the AI arms race.
(Source: CNBC)
Inside Nvidia’s $20 Billion Groq Deal — And Who Gets Paid
A complex $20 billion agreement between Nvidia and AI chip start-up Groq is delivering substantial payouts to employees and investors without a traditional acquisition or equity transfer. Under the non-exclusive licensing deal, most Groq employees are expected to join Nvidia with a mix of cash payouts and stock, while Groq continues operating independently. The structure reflects a growing trend in AI dealmaking designed to secure talent and technology while minimizing antitrust risk, highlighting the enormous financial stakes surrounding AI hardware innovation.
Key Takeaways
- A non-traditional deal structure: Nvidia avoided a full acquisition while still valuing Groq at $20 billion through a licensing agreement.
- Employees and investors benefit significantly: Most Groq shareholders and staff are receiving major cash and stock payouts, often with accelerated vesting.
- Antitrust pressure is shaping AI deals: Big Tech companies are increasingly using creative deal structures to avoid regulatory scrutiny.
(Source: Axios)
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