AI in Focus: Platform Power, Agentic AI, and the Chip Wars

Week 6: Dec. 29 – Jan. 2

AI Unpacked

Welcome back to AI Unpacked, your weekly briefing on the biggest developments shaping the AI landscape. As 2025 comes to a close and 2026 begins, AI headlines were dominated by Big Tech power plays, from Apple’s growing reliance on OpenAI, to Meta’s latest acquisition spree, to fresh challenges against Nvidia’s dominance, and Wall Street’s enthusiasm for AI-fueled gains. Here’s what mattered most this week.

OpenAI Deepens Its Reach Inside Apple’s App Store

Apple’s App Store is becoming an increasingly important distribution channel for OpenAI, highlighting how deeply AI is being embedded into consumer software ecosystems. According to the Wall Street Journal, OpenAI-powered features are now influencing how developers design and market apps, as generative AI tools gain prominence across productivity, creativity, and consumer use cases.

While Apple continues to emphasize privacy and on-device processing, the partnership underscores a pragmatic approach of leveraging OpenAI’s advanced models where they add the most value. For OpenAI, tighter integration into Apple’s ecosystem offers exposure to hundreds of millions of users, accelerating adoption at a scale few platforms can match.

The broader implication is that the next phase of AI competition isn’t just about building the best models. It’s about distribution. Companies that control operating systems, app marketplaces, and default user experiences are emerging as critical gatekeepers for AI adoption.

Google Stock Caps Its Best Year Since 2009 on AI Optimism

Alphabet’s stock wrapped up its strongest year since 2009, driven largely by investor confidence in the company’s AI strategy. CNBC reports that Wall Street has been increasingly bullish on Google’s ability to monetize AI across search, cloud, advertising, and productivity tools.

Despite concerns earlier in the year about competition from AI-native challengers, Alphabet has reassured investors with aggressive model development, expanded AI-powered features, and rapid enterprise adoption through Google Cloud. The rally reflects a broader market belief that incumbents with massive data, distribution, and infrastructure advantages are well positioned to benefit from AI rather than be disrupted by it.

For the market, the takeaway is clear. AI is no longer just a speculative theme. It is now a core driver of earnings expectations and long-term valuation for Big Tech.

Meta Acquires Singapore-Based AI Agent Startup

Meta continued its aggressive AI expansion with the acquisition of Manus AI, a Singapore-based startup focused on building autonomous AI agents, according to CNBC. Manus develops agentic AI systems designed to carry out multi-step tasks independently, coordinate actions across software tools, and operate with minimal human supervision. The company has been building agents aimed at enterprise and productivity use cases, rather than consumer chat interfaces alone.

The deal reflects Meta’s growing emphasis on agentic AI as a product layer, not just a research concept. By acquiring Manus, Meta gains a team experienced in deploying task-oriented agents that can execute workflows, make decisions, and interact with other systems. This capability aligns with Meta’s broader strategy to embed AI agents across its ecosystem, including workplace tools, developer platforms, and consumer applications, where automation and task completion matter more than conversational novelty.

More broadly, the acquisition underscores a shift in how large tech companies are scaling AI capabilities. Instead of relying exclusively on internally built foundation models, companies like Meta are increasingly acquiring specialized startups to accelerate time to market in fast-moving areas such as AI agents. As agentic systems move from demos into real-world deployment, strategic M&A is emerging as a critical lever in the next phase of the AI arms race.e.

A New Challenger Takes Aim at Nvidia’s AI Chip Dominance

Nvidia’s grip on the AI hardware market is facing fresh pressure as startups continue to explore alternatives to its GPUs. The Wall Street Journal reports on FuriosaAI, a South Korean chip startup positioning itself as a challenger by focusing on efficient AI inference rather than brute-force training power.

Inference, the process of running trained models in real-world applications, has become a critical battleground as AI moves into production at scale. Furiosa’s approach targets lower power consumption and cost efficiency, appealing to customers looking to deploy AI without relying entirely on Nvidia’s expensive hardware stack.

FuriosaAI's RNGD Chip FuriosaAI

While Nvidia remains the clear leader, the emergence of credible challengers signals a shift in the hardware landscape. The next phase of competition will likely hinge on efficiency, specialization, and deployment economics, not just raw performance.

As the year turns, one theme stands out. AI is no longer confined to research labs or hype cycles. It is reshaping platforms, balance sheets, and competitive dynamics across the tech industry. We’ll be back next week to break down what’s next as AI momentum carries into the new year to break down what’s next as AI momentum carries into the new year.