Because boards lack deep expertise in AI's seismic impact, they are pursuing scale-driven M&A. The goal is to accumulate diverse assets ('cards in a deck') to maintain flexibility and strategic options in an unpredictable, AI-driven future, rather than making specific bets on the technology itself.

Major AI model labs will acquire leading agent labs not just for talent, but for their superior user interfaces. For the agent labs, selling is a strategic move to avoid being eventually out-competed by the very model providers they rely on, making these M&A deals mutually beneficial.

Top AI labs like Anthropic are simultaneously taking massive investments from direct competitors like Microsoft, NVIDIA, Google, and Amazon. This creates a confusing web of reciprocal deals for capital and cloud compute, blurring traditional competitive lines and creating complex interdependencies.

Meta is likely acquiring Manus to pair its AI agent technology with its open-source models for on-premise enterprise deployments. This signals a strategic expansion into enterprise tooling, moving beyond its core social media business and leveraging its existing open-source leadership.

Initially, even OpenAI believed a single, ultimate 'model to rule them all' would emerge. This thinking has completely changed to favor a proliferation of specialized models, creating a healthier, less winner-take-all ecosystem where different models serve different needs.

Meta is publicly framing its acquisition of the AI agent startup Manus as an enterprise play. However, the underlying strategy is likely to leverage Manus's talent to build a dominant consumer AI agent for tasks like travel and shopping, creating a new, defensible platform.

Despite being key backers of OpenAI, Microsoft and NVIDIA are investing heavily in its competitor, Anthropic. This signals a strategic shift by tech giants to diversify their AI investments, ensuring no single lab becomes dominant and fostering a more competitive ecosystem.

Microsoft's early OpenAI investment was a calculated, risk-adjusted decision. They saw that generalizable AI platforms were a 'must happen' future and asked, 'Can we remain a top cloud provider without it?' The clear 'no' made the investment a defensive necessity, not just an offensive gamble.

Major AI labs like OpenAI and Anthropic are partnering with competing cloud and chip providers (Amazon, Google, Microsoft). This creates a complex web of alliances where rivals become partners, spreading risk and ensuring access to the best available technology, regardless of primary corporate allegiances.