Meta acquires Manus to accelerate AI task automation strategy

Ethan Cole
Ethan Cole I’m Ethan Cole, a digital journalist based in New York. I write about how technology shapes culture and everyday life — from AI and machine learning to cloud services, cybersecurity, hardware, mobile apps, software, and Web3. I’ve been working in tech media for over 7 years, covering everything from big industry news to indie app launches. I enjoy making complex topics easy to understand and showing how new tools actually matter in the real world. Outside of work, I’m a big fan of gaming, coffee, and sci-fi books. You’ll often find me testing a new mobile app, playing the latest indie game, or exploring AI tools for creativity.
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Meta acquires Manus to accelerate AI task automation strategy

Meta acquires Manus in one of the most high-profile AI deals of the year, signaling a deeper push into autonomous task automation. The acquisition brings a fast-growing AI agent platform into Meta’s ecosystem at a moment when competition around applied AI is intensifying.

Rather than focusing on another research lab or foundation model, Meta is buying execution. Manus built its reputation on agents that actually perform work, not just generate text.

Meta acquires Manus in a landmark AI deal

Meta’s acquisition of Manus is reportedly valued at more than $2 billion, making it one of the largest exits tied to Asia’s AI startup ecosystem. The deal highlights Meta’s growing appetite for applied AI platforms that already show traction with real users and revenue.

Manus emerged publicly in early 2025, positioning itself as a general AI agent capable of completing complex tasks autonomously. Unlike traditional chatbots, the product focused on outcomes rather than suggestions.

Why Meta acquires Manus for AI agents

Manus was designed to automate concrete workflows. These include market research, coding tasks, sales data analysis, and rapid website creation. Instead of relying on a single proprietary model, the platform orchestrates several third-party large language models.

In practice, this model-agnostic approach allowed Manus to move quickly. It could adopt stronger models as they appeared while focusing its own development on orchestration and task execution.

As a result, Manus gained attention for doing real work rather than acting as a productivity assistant.

Manus growth that convinced Meta

According to the company, Manus reached millions of users within months of launch. It also reported annualized revenue exceeding $100 million less than a year after entering the market.

That level of traction made Manus unusual among AI startups. Many tools gain visibility without monetization. Manus, however, combined viral growth with clear enterprise and business use cases.

This momentum likely played a key role in Meta’s decision to move quickly.

Strategic timing for Meta

Meta acquires Manus at a moment when the company is redefining how AI fits into its broader product strategy. While Meta continues to invest heavily in foundation models, it has also emphasized agents, assistants, and applied AI experiences.

Manus gives Meta a shortcut into this space. Instead of building a similar platform internally, Meta gains a mature system with proven demand and an experienced team.

At the same time, the acquisition reduces Meta’s reliance on purely experimental AI products.

Global expansion and organizational shift

Before the acquisition, Manus underwent significant internal changes. The company laid off much of its Beijing workforce and relocated its headquarters to Singapore. This move reflected ambitions to expand globally and operate outside a single regional ecosystem.

When Meta approached Manus, the startup was reportedly seeking new funding at a $2 billion valuation. The acquisition offered both scale and stability.

Manus leadership stated that joining Meta would not fundamentally change how the product operates or how decisions are made.

Why AI agents matter now

The deal underscores a broader shift in AI adoption. Enterprises increasingly care less about raw model performance and more about task completion.

AI agents that can research, analyze, build, and deploy autonomously are becoming more valuable than general chat interfaces. Meta acquires Manus precisely because it fits this direction.

Instead of asking users what to do next, these systems act.

Competitive pressure across the AI landscape

Meta’s move also reflects growing competition among major tech companies. Autonomous agents are emerging as a new battleground, alongside foundation models and AI infrastructure.

By acquiring Manus, Meta strengthens its position against rivals investing heavily in applied AI workflows. It also signals that execution-focused startups are now prime acquisition targets.

This trend may accelerate consolidation across the AI startup ecosystem.

Final thoughts

Meta acquires Manus not just to expand its AI portfolio, but to anchor its strategy around agents that deliver measurable outcomes. The acquisition blends fast-moving startup execution with Meta’s scale and resources.

As AI shifts from experimentation to automation, deals like this may define the next phase of the industry.

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