Your competitors are already automating. Here's the data.
Retail and ecommerce teams using AI for customer service are resolving 40-60% more tickets without more staff, cutting cost-per-ticket by 30%+, and handling seasonal spikes 3x faster.
But here's what separates winners from everyone else: they started with the data, not the hype.
Gladly handles the predictable volume, FAQs, routing, returns, order status, while your team focuses on customers who need a human touch. The result? Better experiences. Lower costs. Real competitive advantage. Ready to see what's possible for your business?
Meta Closes 2025 with $2B+ Manus Acquisition: The AI Wars Enter a New Phase
Meta wrapped up 2025's acquisition season with a bang, acquiring AI agent startup Manus for over $2 billion—a deal that signals a decisive pivot in how Big Tech is approaching artificial intelligence.
Unlike the model-building arms race that defined recent years, the Manus acquisition represents something different: a bet on practical automation that actually completes tasks. Manus specializes in AI agents capable of end-to-end workflows, technology that could soon power seamless automation across Meta's ecosystem of Facebook, Instagram, and WhatsApp.
This move suggests Mark Zuckerberg is trading hype for utility. While competitors have focused on building ever-larger language models, Meta appears to be doubling down on AI that drives real business outcomes—agents that can handle customer service inquiries, process orders, or manage social media campaigns without human intervention.
The timing is telling. As AI skepticism grows around flashy demos that underwhelm in production, Meta's strategy reflects a broader industry maturation. The question is no longer just "how smart is your model?" but "what can it actually do?"
For Meta, integrating Manus could transform its platforms into genuine business automation hubs, potentially unlocking new revenue streams while deepening user engagement. For the AI industry, it's a signal that 2026 may belong not to the companies with the most impressive benchmarks, but to those building AI that works—reliably, repeatedly, and profitably.
The race isn't over. It's just entered a more pragmatic phase.

