Google's New Enterprise Play, Reflection's $2B Bet, and Why Your AI Can Learn to Kill

Google just threw down the gauntlet in the enterprise AI race, and it's not subtle about it. While Amazon reboots its workplace chatbot and a $2 billion startup promises to save American AI from Chinese dominance, the real story is about control. Who owns the front door to AI in your organization, and what happens when that door has a few cracks in it?

Today we're digging into Google's full-court press with Gemini Enterprise, why it matters that ex-DeepMind researchers just raised more money than most countries' GDP, and the uncomfortable truth about AI security that Eric Schmidt wants you to hear.

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Google's Gemini Enterprise: The Platform Play You Need to Understand

Google just unveiled Gemini Enterprise, and calling it a chatbot would be like calling a Porsche a golf cart. This is Google's bid to become the operating system for enterprise AI, a comprehensive platform that integrates your company's data, tools, and workflows into one conversational interface powered by their most advanced Gemini models.

The pitch is simple but ambitious: every employee, every workflow, one AI-powered front door. It’s almost as if it’s Google's answer to the chaos of shadow AI, where your teams are currently juggling ChatGPT tabs, Copilot windows, and whatever Claude subscription they're hiding from IT.

Here's where it gets practical. Gemini Enterprise is also a no-code workbench where any employee can build custom AI agents to automate their specific workflows. Picture a marketing manager spinning up an agent that generates campaign concepts, pulls approved brand assets, and produces social media copy and visual mockups in minutes instead of days. The agent has secure access to company data, so it understands product details and brand guidelines without manual input.

Four capabilities that separate this from the pack:

1. Custom agent building: Google ships pre-built agents (Deep Research and Data Science) plus an agent marketplace where you can deploy thousands of vetted third-party solutions. Any employee, from marketing to finance, can build specialized agents without writing code.

2. Cross-system context: Connects to Google Workspace and Microsoft 365, plus Salesforce and SAP. It's not just searching these systems; it's building context across them. Banco BV is automating hours of work for relationship managers by pulling context from internal analytics. Harvey is using it for legal AI that makes contract analysis dramatically faster.

3. Full workflow orchestration: Google is both automating tasks and orchestrating entire processes across multiple systems. Macquarie Bank improved self-service capabilities (38% more users finding answers on their own) and reduced false positive alerts for client protection by 40%. That's process transformation, not incremental improvement.

4. Multi-modal integration: If you're in the Google Workspace ecosystem, Gemini Enterprise works where your teams live. Google Vids transforms presentations into videos with AI-generated scripts and voiceovers. Google Meet offers real-time speech translation that captures tone and expression across languages. This isn't theoretical; it's shipping now.

The security angle matters too. Unlike consumer chatbots, Gemini Enterprise is grounded in your company's information with your personal work context. It can chat with your documents, data, and applications while maintaining the security posture you'd expect from an enterprise cloud provider. This is the "ChatGPT is great, but you can't use it at work" problem that every CISO is grappling with right now.

What this means for your procurement strategy: Gemini Enterprise isn't just competing with Microsoft's Copilot or Amazon's Quick Suite (more on that later). It's competing with the entire patchwork of AI tools your teams have already adopted. Google is betting that consolidation around a single, deeply integrated platform beats the franken-stack approach most enterprises are accidentally building. The agent marketplace is the tell here: they're building an ecosystem, not just a product.

Here's what to watch. Google Cloud just crossed $50 billion in annual revenue with 13 product lines each generating over $1 billion, and 65% of their customers are already using AI products. They're also hosting nine of the top ten AI labs and nearly all AI unicorns. That's vendor lock-in disguised as innovation partnership.

The question your executive team needs to answer: is one platform better than best-of-breed tools for different functions? Google is betting yes. They're positioning Gemini Enterprise as the entry point to their entire AI stack, from infrastructure to research breakthroughs to products used by billions. It's a walled garden, but it's a very nice garden with Nobel Prize winners maintaining it.

The timing is deliberate. This announcement comes as enterprises are moving from AI experimentation to actual deployment at scale. The companies that figure out their AI platform strategy now will have a serious advantage over those still running pilot projects in 2026.

AI Headlines

1. Reflection Raises $2B to Challenge DeepSeek and Build "America's Open Frontier AI Lab"

   Two ex-Google DeepMind researchers (the team behind AlphaGo) just raised $2 billion at an $8 billion valuation, jumping 15x from their valuation seven months ago. Reflection is positioning itself as both an open-source alternative to closed labs like OpenAI and a Western response to Chinese AI firms like DeepSeek.
   Read more →

2. Amazon Reboots Workplace AI with Quick Suite, Competing at $20/Month

   Amazon Web Services just launched Quick Suite, its revamped AI agent platform for enterprise workers, effectively sunsetting Q Business after just 18 months. At $20 per user per month, it's pricing aggressively against Microsoft's $30 Copilot and Google's $30 Gemini Enterprise. Quick Suite can analyze sales data, produce reports, summarize web content, and integrate with Slack, Salesforce, Microsoft file storage, and Adobe tools. It's housed in a web app with a browser plugin that follows users around the internet.
   Read more →

3. Eric Schmidt Warns AI Models Can Be Hacked: "They Learn How to Kill Someone"

   Google's former CEO delivered a stark reminder at the Sifted Summit: AI models, both closed and open, can be reverse-engineered to remove their guardrails. Schmidt noted that while all major companies prevent their models from answering dangerous questions, there's evidence these safeguards can be bypassed through techniques like prompt injection and jailbreaking.
   Read more →

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TL;DR:

• Google launched Gemini Enterprise, a comprehensive AI platform designed to be the single front door for enterprise AI, integrating all company data, tools, and workflows with advanced Gemini models and processing 1.3 quadrillion monthly tokens.

• Reflection AI raised $2 billion to build America's open frontier lab with ex-DeepMind talent, positioning itself as both an open-source alternative to closed labs and a Western answer to Chinese AI dominance.

• Former Google CEO Eric Schmidt warned that AI models can be hacked to remove safety guardrails despite all major companies implementing protections, highlighting the lack of effective non-proliferation regimes.

• Amazon launched Quick Suite at $20/month (undercutting Microsoft and Google at $30/month) with AI agents for workplace tasks, though AWS faces an uphill battle getting office workers to adopt its brand.

• The enterprise AI platform war is officially on, with cloud giants racing to consolidate the franken-stack of AI tools companies are accidentally building into single, secure, governed platforms.

Stay Sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together