For Bigger Players ( Enterprise, Consultancy)

If you're at an enterprise level or a consultancy advising Fortune 500s, the I/O 2025 announcements are a clarion call to bake AI into your strategy, across the board. Enterprises move slower than startups, but Google just made it clear that AI isn't a sideshow – it's the main stage. Here's what to consider:

Customer Experience Reimagined

Enterprises need to anticipate that customers will interact with their brand through these new AI interfaces. For example, a bank might see users asking AI Mode "What's the best savings account for a college grad?" instead of visiting the bank's site. If the AI is comparing products and citing sources, enterprise content teams should ensure product info is clear, comprehensive, and up to date to be favoured in those answers. This might mean tighter collaboration between product, marketing, and IT to expose data (like interest rates, features) in an AI-readable format (APIs or structured data).

Internal AI Deployment

Many large orgs are building internal AI tools. Google's announcements provide ready-made building blocks. Google AI Studio and the Gen AI SDK let developers quickly embed Gemini's abilities into apps. An enterprise consultancy should be telling its clients: don't reinvent the wheel, leverage Google's models via API for your use cases. Whether it's an internal chatbot that knows your company's knowledge base or an AI to automate support tickets, Gemini 2.5 could likely power it.

The ML Kit GenAI (Gemini Nano) is gold– on-device AI for things like summarization or translation on mobile. This could be huge for enterprise mobile apps that need AI features without constant cloud calls (think: privacy and speed).

Data and Privacy Considerations

Enterprises are (rightly) cautious about privacy. The idea of connecting personal Gmail to search results is nifty for consumers, but for enterprises, data governance is vital. Consultancies should guide clients on how to allow AI to enhance their services while protecting sensitive info. For example, if you're a healthcare provider with a patient app, you might use Gemini in a way that it doesn't expose personal health info, or you opt for on-premise model deployment. Google Cloud might eventually offer fine-tuned Gemini models in a private environment (worth watching out for).

Upskill and Innovate Culture

I/O showed that AI can write code, fix code (Gemini in Chrome DevTools can debug for you), generate creatives, etc. Enterprises should see this as an opportunity to upskill their workforce rather than fear job displacement. The smart move is training employees to use these AI tools to be more productive. I've already heard of consulting firms planning "AI training days" – teaching consultants how to use these tools to analyze data faster or write reports with AI assistance.

Enterprise Search & Knowledge

Google's own products (like its NotebookLM, which got folded into the Gemini app) allow uploading your own docs for AI analysis. Enterprises can use this concept for their knowledge management. Imagine an internal "deep search" that an employee can ask, "Summarize our Q3 performance and pull any key risks mentioned in audit reports." AI can do that if fed the data. So start building those internal corpuses and use Google's frameworks to enable deep search on your data.

From a consultant's POV, you should help big clients identify where AI can add value quick and pilot it. Those who snooze will lose – to competitors who create more seamless, AI-powered customer experiences or who drastically cut costs by automating rote tasks. But also, counsel them on doing it responsibly. Bias, compliance, and security are still concerns with AI. Google's making strides (they talked about model safety too, albeit briefly), but enterprises must tread carefully.

Bottom line: The mantra for enterprises should be "AI everywhere, but with oversight." Google just showed the canvas; it's up to each big company to paint their AI strategy on it. 

My advice: start yesterday. Even our enterprise clients in traditionally conservative sectors (looking at you, finance) are now realizing that not adopting AI is riskier than adopting it. As a strategist, I love this challenge – it's the dawn of a new business process revolution, and we get to architect it.