Gemini Enterprise Agent Platform title card with Build, Scale, Govern and Optimize labels on a black background — Google's title card for Gemini Enterprise Agent Platform, launched on April 23, 2026. Image: Google Cloud.

Two of India's largest IT services firms made the same bet this week. Tech Mahindra and LTM both announced bigger pushes into Gemini Enterprise. It is Google Cloud's platform for building and running AI agents at work.

Tech Mahindra is training more than 12,500 people on it. LTM, the company formerly known as LTIMindtree, is building a dedicated centre of excellence around it. When firms this size move together, clients start asking their smaller vendors the same questions.

I'm Nitin from Debugged Pro. I coordinate software and AI projects for clients in India and the USA. Here is what was announced, what the platform actually does, and how I would plan for it as a mid-sized agency.

What Tech Mahindra and LTM Announced

The two news items landed a day apart. Both are framed around the same problem: companies are stuck in AI pilots and want help reaching production.

October 6, 2026: Tech Mahindra said it is expanding its agentic AI readiness with Google Cloud.
October 7, 2026: LTM announced an expanded collaboration to help speed up Gemini Enterprise adoption at scale.

Neither release shares revenue targets or client names. They are about people, delivery capacity and packaged solutions. That tells you where the competition is heading.

Tech Mahindra's Build with Gemini Rollout

According to Tech Mahindra's press release on its Gemini Enterprise expansion, the core of the plan is a Google Cloud workshop called Build with Gemini. Tech Mahindra is rolling it out to more than 12,500 associates worldwide.

The workshop teaches staff to create, secure and govern AI agents. It covers three named Google tools: Agent Runtime, Agent Gateway and Model Armor. People who finish it earn a Google Cloud Skill Badge.

The company also pointed to industry solutions it already sells through Google Cloud Marketplace. It listed telecom, financial services, manufacturing and retail as sectors where it has built agentic AI work.

Pramod Panda, Tech Mahindra's Chief Learning Officer, said: "Enterprise AI will scale only when organizations can combine technology innovation with the talent and delivery capability required to put it into production."

Kelly Rogan, who leads Global System Integrators Partnerships at Google Cloud, added that enterprises are moving quickly from AI experiments to deployment, where domain knowledge and engineering skill matter most.

Abstract glowing pink and orange glass shapes on a dark background used as Tech Mahindra's Gemini Enterprise banner — Banner from Tech Mahindra's October 6, 2026 announcement on scaling Gemini Enterprise readiness. Image: Tech Mahindra.

LTM's Gemini Enterprise Centre of Excellence

LTM's plan is more structural. LTM's announcement, carried by The Tribune via Business Wire India, lists three pillars:

A Gemini Enterprise Center of Excellence: a dedicated group of AI, cloud and industry specialists for large deployments.
Specialized talent and delivery: Forward Deployed Engineers, Gemini model specialists, and training and certification programs.
Industry solutions: AI products for BFSI, manufacturing, retail and CPG, media and entertainment, and energy and utilities.

Those solutions will be shown at an upcoming Gemini Enterprise Customer Experience Center. LTM did not give an opening date.

Krishnan Iyer, LTM's Chief Growth Officer, said: "Enterprises are looking to move beyond AI experimentation and scale adoption with clear business outcomes."

LTM says it has more than 87,000 employees in 40 countries. Even a small share of that headcount trained on one platform is a big number.

What Gemini Enterprise Actually Includes

The name gets used loosely, so it helps to be precise. Gemini Enterprise is the employee-facing app where staff use agents. The build side is Gemini Enterprise Agent Platform, which Google launched on April 23, 2026.

In Google Cloud's launch post for Gemini Enterprise Agent Platform, the company called it the evolution of Vertex AI. Google also said all Vertex AI services and roadmap updates will now come through Agent Platform rather than as a standalone service.

That matters if you have clients on Vertex AI today. Their roadmap now runs through this platform whether they planned for it or not.

Here are the parts that come up most in client work:

Component	What it does	Why it matters on a project
Model Garden	Access to more than 200 models, including Gemini, Gemma and Anthropic's Claude models	You are not locked into one model family
Agent Studio and ADK	Low-code builder plus a code-first Agent Development Kit	Business users can prototype, developers can take over
Agent Runtime	Runs agents, including long-running ones that keep state for days	Fits multi-step work like sales follow-ups
Memory Bank	Stores long-term context from past conversations	Agents remember user preferences between sessions
Agent Identity and Registry	Gives each agent a unique ID and keeps a list of approved agents and tools	Every action can be traced back to an agent and a policy
Agent Gateway and Model Armor	One control point for agent traffic, with protection against prompt injection and data leaks	This is what security teams ask about first
Simulation, Evaluation, Observability	Test agents before launch and trace their reasoning after	Gives you proof that an agent works before go-live

Notice which tools Tech Mahindra chose for its workshop. Runtime, Gateway and Model Armor are about running agents safely, not about building flashy demos. That choice says a lot about what enterprise buyers are paying for.

Gemini Enterprise Agent Platform architecture diagram showing Build, Scale, Govern and Optimize layers and their components — Google's overview of Agent Platform layers, from Agent Development Kit to Agent Gateway and Agent Evaluation. Image: Google Cloud.

Why Gemini Enterprise Skills Matter for Agencies

Large IT firms are not training thousands of people for fun. They do it because clients are asking for certified teams on specific platforms. Once the big vendors have that, smaller vendors get compared against it.

We are seeing the same pattern across every major AI platform in recent weeks. Microsoft added a Frontier specialization for partners. We covered it in our post on the Microsoft partner program and AI agent badges. Anthropic ties partner status to certified people and production customers. Our guide explains the Claude Partner Network tiers.

Google's version of this story is now playing out through its biggest systems integrators. Three things stand out to me:

Governance is the selling point. Both releases stress security, governance and moving from pilots to production.
Forward Deployed Engineers are becoming standard. LTM is the latest firm to add them to its delivery model.
Packaged solutions win attention. Tech Mahindra offers industry solutions through Google Cloud Marketplace, not just hours.

What It Means in India

For Indian agencies, the hiring market will feel this first. Engineers with hands-on Gemini Enterprise experience will get offers from large firms. Plan for that before you invest in training.

There is also an opening. Big firms focus on large accounts. Mid-sized Indian companies in manufacturing, retail and finance still need help, and they often prefer a smaller team that answers the phone.

What It Means in the USA

US clients usually buy on proof. Many will ask which cloud your team knows and what you have shipped on it. If a client already runs Google Workspace or Google Cloud, Gemini Enterprise will likely be on their shortlist.

The safer pitch is narrow and honest. Show one agent you built, how you governed it, and what it changed for the client.

A 6-Step Plan to Get Your Team Ready for Gemini Enterprise

If I were planning this for a 20 to 50 person agency, I would go in this order.

Check your client base first. List which clients use Google Cloud or Google Workspace. If it is under a quarter, do not lead with Google.
Train a small core group. Start with three to five senior developers. Have them earn a Google Cloud Skill Badge before you scale training.
Build one internal agent. Pick a real task, like ticket triage or proposal drafting. Run it through Agent Gateway and Model Armor so you learn the security setup.
Write a governance checklist. Cover agent identity, tool access, logging and cost limits. Clients' security teams will ask for this.
Turn one client pilot into production. Choose a client with a clear owner and a measurable goal. Use evaluation tools to prove it works before launch.
Package what you learned. Turn the work into a fixed-scope offer for one industry you know well.

Mistakes to Avoid

Chasing badges on every cloud at once. Pick the platform your clients already pay for and go deep.
Training only juniors. Architects shape the governance design, so they need the training first.
Skipping cost controls. Long-running agents can run for days. Set budget alerts from day one.
Treating a demo as delivery. A working prototype is not the same as an agent with logging, access rules and an owner.

The Honest Caveats

These are press releases, so read them with care. Neither company shared client results, deployment counts or revenue linked to Gemini Enterprise.

A skill badge from a workshop is also not the same as years of production experience. And LTM's Customer Experience Center is still listed as upcoming.

Platform risk is real too. Google has already folded Vertex AI into Agent Platform. Products in this space get renamed and merged often. Build skills that transfer, like agent testing and access control.

Not sure whether Google, Microsoft or Anthropic fits your clients best? Our software development consulting team can review your AI roadmap and delivery setup.

Key Takeaways

Tech Mahindra is training more than 12,500 associates on Gemini Enterprise through Google's Build with Gemini workshop.
LTM is building a Gemini Enterprise Center of Excellence with Forward Deployed Engineers and industry solutions.
Gemini Enterprise Agent Platform replaces Vertex AI as Google's home for building and governing agents.
Governance tools like Agent Gateway and Model Armor are now central to enterprise AI sales.
Smaller agencies should train a core team, ship one governed agent and package it for one industry.

About the Author

Nitin Kumar is the Lead Project Coordinator at Debugged Pro. He works with development teams and clients in India and the USA to plan software and AI projects, set delivery processes and keep quality high. He writes about practical AI adoption for agencies and growing businesses.