The NVIDIA Enterprise Ecosystem: Are Indian SIs Missing the AI Gold Rush?

-Hey High Stakers,-

Good morning and welcome to the 2nd issue of High Stakes!

NVIDIA’s building a Microsoft-like AI ecosystem—and Indian system integrators risk getting left behind.

Here’s why they're at risk and what they must do differently—fast.

 Read on as I cover 6 aspects in this piece. 

1. The 'Can't Miss' Opportunity for Indian SIs with NVIDIA

2. NVIDIA's Shift: From Hardware to Ecosystem and Software

3. Why Indian SIs are Falling Behind in this Race

4. But Does NVIDIA Really Need Indian SIs?

5. How Indian SIs Can Turn This Around

6. Final Take: Key Questions for Enterprise Tech Leaders & Analysts

-The opportunity Indian SIs can’t afford to miss-

Indian IT services firms want to win in enterprise AI. They have the scale, the client relationships, and the execution muscle. But there's a gaping hole in their AI strategy: NVIDIA. Or so it would seem. 

Look at the partnerships shaping AI today—Accenture, Deloitte, and Microsoft are all deeply embedded in NVIDIA's ecosystem. Yet, Indian SIs—despite their global presence—are not near the main stage.

The reason? They're thinking like service vendors, not ecosystem players. 

-NVIDIA is shifting from Hardware Ecosystem-

NVIDIA is no longer just a GPU company. 

It's transforming into a full-stack AI ecosystem provider, moving from 88% hardware revenue in 2024 to only 60% by 2030.

This shift is already rewarding those who play the ecosystem game:

• Accenture & Deloitte: Expected to generate $1-1.2B in NVIDIA-related revenue by 2025.

• Indian SIs: Projected at just $0.5-0.8B—leaving billions on the table.

• AI Stack Adoption: Only 6% of Indian SI AI projects use CUDA beyond basic inferencing.

-Why Indian SIs are losing this battle-

🚨 1. They Treat NVIDIA Like a Vendor, Not a Partner 

Old playbook: Wait for technology to mature, then resell and implement. 

New playbook: Partnership depth determines access, pricing, and co-selling opportunities.

🚨 2. They Are Stuck in Implementation Mode 

Global SIs are embedding NVIDIA across AI factories, Omniverse digital twins, and industry solutions. 

Indian SIs are just reselling GPUs if that.

🚨 3. They Are Handing Profits to Hyperscalers 

By routing NVIDIA deployments through AWS/Azure, Indian SIs give up 30% of margins instead of building direct NVIDIA capabilities. 

-But does NVIDIA need System Integrators? Indian SIs, in particular?-

It seems clear that SIs need NVIDIA, but what about the other way around? 

The evidence suggests NVIDIA absolutely needs strong SI partnerships to scale its ecosystem beyond hardware.

Reason #1: 

NVIDIA's transformation from 88% hardware revenue to a projected 60% by 2030 hinges on ecosystem depth. System Integrators, with their client relationships and implementation expertise, are critical force multipliers for NVIDIA's full-stack adoption.

In India specifically, press mentions show NVIDIA has aggressively courted partnerships with Reliance, TCS, Infosys, Tech Mahindra, and others since October 2024. 

Jensen Huang himself declared that "India will be a country that exports AI," signaling the strategic importance of Indian SIs in NVIDIA's global expansion.

Reason #2: 

NVIDIA's commitment goes far deeper than partnerships. Since establishing operations in India in 2004, the company has built design centers across multiple cities that now serve as crucial R&D hubs. 

These centers don't just service clients—they're integral to NVIDIA's global innovation pipeline.

Reason #3: 

The company's Deep Learning Institute has upskilled more than 200,000 Indian developers, creating a talent ecosystem that both SIs and NVIDIA leverage. 

At the 2024 Mumbai AI Summit, Huang even discussed "going full steam ahead for fab ambitions in India," aligning with India's Semiconductor Mission and signaling potential manufacturing investments.

Reason #4: 

NVIDIA's India units are slated for "20 times more computing power" year-over-year, a dramatic scaling that demonstrates the company views India as strategic to its global growth, not just as a service delivery location.

Reason #5: 

The company has also restructured its channel leadership to better manage growing relationships with global and regional integrators, a clear vote of confidence in the SI model and recognition that NVIDIA's ecosystem play requires strong implementation partners to succeed.

-Three winner Examples to follow-

🏆 Winner #1. “Co-Develop, Don't Just Implement”

Example: Accenture has 30,000+ NVIDIA-certified architects. 

Winning Play: Stop selling "NVIDIA implementation. Build co-branded AI solutions for specific industries instead.

Ideas for SIs: 

1. How about building 3-5 industry-specific AI solutions (think healthcare diagnostics or supply chain twins) with NVIDIA's engineering teams, not for them? Charge premium pricing for IP, not hours.

2. Closer home to the Indian SIs, see what Zoho and NVIDIA are doing building custom LLMs for specific business applications. How about delivering solutions with deep contextual understanding that generic implementations can't match?

🏆 Winner #2. “Own the Full Stack”

Example: HPE's Private Cloud AI integrates the complete NVIDIA stack. 

Winning Play: Bundle DGX Cloud + CUDA optimization + Omniverse digital twins into one offering. [Note: DGX Cloud provides dedicated clusters of NVIDIA DGX AI supercomputing systems paired with the NVIDIA AI Enterprise software suite, accessible via a simple web browser.]

Ideas for SIs: 

1. Considering slapping DGX Cloud into a proposal? Weak. But package it with CUDA optimization + Omniverse integration along with a bonus offer of "AI ROI Insurance" (e.g., guaranteed 20% efficiency gain or free re-engineering)? 

2. Follow the good old IBM Consulting's approach of combining their industry expertise with NVIDIA's full technology stack? They're integrating "NVIDIA AI Enterprise software, NVIDIA NIM microservices, and NVIDIA Omniverse" to streamline AI workflows and develop business-specific AI use cases. 

🏆 Winner #3. “Monetize AI IP, Not Just Services Winners”

Example: Deloitte charges 20-30% premiums on NVIDIA-embedded solutions. 

Winning Play: Create recurring revenue streams via NVIDIA's NGC marketplace. [Note: NGC stands for NVIDIA GPU Cloud. It is a cloud-based platform that serves as a hub for GPU-optimized software for deep learning, machine learning, and high-performance computing (HPC). It is essentially a comprehensive catalog of pre-configured containers, pre-trained models, model scripts, and industry solutions that allow data scientists, developers, and researchers to focus on building solutions and gathering insights faster]

Ideas for SIs: 

1. Why not package proprietary AI models and workflows as subscription products on NVIDIA's NGC marketplace instead of just selling implementation hours?

2. How about creating industry-specific containerized solutions with tiered pricing (free basic versions, premium paid features) to generate recurring revenue?

3. OR even consider monetizing your IP through NGC's distribution network (250K+ users, 1M+ downloads) while bundling implementation services at premium rates?

Podcast for the road: "Acquired" episode on NVIDIA’s ecosystem pivot—listen while redesigning your GTM-

-Final Take: Key Questions for Enterprise Tech Leaders & Analysts-

If you're buying AI solutions:

Demand partners who:

• Show CUDA muscles: 94% of Indian SI projects use NVIDIA just for inferencing. Your vendor better prove they're using CUDA-X libraries for training optimizations—ask for benchmark comparisons.

• Bring their own IP: Deloitte's 20-30% premiums aren't for services—they're for proprietary AI models on the NGC marketplace. No IP ownership? Walk away.

• Have skin in the game: If they're not offering shared-risk contracts tied to business outcomes (revenue lift, cost reduction), they're just GPU tourists.

If you're shaping opinions (analysts, VCs, media):

Double down on two narratives:

• "Ecosystem depth = valuation multiplier": Track how SI partnerships with NVIDIA correlate with stock performance (spoiler: Accenture's up 18% YTD vs. Indian peers at 4%)

• Call out legacy behavior: Call out SIs still using "NVIDIA implementation services" in their marketing—it's 2025's version of "we do cloud migration."

Bookmark this:

-The Bottom Line-

NVIDIA's ecosystem isn't a partner program—it's a loyalty test. Tech sellers either build moats through co-development, buyers ruthlessly filter for IP depth, or everyone loses to the Accentures of the world. Time to pick a lane.

-Final Thought: The Window is closing-

Indian SIs are world-class at delivery, but they need to rethink their NVIDIA strategy—fast. The players who co-develop, own the stack, and monetize IP will dominate. Those who don't?

They'll be stuck in low-margin implementation work, watching others take the AI gold.

Best,
Srini

P.S. If this sparked ideas about your NVIDIA partnership strategy, share it with your team. The insights could reshape your 2025 AI investment roadmap.