Companies are changing the architecture for how they compete.
By Sarah Elk and Eric ShengCopyright © 2025 Bain & Company, Inc. All rights reserved.Nvidia GTC 2025: AI Matures into Enterprise Infrastructure
Bain provide their latest input on evolution of AI following the Nvidia GTC Conference. My take is that Bain are ahead of the markets on understanding this evolution. AI is becoming industrialized and the work and products coming from Nvidia provide the next generation of building blocks of this evolution. And the prime mover of that evolution is to develop business value through corporate reconstruction built around AI.
This provides a framework that allows software development to focus on levering the scale of LLM built on the new data centres from Microsoft, Google, and Amazon, notwithstanding the machinations of data centre capacity to establish this new industrial base. Earlier in 2024 Jensen was speaking in these terms throughout 2024:
Jensen Huang envisions 24/7 AI factories: “Just like we generate electricity, we’re now going to be generating AI”
We are in the midst of an Industrial Revolution and we all know the British history of 100 years plus to shift fully from horses through steam, Iron and finally factories and the social changes which followed.
2025 has different levels of patience and desire for immediacy and we must observe the shifts in the 2024/2025 industrial revolution in that context. Business, Process and Technology are evolving at breakneck speed and the components of the shifts are being worked out daily and weekly. But the evolution and business transformation is and will happen, so get past that doubt.
Here is the latest from Bain and the original source.
___________________________________________________
Bain & Co view
We came away from Nvidia’s GTC event last week with a reinforced belief that AI has moved well beyond pilots and proofs of concept to scaled deployment and operational impact. Consistent with what we see in our work with clients, organizations are no longer testing AI at the edges. They are re-architecting how
they compete. Across industries, AI is moving from innovation teams into the business core. Below are nine key themes we observed at GTC that are shaping the enterprise AI landscape.
1. “No data, no AI”—and now, AI is generating the next layer of data.
Data remains the biggest challenge and the biggest opportunity. Every successful AI deployment presented at GTC rested on clean, connected, and accessible data. But the frontier is no longer just data consumption; it’s data creation. AI is surfacing previously invisible insights: operational patterns, best practices, and in-the-moment decisions propelling activities like frontline sales that can be reused and optimized. Generative AI is also helping address classic data challenges, from search and retrieval to confidence scoring and synthetic augmentation. Organizations that invest in feedback loops and change management are building true data flywheels.
Data remains the biggest challenge and the biggest opportunity. Every successful AI deployment presented at GTC rested on clean, connected, and accessible data.
2. Smaller, specialized models are rewriting the economics of AI.
The dominance of large, general-purpose models is giving way to smaller, fine-tuned systems built for specific domains. Techniques like quantization, pruning, and retrieval-augmented generation (RAG) are unlocking cost savings without sacrificing performance. Enterprises are increasingly embracing model fine-tuning and self-hosting for better control, lower latency, and improved privacy—though doing so brings operational complexity that few organizations are fully prepared for at present.
3. Agentic AI is starting to gain traction—and trust depends on structure.
The progression has moved from RAG to AI assistants and now agentic AI. Fully autonomous AI agents, however, are rarely deployed at scale. The biggest challenge remains evaluating the accuracy of an agent’s output, something both business leaders and engineers are grappling with. But a clear theme has emerged: Structure matters. Enterprises are prioritizing transparency, escalation paths, redundancy guardrails, traceability and auditability in production, and predictable behavior. While fully autonomous agents remain rare, semiautonomous systems—with human oversight—are the pragmatic near-term standard. Frameworks like Nvidia AgentIQ are helping bring order to this new frontier. There is also growing momentum around “agent orchestration platforms,” with some companies developing in-house solutions. This trend reflects a broader push to simplify the creation and integration of AI agents into enterprise systems.
4. Digital twins and simulation are now everyday enterprise tools.
Simulation has shifted from innovation showcase to standard operating practice. Teams are using digital twins to model factories, stores, and supply chains, testing changes virtually before implementing them physically. The result is faster rollout cycles, lower risk, and more confident decision making. Executives increasingly prefer virtual walkthroughs over site visits, especially as twins become more integrated with real-time spatial and operational data.
5. Video is becoming the next major dataset.
Computer vision and video language models are transforming video from passive monitoring to active intelligence. Organizations are using video to analyze customer behavior, product interaction, compliance, and safety in real time. These insights are now directly influencing merchandising, labor planning, and layout optimization, turning physical spaces into intelligent, data-rich environments.
6. Enterprises are shifting from build to buy for large language model operations (LLMOps) and infrastructure—and adoption is accelerating.
Off-the-shelf tools like Nvidia DGX Cloud and Inference Microservices (NIM) are lowering the barriers to enterprise AI adoption. Companies are launching copilots, knowledge assistants, and other custom genAI applications without having to build deep machine learning operations or LLMOps stacks. We’re also seeing increased accessibility to advanced capabilities like decision optimization and simulation, now running on out-of-the-box, GPU-accelerated infrastructure.
7. Simulation is emerging as the new collaboration layer.
Beyond modeling, simulation is becoming a unifying platform for cross-functional teams. With Nvidia Omniverse integrating seamlessly into design and operations tools, teams can cocreate in virtual environments before making real-world changes. This is reducing iteration cycles, improving coordination, and unlocking faster, lower-risk decision making across functions.
8. Custom model deployment is the new organizational bottleneck.
Fine-tuning foundation models is becoming easier, but deploying them into production is still hard.
Teams face challenges around performance optimization, latency, hardware compatibility, and security.
Enterprises are realizing that production-readiness requires strong internal capabilities and deliberate investment in infrastructure.
Fine-tuning foundation models is becoming easier, but deploying them into production is still hard.
9. Multimodal AI is transforming creative workflows and brand expression.
Tools like Nvidia Picasso, Adobe Firefly, and open-source diffusion models are enabling teams to generate product visuals, videos, 3D assets, and social content—all from natural language prompts. Companies are scaling content generation with creative pipelines from platforms like RunwayML, Canva, and Synthesia.
This shift is speeding up campaign cycles, enabling hyper-personalization, and making high-quality creative accessible to teams of any size.
Bain & Co
Bain & Company is a global consultancy that helps the world’s most ambitious change makers define the future.
Across the globe, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition, and redefine industries. We complement our tailored, integrated expertise with a vibrant ecosystem of digital innovators to deliver better, faster, and more enduring outcomes. Our 10-year commitment to invest more than $1 billion in pro bono services brings our talent, expertise, and insight to organizations tackling today’s urgent challenges in education, racial equity, social justice, economic development, and the environment.For more information, visit www.bain.com
Bankwatch 