At MWC 2026, Ameer Saithu, Executive Vice President of Semiconductor at HCLTech, and Gaston Sandoval, Corporate Vice President, PC Marketing and Commercial Channel at AMD, explored how artificial intelligence is transforming the semiconductor value chain, and what it means for enterprises looking to scale AI.

Their discussion highlighted a fundamental shift: the conversation is moving beyond processors toward outcomes.

From chips to outcomes

For decades, semiconductor innovation has focused on performance metrics, including cores, process nodes and processing power. But AI is reshaping the discussion.

According to Sandoval, enterprises are increasingly less interested in hardware specifications and more focused on business impact.

“AI is moving really fast, and the role we play in semiconductors is becoming very prominent,” he said. “But the conversations we’re having with customers are changing. They’re saying: let’s talk less about chips and more about outcomes.”

Many organizations have already experimented with AI through pilots and proofs of concept. The next challenge is scaling those initiatives into production environments that deliver measurable value.

“The other big question we’re getting is: ‘I’m doing a lot of pilots, now it’s time to scale. How do I go from pilots to production?’” Sandoval explained.

That shift requires enterprises to rethink the entire technology stack.

“It really puts pressure on looking at the complete architecture of the solutions you’re trying to deploy, all the way from silicon to managed services. And we’re working with global system integration leaders like you [HCLTech] to make that happen.”

Rethinking the AI architecture

Scaling AI is forcing companies to consider infrastructure decisions more holistically. Instead of evaluating individual components in isolation, organizations must design integrated architectures spanning chips, cloud platforms and enterprise applications.

Saithu noted that this systems-level view aligns closely with how HCLTech approaches digital transformation.

“Technology does not just come from enterprise applications onwards,” he said. “It actually goes all the way from the chip to cloud.”

Semiconductor innovation remains a key driver of AI capability. While many AI breakthroughs appear in consumer-facing tools, much of the underlying progress happens deeper in the stack.

“A significant part of the advancements in AI has happened at the chip level,” explained Saithu. “The disruption happening at companies like AMD is critical for us to bring to our customers.”

As a result, enterprises increasingly need partners who can connect innovations at the silicon layer to real-world industry use cases.

The rise of ecosystem-driven innovation

Another major shift is the growing importance of partnerships across the technology ecosystem.

AI solutions today span hardware vendors, cloud providers, software platforms and system integrators. No single company can deliver the entire stack independently.

“The combination of silicon, hardware OEM partners, ISVs and system integrators — that actually becomes the product,” said Sandoval.

For semiconductor companies, partnerships are not just operational necessities but strategic differentiators.

“Partnerships can amplify differentiation, or destroy it,” he said. “Working with partners that understand business priorities and business pain points is essential.”

Maintaining openness across ecosystems is also becoming increasingly important as organizations experiment with different AI architectures.

“We want to make sure we do not lock in our customers, so they have the freedom of choice and the freedom of adjustments, because AI is moving so fast,” added Sandoval.

A new role for semiconductor companies

AI is also reshaping how semiconductor companies engage with enterprises.

Historically, many chip companies primarily worked through OEM and hardware partners. But AI-driven infrastructure decisions are pushing semiconductor providers closer to enterprise technology strategy.

“Traditionally AMD was seen as a consumer or gaming brand, not so much an enterprise player,” said Sandoval. “AI has given us an incredible platform to have different conversations.”

Enterprises are now seeking strategic discussions about infrastructure, architecture and long-term innovation.

Customers are increasingly asking how to layer intelligence on top of their existing technology environments.

“Customers are looking at how they put another layer on top of their infrastructure — an intelligent layer that sits on top of AI,” said Sandoval. “That becomes the key interactive layer with the end user.”

Co-engineering the future of AI

As AI adoption accelerates, deeper collaboration across the semiconductor ecosystem is becoming essential.

Saithu emphasized that meaningful transformation requires long-term partnerships built around co-creation, co-engineering and shared technology roadmaps.

“Many of these investments take 18 to 24 months to realize the business case, so we need to understand what is coming next.”

That forward visibility allows organizations to design future-ready platforms and business models.

“The kind of intimate partnership where you do co-creation and co-engineering together is what customers are demanding now,” agreed Sandoval.

Ultimately, from component supplier to strategic partner in enterprise transformation, AI is redefining the semiconductor industry’s role.

As organizations move from experimentation to scaled AI deployment, success will depend on how effectively companies connect innovations across the entire technology stack.

From silicon to systems, the semiconductor value chain is becoming the foundation of the AI-native enterprise.