Your AI Is Starving for Good Data

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From Day One Editors
April 24, 2026 • Estimated Reading Time: 8 minutes

Before companies can get real value from AI, they run into a more basic constraint: most of their data isn’t good enough yet.

Despite all the excitement surrounding large language models, Raman Achutharaman, the SVP of operations, AI and productivity at Applied Materials, emphasizes that the real frontier lies in scientific and engineering data. The publicly available corpus of information, research papers, and technical articles is often biased toward positive results and lacks the calibration needed for rigorous scientific work. 

“You’ve got to generate your own data,” he said during a fireside chat at From Day One’s Silicon Valley conference. 

To that end, Applied Materials is investing billions in a new research and development lab in Sunnyvale, California. The facility will help generate high‑quality data that will fuel the next generation of semiconductor innovation. 

“Having data at the right rate, using AI to be able to solve complex problems, needs not just AI. You actually need a whole bunch of other things: engineering, physical infrastructure, and actual experiments,” he said. 

The Quiet Giant of the Semiconductor Revolution

Applied Materials doesn’t manufacture the tech gadgets that have become part of our daily lives, like smartphones and laptops; instead, it builds the multi‑million‑dollar equipment that manufacturers use to produce the semiconductors inside them. 

As Achutharaman said to Steve Koepp, co-founder and editor at From Day One, who moderated the conversation, a single advanced logic chip requires roughly 2,000 processing steps and three months to complete, despite being “a thousand times smaller than a human hair.” Founded in 1967, Applied Materials predates companies such as Apple and Intel in Silicon Valley and now employs more than 36,000 people globally.  

The company’s immense global footprint, supercharged by the accelerating AI revolution, makes digital transformation an urgent directive. To help meet this objective, Achutharaman’s role was created specifically to unify an organization that had grown “very global” and “very vertical.” He frames his team as an “internal consulting arm,” a nimble force that’s embedded in the middle to drive collective growth and navigate the friction of cross‑functional execution.

A Different Approach to Innovation

When generative AI burst onto the scene, Achutharaman joined forces with the company's CIO and CTO to form a leadership trio that would charter the company's AI journey. Their guiding principle was to avoid using “AI for the sake of AI.” Instead, they focused on re‑engineering decades‑old workflows. 

This mindset has led to a deliberate, problem‑centric rollout. The company established rigorous governance structures early on instead of unleashing every new tool on its workforce, addressing cybersecurity, intellectual property protection, and ethical concerns before any technology was deployed. “You’ve got to find what value you’re going to generate, and then which tech comes along the way,” he said.

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