Technology Live! Munich: Solidigm Shares Why AI Success Starts with People, Not Just Technology

AI is shifting team culture and performance.

Solidigm leaders shared their experience from an eight-quarter internal AI transformation journey. The message was clear: AI adoption is not simply about deploying new tools.

Franklyn continued that leaders need to approach AI holistically as a change management initiative to encourage new behaviors, build confidence, and create lasting habits across the organization. This includes establishing common AI platforms, empowering AI champions within each department, and encouraging peer-to-peer learning rather than relying solely on top-down mandates.

Rather than simply adding AI to existing workflows, he explained the advantages of integration across engineering, planning, and software development after process re-engineering. According to Franklyn, this is driving measurable results in usage and business outcomes, including faster development cycles, improved operational efficiency, and accelerated time to market.

For instance, workflows that once took weeks can now be completed in hours. “We don’t continue to invest because everyone says AI will change the world,” explained Franklyn. “We continue to invest because we see ROI and actual business impact.”

AI is redefining infrastructure economics.

The presentation also explored how AI is fundamentally changing enterprise data and the infrastructure required to support it.

Organizations are generating richer, multimodal data and increasingly complex inference workloads, and information is constantly moving between hot, warm, and cold storage tiers. This shift is driving new infrastructure requirements, with AI data centers demanding high-capacity, high-performance storage alongside GPUs.

As AI clusters continue to grow, floor space, rack density, cooling, and power delivery are becoming just as important as terabytes. Reflecting on how AI is reshaping storage economics, Solidigm leaders shared their firsthand experience seeing the industry shift toward metrics that optimize the entire AI data center.

In addition to questions about drive capacity, Shadley added that data center footprint questions, even down to how many floor tile spaces can be saved, are starting to dominate conversations with customers as AI systems continue to grow at massive scale and pace.

Solidigm leaders continued by emphasizing the role power efficiency plays in ensuring every watt and square inch is maximized for AI performance.

This is why, Shadley explained, Solidigm was one of the first to introduce cold-plate eSSD technology to enable fully liquid-cooled fanless server environments with improved thermal efficiency, a smaller design footprint, and decreased cooling costs. He clarified that liquid cooling benefits extend beyond power reduction as additional power availability can free up power for valuable AI cluster resources, especially GPUs.

The presentation closed by reinforcing that as AI workloads can and will continue to scale, organizations must think beyond traditional metrics and reevaluate the entire infrastructure stack—especially storage.