Chad Smykay | Tech Journal

Chad Smykay, AI CTO and Distinguished Technologist at Hewlett Packard Enterprise, is leading a revolution in enterprise technology that is transforming traditional adoption timelines.

While conventional software cycles used to measure progress in years, AI advancements are now emerging monthly, fundamentally altering how executives formulate AI strategies.

Chad’s career

With 25 years in enterprise IT and 12 years specifically focused on machine learning, Chad offers unique insights shaped by the transition from big data to AI.

His early work on fraud detection systems—now common in banking—provided him with valuable lessons about technology adoption patterns. His experience at Rackspace, where he helped scale the company from 30 to over 5,000 employees during its eight-year journey to going public, gives him crucial insights into scaling technology and philosophy simultaneously.

HPE’s position

HPE, the US$28 billion tech giant dedicated solely to enterprise infrastructure and cloud services, has positioned itself at the heart of the AI revolution.

The company’s GreenLake platform functions as a cloud service model, enabling customers to access AI-capable resources on demand while alleviating capital expenditure concerns that often hinder AI initiatives.

The recent US$14 billion acquisition of Juniper Networks highlights HPE’s commitment to AI-enabled infrastructure.

When combined with HPE’s existing Aruba networking portfolio, this creates a comprehensive offering that addresses the often-overlooked networking needs of AI implementations.

“Networking gets left out,” Chad explains, emphasizing the essential role networks play in supporting AI applications.

A business-first approach

HPE’s methodology prioritizes understanding business objectives before recommending technologies.

This consultative approach, informed by Chad’s experience across various industry verticals with distinct regulatory environments, helps avoid the implementation of impressive technology that fails to solve real business challenges.

The company’s Private Cloud AI solution exemplifies this philosophy.

Instead of forcing customers into public cloud environments that may not meet regulatory requirements, this turnkey solution includes Nvidia’s GPU infrastructure, pre-configured software stacks, and professional services deployed on customer premises—particularly beneficial for healthcare, financial services, and government agencies that require strict data governance.

An ever-changing market

The shift in customer discussions represents perhaps the most significant change in Chad’s career. Organizations that spent 2023 questioning the need for AI strategies are now focused on implementation details and governance frameworks. “Customers used to ask: ‘Do I need to do it?’ But that conversation is no longer happening,” he reveals.

This evolution has compressed typical enterprise technology adoption cycles from years to months.

Organizations are now discussing advanced concepts like agentic AI, with some skipping basic implementations such as chatbots to concentrate on sophisticated applications that deliver immediate business impacts.

The importance of partnerships

HPE’s global reach across continents, industries, and use cases presents scale challenges that no single organization can tackle alone.

Strategic partnerships, such as the one with Trace3, a Denver-based systems integrator with 13 years of dedicated AI experience, enable comprehensive customer solutions that neither organization could provide independently.

These partnerships address the general shortage of qualified AI and data science professionals while offering proven delivery capabilities.

One notable collaboration involves a healthcare organization utilizing computer vision for 3D heart imaging analysis, leveraging HPE’s Private Cloud AI environment to detect anomalies in real-time medical imaging.

Navigating regulations

The complex regulatory landscape requires careful navigation across multiple jurisdictions and industries.

EU regulations, state-level legislation, and industry-specific compliance requirements create obligations that extend beyond technical considerations to include legal, ethical, and reputational risks.

“Now, more than ever, it’s crucial that legal is involved from the start,” Chad states, advocating for proactive compliance integration rather than treating it as an afterthought. This includes maintaining architectural flexibility to adapt to changing regulations without necessitating complete system rebuilds.

Looking to the future

Looking ahead, Chad anticipates widespread adoption of agentic AI systems where autonomous agents collaborate through open marketplaces to accomplish complex tasks.

These agent marketplaces could enable AI systems to communicate independently across organizational boundaries, managing routine tasks without human oversight.

Among various AI applications, life sciences research generates the most excitement due to its potential societal impact.

Specialized LLMs designed for genomics and chemistry datasets promise significant healthcare breakthroughs within three to five years, potentially revolutionizing medical research and treatment development.

Read the full story HERE.