Chad Smykay

Chad Smykay, AI CTO and Distinguished Technologist at Hewlett Packard Enterprise, stands at the forefront of an enterprise technology revolution that's rewriting traditional adoption timelines. 

Where conventional software cycles once measured progress in years, AI developments now arrive monthly, fundamentally changing how executives approach AI strategy.

Chad’s career

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

His early work on fraud detection systems – now ubiquitous in banking – taught him valuable lessons about technology adoption patterns. His experience at Rackspace, helping scale the company from 30 to more than 5,000 employees during its eight-year journey to going public, provides crucial understanding of scaling technology and philosophy simultaneously.

HPE's position

HPE, the US$28bn tech giant focusing exclusively on enterprise infrastructure and cloud services, has positioned itself at the center of the AI revolution.

 The company's GreenLake platform operates as a cloud service model, allowing customers to consume AI-capable resources on demand while addressing capital expenditure concerns that often stall AI initiatives.

The recent US$14bn acquisition of Juniper Networks underscores HPE's commitment to AI-enabled infrastructure. 

Combined with HPE's existing Aruba networking portfolio, this creates an integrated offering addressing the often-overlooked networking requirements of AI implementations. 

"Networking gets left out," Chad explains, emphasising the critical foundation networks provide for AI applications.

A business-first approach

HPE's methodology prioritises understanding business objectives before recommending technologies.

 This consultative approach, informed by Chad's experience across industry verticals with distinct regulatory environments, helps avoid implementing impressive technology that fails to address real business problems.

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

Rather than 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 valuable for healthcare, financial services and government agencies requiring strict data governance.

An ever-changing market

The transformation in customer discussions represents perhaps the most significant shift in Chad's career. Organisations that spent 2023 questioning whether they needed AI strategies now focus on implementation details and governance frameworks. "Customers used to say: 'Do I need to do it?' But we're no longer having that conversation," he reveals.

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

Organisations now discuss advanced concepts like agentic AI, with some bypassing basic implementations like chatbots to focus on sophisticated applications delivering immediate business impacts.

The importance of partnerships

HPE's global reach across continents, industries and use cases creates scale challenges no single organisation can address independently. 

Strategic partnerships like that with Trace3, a Denver-based systems integrator with 13 years of dedicated AI practice, enable comprehensive customer solutions neither organization could deliver alone.

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

One notable collaboration involves a healthcare organization using 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 extending beyond technical considerations to encompass legal, ethical and reputational risks.

"Now, more than ever, it's important that legal's involved from the start," Chad says, advocating for proactive compliance integration rather than treating it as an afterthought. This includes maintaining architectural flexibility to adapt to changing regulations without requiring 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, handling routine tasks without human oversight.

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

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

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