HP Is Putting AI to Work at Scale as Customer Zero

What does it take to deploy AI across an enterprise?
 
One lesson has become clear: organizations scale AI by transforming how work gets done.
 
"It's important to really understand that there's far more to AI than a tech rollout. It really is a business transformation," says Niall Johnston, Chief Information Officer at HP. 
 
Organizations that achieve meaningful outcomes from AI are often the ones that first establish the right foundations, including consistent data, repeatable processes, governance frameworks and workforce readiness.
 
As AI moves from experimentation into core business operations, those foundations become increasingly important. Reliable data enables AI systems to generate useful outputs. Governance helps build trust. Standardized processes create the consistency needed to scale AI across teams and functions.
 
For many organizations, the challenge is creating the conditions that allow AI to be deployed responsibly and effectively.
 
Why does enterprise AI require a hybrid approach?
 
As organizations begin embedding AI into everyday workflows, enterprises are considering where AI should run.
 
"We believe AI deployment in enterprises like HP will be hybrid," says Ayan De, Global Head of Corporate & Solution Strategy at HP. "Some workloads will run locally, while others will run in the cloud, depending on where they can deliver the most value."
 
As Paul Thomas, VP of Engineering at HP, explains, "We don't need a professor to tell us how to boil an egg."
 
As organizations evaluate AI deployment strategies, they are increasingly looking at how to match workloads to the environments and levels of intelligence that can deliver the best balance of performance, cost and user experience.
 
"One of the challenges today is that we expect users to choose the right AI model, and they'll gravitate toward the most advanced one," Thomas says. "But not every task requires the most powerful model. A key role of the AI PC will be intelligently matching the workload to the right level of inference, improving both quality and cost efficiency."
 
What are we learning from AI deployment inside HP?
 
HP's own AI journey is helping us better understand how AI can improve both employee experiences and business outcomes.
 
We're seeing firsthand that matching workloads to the right environment isn't just a technical decision. It can have a measurable impact on employee productivity and experience.
 
In an internal study of 4,000 HP senior leaders and customer-facing employees using AI PCs, participants reported time savings of up to four hours a week across communication, content creation and data analysis workflows.¹
 
We're also seeing how AI can help organizations operate more efficiently behind the scenes.
 
The HP Workforce Experience Platform (WXP) acts as the feedback loop connecting devices, telemetry and employee experience data, enabling HP IT to move from reactive support toward proactive experience management.
 
By combining AI with data from connected devices and applications, WXP also helps HP IT improve experiences, reduce waste and operate more efficiently. For example, analysis of fleet data across connected printers revealed that toner cartridges were often replaced prematurely. By fine-tuning the replenishment process, HP reduced toner waste from 25% to 5%.²
 
Together, these experiences reinforce an important lesson: AI delivers the greatest impact when it is applied to real business challenges and supported by the right governance, security and employee trust.
 
How is HP applying these lessons for customers?
 
As "customer zero," HP uses its own experience to help inform the technologies, services and best practices we bring to customers.
 
What we're learning reinforces the value of hybrid AI: matching trusted intelligence to the right place, at the right time and for the right workload, with the security, governance and visibility to support it.