At HPE Discover More Mumbai, Sue Preston, Worldwide Vice President & General Manager – Advisory and Professional Services, Hewlett Packard Enterprise, outlined why governance, data maturity and hybrid architectures will define the next phase of enterprise AI.
Mumbai’s HPE Discover More event came at a time when enterprises are grappling with an uncomfortable paradox: while artificial intelligence is everywhere in boardroom conversations, very few organisations have been able to convert pilots into measurable business outcomes. Amid the buzz around GenAI and agentic AI, Sue Preston’s keynote struck a pragmatic note — one grounded in architecture, data discipline and trust.
Preston, who leads HPE’s Advisory and Professional Services business globally, spends nearly half her time engaging directly with customers across industries. Her perspective is shaped less by hype cycles and more by the recurring challenges she sees on the ground.
“Most enterprises are not short on AI ideas. What they struggle with is turning fragmented experimentation into scalable, governed outcomes that the business can trust,” said Preston.
From noise to relevance
According to Preston, one of the biggest expectations from CIOs and digital leaders today is clarity — clarity on which technologies matter, where to invest, and how to avoid long-term lock-in. HPE’s advisory-led approach is designed to cut through this noise.
Her teams work across HPE’s core pillars — networking, hybrid cloud and AI — underpinned by cybersecurity, resilience, sustainability and skills. The starting point, she emphasised, is not technology, but business intent.
“Our role is to help customers define the architectural strategy that aligns to their business goals. Technology should accelerate outcomes, not complicate them,” she noted.
AI-driven networks and zero trust by design
As enterprises move to distributed and hybrid operating models, the network has become the heartbeat of digital operations. Preston highlighted a clear shift toward AI-driven, self-healing networks where observability and security are embedded, not bolted on.
With HPE’s Aruba networking at the edge and Juniper capabilities extending into the data centre, enterprises are increasingly looking for a single pane of glass to manage performance, resilience and threat response.
“Customers want networks that can predict, observe and fix issues before anyone even knows there’s a problem. Zero trust has to be built in by design,” Preston explained.
Hybrid by default, governed by design
From manufacturing and retail to BFSI, Preston pointed out a consistent pattern: the world is now hybrid by default. Data lives across edge locations, private clouds and hyperscalers, and enterprises need visibility and control across this sprawl.
HPE GreenLake, combined with its Cloud Management Platform, enables organisations to run workloads where they make the most sense — on-prem, at the edge or in the public cloud — while retaining governance and cost transparency.
“The question customers ask us is simple: which workloads should run where, and how do we manage them as one estate?” she said.
Virtualisation, openness and future-proofing
Another area seeing intense scrutiny is virtualisation. With rising licensing costs and concerns around vendor lock-in, enterprises are reassessing their long-term strategies. Preston pointed to HPE’s investments in Morpheus, VM Essentials and OpsRamp as critical enablers of an open, flexible operating model.
“Every enterprise customer I meet is re-evaluating virtualisation. They want to maximise what they have today, while keeping the agility to move to what comes next,” she stated.
Why AI stalls at pilots
Despite the enthusiasm around AI, most organisations remain stuck in experimentation. Preston attributed this to a combination of low data maturity, weak governance, skills gaps and siloed decision-making.
Drawing from HPE’s Architecting the AI Advantage research, she noted that overconfidence in readiness is often a hidden barrier.
“You cannot deliver agentic AI without trusted data and strong data governance. Data is the fuel — without it, AI simply doesn’t scale,” Preston stressed.
HPE’s discovery workshops are designed to address this by bringing business, IT, legal and compliance stakeholders together, aligning priorities and identifying use cases with the fastest path to value.
From GenAI to agentic AI
Looking ahead, Preston believes agentic AI will redefine enterprise operations over the next 24–36 months, enabling more autonomous decision-making across networks, infrastructure and business processes.
This shift, however, will place even greater emphasis on AI-ready data layers, unified hybrid command centres and secure-by-design architectures.
“Enterprises will need AI-ready data fabrics, unified observability and architectures they can trust to make autonomous decisions,” she pointed out.
Sustainability as a core design principle
Beyond AI, Preston is deeply invested in sustainability and ethical innovation. From energy-efficient data centre design to GreenLake Intelligence for carbon and ESG reporting, HPE is increasingly embedding sustainability into infrastructure decisions.
“As AI workloads grow, energy efficiency, emissions visibility and sustainability metrics become non-negotiable. You can now measure carbon impact per workload,” she said.
She also highlighted HPE’s broader ‘force for good’ initiatives — from heat reuse projects with global partners to AI-driven supply chain transparency pilots addressing forced labour risks.
As enterprises enter 2026, Preston’s message to CIOs was clear: success in AI will not be defined by who experiments the fastest, but by who governs, scales and sustains the smartest.
“AI is not just a technology shift. It’s an organisational shift. Those who invest in the foundations — data, architecture, skills and trust — will be the ones who truly realise its value,” she concluded.