Enterprise AI has moved rapidly from experimentation to
implementation, but turning an idea into a secure, scalable and
commercially viable solution remains complex. In this episode,
Kevin Brown speaks with Chris Campbell, Senior Director, AI
Solutions at World Wide Technology, about how organisations can
identify valuable AI use cases, prepare their data and determine
where their workloads should run.
Chris shares lessons from WWT’s own AI adoption journey,
including its evaluation of approximately 70 initial use cases
and the development of tools designed to improve internal
efficiency. He explains why successful AI projects require more
than access to a model or computing power. Organisations also
need strong executive sponsorship, clearly defined business
outcomes, reliable data and an infrastructure strategy aligned
with the needs of each workload.
The conversation then turns to hybrid AI infrastructure and the
growing role of neocloud providers. Chris explores the trade-offs
between public cloud, private infrastructure, colocation and
rented GPU capacity, as well as how neoclouds can provide a
bridge while enterprises develop their longer-term facilities.
With significant new data centre capacity under construction, he
argues that the industry is still at the beginning of a much
longer transformation.
Featured guest: Chris Campbell, Senior Director, AI Solutions,
World Wide Technology
Key quote: “We’re in the first mile of a marathon that’s never
going to end.”
Key takeaways:
Successful enterprise AI programmes begin with clearly
defined business problems and measurable outcomes, rather
than technology alone.
A cross-functional AI centre of excellence can help
organisations assess use cases, data readiness, risk and
potential return.
Clean, accessible and well-governed data remains fundamental
to moving AI projects from pilot to production.
AI workload placement should reflect factors such as
security, data sovereignty, cost, performance, scalability
and time to deployment.
Neocloud providers give organisations access to dedicated GPU
capacity without requiring them to build and operate
infrastructure immediately.
A hybrid approach can allow enterprises to use rented
capacity as a bridge while developing longer-term private,
hosted or on-premises AI environments.
Follow or subscribe to The Machine Room on your preferred podcast
platform for more conversations with the people turning AI
ambition into operational infrastructure.
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