7 JUL 2026
Akamai Technologies
Akamai AI Day for Partners UKIAkamai Inference Cloud Overview
· London, United Kingdom
John Bradshaw · Field CTO, Akamai · Speaker · Writer
Most digital transformations succeed at the technology and fail at the business.
- $300M cloud transformation led
- 8→150 team built in 18 months
- $2M/qtr FinOps savings delivered
John Bradshaw is a cloud and AI strategist at Akamai Technologies, focused on cloud infrastructure, edge computing, and AI inference. He speaks at conferences across Europe and the Middle East — from WeAreDevelopers World Congress to The AI Summit London — on cloud economics, API security, and bringing AI to the edge.
Explore by topic
All topics → Cloud Economics & Sovereignty Cloud bills rarely blow up on compute — they blow up on egress, lock-in, and architecture decisions nobody revisits. Here's where I work through what actually drives the spend, when "just put it in the cloud" stops being the cheap answer, and how to keep control of your own stack. Edge & Distributed Architecture The interesting compute is moving away from a handful of mega-regions and out toward the user. This is my thinking on edge and distributed architecture — why latency, data gravity, and sovereignty keep pushing workloads outward, and what that changes about how you build. AI Inference Economics Training gets the headlines; inference gets the bill. Here's where I dig into the economics of running AI in production — when an API stops being cheaper than self-hosting, where inference should physically live, and how to stop the per-query cost from eating the margin. Agentic AI & MCP Chatbots were the demo; autonomous agents that take real actions are the product. This is my thinking on the patterns that hold up in production — what to let an agent do on its own, where to keep a human in the loop, and how tools and protocols like MCP make it work at scale. Security & AI Governance Agentic AI changes the threat model: the caller is no longer a person, and the guardrails can't live in a PDF. Here's where I work through API security when the caller is an agent, zero trust in practice, and governance as an operating model — controls that trigger, gates where decisions are irreversible, and audit trails that survive contact with a model. Digital Transformation Most digital transformations succeed at the technology and fail at the business. Here's where I look at what actually moves a programme — the operating model, the funding, the decisions you can't delegate — and why the platform choices are usually the easy part. Media: Content to Experience The streaming wars were won on content; the next ones will be won on experience. Here's where I look at what that shift means for media — why discovery, personalisation, and real-time delivery now matter more than the size of the library.
Upcoming Talks
View all → 16 SEP 2026
InfraXMedia
The Xcelerated Compute Show London 2026The Compute Infrastructure Questions Every AI Buyer Should Ask
· London, United Kingdom
Media
View all media →Short session examining how organisations are reconsidering AI deployment locations as the technology accelerates, exploring how edge-based AI is transforming cloud design, application performance, and data governance.
John Bradshaw discusses whether AI's competitive advantage in 2026 lies in model size or infrastructure placement, and how financial scrutiny is refining rather than slowing adoption, pushing intelligence toward edge infrastructure for improved performance and cost efficiency.
John Bradshaw, Field CTO Cloud EMEA at Akamai, explains why 2026 is shaping up to be the breakout year for AI inferencing — the process of putting trained models to work — and why the market remains wide open for challengers to hyperscaler dominance.
Writing
View all writing →An evidence-led reference on MCP for CTOs and architects — the architecture, the transports, the real security picture, the Linux Foundation governance, and where MCP fits into your build-vs-buy strategy.
Why the build-vs-buy decision is never binary, how to think about total cost of ownership, and the hybrid approach that actually works in practice.
The economics of API vs self-hosted AI inference, where the crossover point sits, and why the hybrid approach wins for most production workloads.