Matthew Atherfold

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Dublin & London · Enterprise AI · Data · Transformation
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2024–20252 min read

Workday · Chief of Staff, Product Engineering Transformation

Stood up Workday's AI Centre of Excellence and a new Asia innovation centre.

Chief of Staff to the SVP running 2,500 engineers building AI-enabled HCM and Finance. Established the AI CoE, opened a new Asia innovation centre, and ran the operating cadence behind the org.

Case at a glance— 01
Problem type

Turn AI into operating capability

The mandate

Give a 2,500-person engineering org a single operating rhythm, a credible AI capability layer underneath the product roadmap, and a second centre of gravity in Asia, without slowing the release train.

Workstreams

1

Distinct parts of the intervention

Headline result

2,500

Engineers in scope

Measured outcomes— 02
2,500
Engineers in scope
1
AI CoE established
1
Asia innovation centre opened
HCM + Fins
Product lines supported
The situation— 03
Context

What was happening.

Workday's Product Engineering & QA organisation, 2,500 engineers across HCM and Finance, was shipping AI-enabled product on an accelerating cadence while standing up new geographies and absorbing a step-change in expectations from customers, regulators and the board.

Mandate

What had to change.

Give a 2,500-person engineering org a single operating rhythm, a credible AI capability layer underneath the product roadmap, and a second centre of gravity in Asia, without slowing the release train.

What changed

The moves that made the difference.

The intervention, broken into the moves that mattered.

01

Highlights

5 moves
  • Ran the SVP's operating cadence, strategy reviews, staff meetings, board and exec readouts, OKR rollups, so the org made decisions on the same drumbeat instead of in side-channels.
  • Established Workday's AI Centre of Excellence as the shared capability layer behind HCM and Finance: shared patterns, evaluation harnesses, responsible-AI guardrails and a single intake for cross-product AI work.
  • Opened a new Asia innovation centre, site selection input, leadership hiring plan, charter and operating model, giving the org a second time zone for follow-the-sun engineering and a closer line to APAC customers.
  • Built the executive narrative connecting AI investment, engineering capacity and customer outcomes, so the same story held up in board, customer and all-hands settings.
  • Acted as translator between engineering leadership, product, GTM and the CEO's office, converting technical constraints into commercial language and commercial pressure into engineering priorities.
What I would carry forward
“What I'd repeat: build the AI capability layer as shared infrastructure, not as a feature team, the second and third product lines only move fast if the first one paid the governance, evaluation and guardrail tax once. What I'd change: I'd over-invest earlier in the connective tissue between the AI CoE and the release trains. The hardest part of an AI CoE isn't standing it up; it's stopping it from becoming a parallel org the product teams route around.”
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