Every AI initiative passes the same intake template: purpose, assumptions, risks, business value. Then it moves on one path — idea, pilot, production. Nothing skips a stage.
Five initiatives are live: AI-assisted requirements analysis, test-documentation generation, a regression-test prioritisation agent, a DevOps self-service assistant, and AIOps anomaly detection.
I connected AI agents to enterprise tools such as Jira and Confluence through MCP servers.
I built a library of 20 AI skills and around 50 prompts, shared across teams. I designed and ran role-based AI enablement for more than 50 employees. I developed five AI service offerings and an AI adoption strategy for the software development lifecycle.
Current
I wrote the AI policy my employer adopted, after working through the EU AI Act and GDPR.
Commercial proposal prep went from two weeks to one. Monthly capacity went from about 30 to 45–50. I’ve taken client AI opportunities from discovery through solution design to enterprise negotiation, and contributed to around $800K in AI-related deals.
Current
I also manage our vendor network and assign vendors to sales opportunities.
I led the work supporting the AWS Generative AI Competency and Anthropic partnership activities. That was work on the competency requirements.
With HR, I built AI functionality into the internal employee-discount portal. I led it and designed the functionality as the business analyst. The AI picks the most relevant discounts for each employee’s weekly email. It’s in pilot, with a company-wide audience.
I speak at webinars and events as an expert on AI adoption, AI in the software development lifecycle and broader AI topics.