1. Find where AI can remove manual, repetitive or slow work, by sitting with teams across all departments and watching how they work rather than relying on what a request form says.
2. Coordinate across departments to scope each initiative: agree what is being solved, who is affected, what data and system access is needed, and who signs off before building starts.
3. Design the solution: shape the flow, the screens and the experience so the tool is genuinely usable by non-technical colleagues.
4. Build it. Use AI-assisted development tools to go from idea to working prototype in days rather than months, then iterate with real users until it is good.
5. Ship internal tools, assistants and automations to production, and take responsibility for whether people use them.
6. Build automations and integrations that connect systems, using tools such as n8n and APIs to move data between e-commerce, CMS, ERP, CRM and third-party services.
7. Handle the unglamorous parts of a working system: error handling, retries, edge cases, monitoring, and fixing things when they break.
8. Evaluate new AI tools and models, run quick tests to see whether they solve a real problem, and recommend what is worth adopting.
9. Measure impact. Agree what success looks like before building, then show the time saved or the improvement delivered afterwards.
10. Keep stakeholders across departments informed: run working sessions and demos, report progress on active initiatives, and manage expectations on priorities and timelines.
11. Drive adoption: demonstrate what has been built, coach colleagues on prompting and usage, and follow up so tools do not go unused.
12. Document what you build clearly enough that someone else can pick it up, and support colleagues onboarding onto new tools.
13. Work with vendors and development partners where a build is beyond what can be done in-house.
14. Ensure all work follows Maison’s IT processes, standards and data handling rules.
