I'm Fawaz — an Organizational Developer working at the seam where talent practice meets AI adoption. I help large, regulated organizations absorb new tools without losing their footing.
I work at the intersection of organizational development and AI adoption — the place where workforce assessments, change management, and the actual tools the team uses next quarter all sit on the same page.
For the past four years I've built and delivered learning, training, and OD programs at BAE Systems Arabian Industries — leading induction for thousands of learners, authoring procedural frameworks that survived CCB review, and stepping in as Acting Training Lead and Acting Internal Quality Specialist where the work demanded it.
Today my focus is AI adoption inside a regulated industrial environment: building local LLM solutions for safety and data residency, shipping Python dashboards and internal SaaS that have cut routine workload by 40%, and authoring the SOPs and concept-of-operation documents the new function will run on.
Building local LLM solutions calibrated for safety, compliance, and data residency. Shipping Python dashboards and internal SaaS that have cut routine training workload by 40%. Authoring the SOPs, CONOPs, and standardization frameworks for a function still being built.
Conducted organizational assessments and translated employee feedback into targeted learning solutions. Used Power BI to evaluate initiative effectiveness. Authored procedural frameworks for cross-departmental consistency. Led the pilot of a 10,000-slide Articulate Storyline course built entirely in-house.
Led a cross-functional team of 11–15 through a period of organizational transition. Implemented performance management systems. Ran standardization workshops and audits aligning departmental practice with organizational goals.
Designed and delivered training programs aligned with organizational objectives — induction, leadership, customer loyalty. Inducted 2,000+ learners. Assessed competencies to measure workforce readiness.
Proved internal build as a viable alternative to off-the-shelf procurement. Curriculum, content, and assessment authored in-house and pushed through standardization review.
Calibrated for safety, compliance, and data residency. Paired with Python dashboards and internal SaaS that cut routine workload by 40%.
Programs designed to bridge classroom learning and operational readiness. Reused across multiple cohorts and refined each cycle. Onboarding designs measurably improved integration and retention rates.
Gave newly appointed members an immediate frame of reference for current projects.
Surfaced the data leadership needed to evaluate and refine initiatives.
Led an 11–15 person cross-functional team. Strengthened collaboration; sustained delivery through the change.
Tools change quarterly. The organization absorbing them does not. The hardest part of AI adoption is the slow, careful work of preparing the team that will inherit it.
Best fit: leaders and teams navigating AI adoption inside complex, regulated environments — and anyone trying to make L&D infrastructure keep pace with what their tools now do.