GenAI Team Skills Gap Assessment

Client: Fortune 500 Retail Company
Engagement Duration: 2 Weeks
Service: GenAI Team Skills Gap Assessment

Objective

Assess the internal data and engineering team’s readiness to support GenAI projects, identify key skill gaps, and recommend upskilling strategies.

What We Did

1. Role-Based Skills Survey

Conducted a structured assessment of roles across data engineers, ML engineers, architects, and analysts.

2. Capability Mapping

Mapped current team strengths across:

• LLM & Prompt Engineering
• Python for AI
• LangChain & RAG concepts
• Data labeling & annotation
• LLMOps tools (Weights & Biases, MLflow)
• Model evaluation & benchmarking

3. Gap Analysis Matrix

Benchmarked against GenAI project requirements to identify low, medium, and high-skill gaps.

4. Actionable Plan Delivered

Delivered a personalized learning roadmap, team-level gap heatmap, and recommendations for hands-on internal labs and certifications.

Outcomes

Gap Visibility: Clear view of current strengths and missing capabilities

Action Plan: 6-week upskilling strategy aligned to upcoming LLM pilot

Team Buy-In: Boosted internal confidence and ownership in GenAI transformation