Strategy
AI Strategy
23+ years across enterprise and startup ecosystems, partnering with CTOs and founders to drive responsible GenAI adoption through solution strategy, agent-based architectures, and end-to-end implementation, deeply experienced in retail, supply chain, fashion, real estate, and ESG.
Making AI work = ML/DL/GenAI tech skills + domain skills + product + competitor landscape + strategy + responsible AI adoption = Solution Architect + AI PM + Dev.
AI offerings
- AI readiness assessments
- Technology evaluations and recommendations
- Data strategy and road mapping
- AI ethics and governance
- Product prototyping
- Model research and development
- Ongoing model improvement
Lenses on AI in the product lifecycle
Leadership & C-suite workshops
Built for corporates, enterprises, and SMEs facing the build-vs-buy call
Workshops for leadership and C-suite teams on AI-native transformation, Claude Code and agentic coding, AI security, and responsible AI practices, framed around the decision every executive actually faces: build, buy, or wait.
- AI-native transformation for leadership teams
- Claude Code for teams: structuring work, designing solutions, and applying AI at the product and project level, not just individual coding
- AI security & risk frameworks for the boardroom
- Responsible AI practices, governance, and audit readiness
- Build vs. buy decision frameworks
We won't charge for training alone. We travel through the transformation with your team, so what gets taught in the room is what actually gets practiced and followed on the job.
Readiness Over Awareness
- ✅ GenAI-First Leadership + Trained Team + Best Practices = Productivity
- ✅ GenAI-Ready Leadership + Pilots + Trained Team = Stability
- ❌ GenAI-Aware Leadership + Aggressive Adoption + AI-Aware Team = Chaos
🤝 If this resonates, let's connect, I'll help you identify the one readiness gap costing your enterprise the most.
Recent workshop
Healthcare AI Security Workshop
Recently delivered a hands-on AI security workshop for one of the largest healthcare organizations in the US. The same AI security, governance, and observability challenges show up at any enterprise running AI across multiple platforms and customer touchpoints, especially around:
- Secure AI implementation across passenger and operational systems
- AI risk awareness for engineering and digital teams
- Observability and control for AI-driven workflows
The goal isn't a trained team that forgets the material in a quarter. It's AI running across your systems with the same guardrails and oversight everywhere, not just on the parts someone happened to review.
Prompt injection, data leakage, hallucination control, and the full AI security workshop detail.
See AI security on Responsible AI →Course and workshop pricing is scoped to your team and sector, contact me for pricing →
Low-risk adoption framework
A measured, transparent path from experimentation to production
Six stages: experimentation, model performance auditing, bias/security checks, field testing, real-time audit, and production adoption, built around continuous evaluation and transparency with customers.
Want this framework applied to your own AI rollout?
Book a strategy sprint →Third-party LLM adoption
Discover, evaluate, monitor and finetune
Training
Deep Learning & GenAI instructor
Bridging first principles and industry perspective, 10+ batches trained in deep learning, vision, forecasting, NLP, and capstone projects, with mindmaps built specifically to teach deep learning concepts and production use cases.
Need GenAI or deep-learning training for your team?
Ask about workshops →What a program manager says
What learners say
Bring GenAI training or a strategy sprint to your team
Workshops, MVP/POV architecture reviews, and strategic AI roadmaps.