Generative AI for Leaders
Driving Transformation, Efficiency, and Strategy Across the Software Lifecycle.
July 28 @ 9:00 am – July 30 @ 5:00 pm UTC+5:30
About the event
Generative AI is reshaping how software is planned, built, and delivered. This executive learning experience is designed for senior leaders seeking to responsibly and effectively embed GenAI capabilities into their delivery ecosystems. Through real-world use cases, expert-led insights, and hands-on strategic planning, participants will learn how to navigate the GenAI landscape across the Software Delivery Lifecycle (SDLC) — from tooling decisions to ethical adoption and scalable implementation.
What You’ll Gain:
- Actionable GenAI use cases mapped to each stage of the SDLC
- Clear evaluation criteria for tools and platforms (build vs. buy, cloud vs. open-source)
- Awareness of ethical, legal, and compliance risks in GenAI delivery
- A leadership framework for scaling GenAI across teams and portfolios
- A tailored 30/60/90-day roadmap to kickstart or accelerate your GenAI adoption journey
Target Audience:
- Senior Delivery & Engineering Managers
- Portfolio & Program Leaders
- Heads of Enterprise Delivery & Transformation
- Client Engagement & Delivery Excellence Professionals
- Innovation Leads & AI Adoption Champions
Prerequisites:
- Experience managing software delivery, programs, or technology portfolios
- Basic familiarity with AI/ML concepts (helpful but not required)
- A strong interest in driving change, innovation, and digital transformation
Reserve your seat now — limited spots available for this high-impact leadership event!
Topics Covered:
- Introduction, course objectives, and participant expectations
- The evolution of GenAI: From rule-based bots to LLM-powered agents
- Key technologies: LLMs, prompts, multimodality, retrieval-augmented generation
- GenAI vs traditional AI in delivery environments
- Role transformation: New-age Delivery Manager mindset
- Industry trends: GenAI adoption in enterprise delivery functions
- Case study and Demonstrations of GenAI use cases (e.g., planning assistant)
Interactive Elements:
- Group Activity: “What could GenAI mean for our delivery organization?”
- Discussion: Real-life challenges GenAI could address
Outcome:
Participants gain a foundational understanding of GenAI and its strategic relevance in delivery management.
Topics Covered:
- Overview of the Software Delivery Lifecycle (SDLC) and its pain points
- Mapping GenAI use cases across delivery stages:
- Planning and estimation
- QA and defect triaging
- Documentation and reporting
- Stakeholder communication
- Risk tracking and retrospectives
- Prioritizing use cases: ROI, complexity, feasibility
- Case studies and tool demonstrations
Interactive Elements:
- Team Exercise: Map GenAI to current delivery projects and workflows
Outcome:
Participants identify specific high-impact areas within their delivery functions where GenAI can create value.
Topics Covered:
- AI ethics in delivery environments: Hallucination, bias, explainability
- Working with client and proprietary data: Privacy, IP, and regulatory considerations
- Shadow AI and prompt injection: Risk examples in delivery workflows
- Creating GenAI usage guidelines and policy guardrails
- Red-teaming GenAI in delivery settings
- Audit, logging, and incident response in AI-powered tools
Interactive Elements:
- Exercise: Draft a “Responsible GenAI Use Policy” for delivery teams
- Discussion: Common pitfalls in GenAI governance
Outcome:
Participants develop awareness of the guardrails needed for secure, compliant, and ethical GenAI adoption.
Topics Covered:
- Change management for GenAI introduction
- Overcoming resistance and fear of automation
- Delivery team enablement: Upskilling plans, CoE models, and experimentation charters
- Organizational maturity models for GenAI adoption
- Stages: Exploration → Experimentation → Integration → Institutionalization
- Optional Segment: Agentic AI – task orchestration, co-pilots, and autonomous agents in delivery
Interactive Elements:
- Facilitated Workshop: Each participant maps 2–3 GenAI opportunity areas in their team
- Group Reflection: Barriers and accelerators to team-wide adoption
Outcome:
Participants are equipped to begin piloting GenAI tools and drive adoption across their teams.
Topics Covered:
- Mapping delivery pain points to GenAI opportunities
- Aligning GenAI initiatives with client and business strategy
- Tooling discussion: Open-source (LangChain, LlamaIndex) vs cloud tools (Vertex AI, Azure OpenAI)
- Tool selection frameworks: build vs buy, integration strategies
- GenAI Operating Models and pilot project frameworks
- Delivery-centric AI Strategy and Governance Blueprint
- Metrics and KPIs for AI adoption success
- Key challenges and mitigation strategies
Capstone Activity:
- Build a personalized 30/60/90-Day GenAI Roadmap
- Identify 2 pilot projects
- Define success criteria and checkpoints
- Outline team onboarding and enablement plan
Closing Session:
- Final Q&A
- Feedback and insights sharing
- Resource handout: Tools, templates, and reference materials
Outcome:
Participants walk away with a strategic plan for implementing GenAI across their delivery portfolio.
Topics Covered:
- Overview of low/no-code GenAI platforms (e.g., Microsoft Copilot Studio, OpenAI playground, Zapier AI)
- Building delivery assistants, risk analyzers
Hands-On Simulations:
- GenAI use cases implementation using Dataiku
- GenAI Chatbot implementation using private knowledgebase
Outcome:
Participants gain firsthand experience creating working GenAI prototypes using simple tools – without needing to code.
Topics Covered:
- AI Agents – What & Why?
- AI Agent vs Agentic AI
- Agentic AI Design Patterns
- Key Agentic AI Platforms
Hands-On Simulations:
- Building AI Agents using n8n
- Building AI Agents using Dataiku
