Faysal AzizFA-0224Agentic & Generative AIDevOps, Cloud & Infrastructure
GenAI Transformation
Empower leaders and managers to co-create an AI-enabled organization guided by purpose, trust, and strategic vision.
Introduction
Why this course
One day
In an era where Generative AI isn’t just a tool but a workforce game-changer, leaders must transcend mere adoption to craft a future where AI augments human ingenuity. This intensive one-day course equips executives, managers, and IT leaders with transformative strategies—spanning strategic vision, human-centered design, IT integration, governance, and culture change—to not just implement AI, but to embed it meaningfully into operations and support ecosystems.
Anchored in deep industry insight and real-world applicability, this course delivers actionable frameworks to inspire confidence, drive adoption, and ensure Generative AI becomes a business enabler—not a liability.
Learning outcomes
Learning outcomes
Participants completing this course will be able to:
- Articulate a clear, purpose-driven AI “North Star” aligned with business vision and IT support realities.
- Design and lead a strategic roadmap that integrates leadership priorities with IT managers, support teams, and infrastructure workflows.
- Leverage AI for support operations—automating incident detection, ticket triage, and infrastructure/application management.
- Anticipate challenges and risks including resistance, technical debt, and governance gaps.
- Drive change through people-first transformation, enabling experimentation, upskilling, and IT–business collaboration.
- Apply practical prompting techniques to unlock AI’s full value in real support and managerial scenarios.
Prerequisites
Prerequisites
- A basic understanding of AI / GenAI—what it does and its business potential.
- Representation from leadership, IT managers, support teams, and change agents for a holistic perspective.
- Access to organizational strategy documentation, IT service management practices, and data governance policies.
- Commitment to experimentation, open culture, and willingness to iterate.
Training outline
7 modules
·
01Framing the Transformation2 topics
1.1 Why GenAI? Purpose beyond hype
- The imperative: Why ask “why?” before adopting AI.
- Learn from real-world missteps (e.g., Commonwealth Bank’s AI misfire).
- Why IT support is the frontline of adoption—linking vision to infrastructure and service delivery.
1.2 Defining the “North Star” for GenAI
- Outcome-focused vision over tool deployment.
- Map organization maturity: manual → AI-augmented → agentic swarms.
- Align IT operations, service desks, and business functions with the North Star.
02Strategic Roadmapping for Leaders, Managers & IT2 topics
2.1 Building a GenAI Strategy Roadmap
- Identify high-value IT and business use cases (support tickets, monitoring, capacity planning).
- Move from pilots to scaled, IT-integrated workflows.
- Adopt pillars: Vision, Values, Risks, IT adoption readiness.
2.2 Leadership & IT Roles in Governance
- Role of CAIO, CIO, and IT managers in oversight.
- Responsible AI governance: ethics, policies, escalation paths.
- IT change boards & oversight committees to manage risk, bias, and reliability.
03Reimagining Workflows & Operating Models2 topics
3.1 Embedding GenAI into IT Operations
- Service desk transformation: AI-driven incident detection, ticket auto-routing, resolution suggestions.
- Infrastructure automation: self-healing systems, auto-scaling environments, config management.
- Application lifecycle: code review, deployment automation, monitoring with AI agents.
3.2 Workflow Evolution Phases
- Phase 1: AI aids repetitive IT tasks (chatbots for ticket queries).
- Phase 2: Human-AI teams co-manage systems and incidents.
- Phase 3: Agentic swarms handle infrastructure and applications with human oversight.
04Building Trust: Data, Governance & Transparency2 topics
4.1 Establishing Trust Infrastructure
- Secure data ecosystems, ITSM logs, and monitoring pipelines.
- Case study: Morgan Stanley’s rigorous evaluation leading to 98% adoption.
4.2 Ethical, Transparent AI in IT Support
- Responsible frameworks for IT automation and support.
- Transparent AI for incident reports and post-mortems.
05People-Centered Change & Culture3 topics
5.1 Reframing AI as Human Enabler
- Position AI as a partner, not replacement, for IT support and managers.
- Enhance empathy, creativity, and decision-making with AI assistance.
5.2 Change Management Pillars
- Leadership alignment, IT workforce readiness, transparent communication.
- Apply ADKAR model to IT & business adoption.
- Tactics for overcoming resistance and building trust.
5.3 Skills & Engagement Tactics
- Upskilling IT support staff in AI operations, prompting, and monitoring.
- Build “AI Support Guilds” to foster peer-led innovation.
- Case study: Singtel’s AI Academy training 10,000+ employees.
06Challenges, Iteration & Scaling3 topics
6.1 Anticipating Challenges
- Technical debt, data silos, lack of IT buy-in.
- Reliability issues: model drift, hallucination, dependency on vendors.
- Regulatory, audit, and compliance gaps.
6.2 Agile Pilot Learning
- Experimentation in IT workflows with tight feedback loops.
- Celebrate early wins in support automation.
6.3 Metrics, ROI & Long-Game Strategy
- Measure incident resolution time, MTTR, infrastructure uptime, employee satisfaction.
- Scale responsibly with IT–business alignment.
07Practical Prompting for Leaders & IT2 topics
7.1 Prompting Essentials
- Principles of effective prompting for executives and IT staff.
- Use cases: drafting incident responses, generating RCA summaries, infrastructure config templates.
7.2 From Basic to Advanced Prompts
- Simple requests (ticket triage) → structured prompts (incident workflows) → chain-of-thought templates (root-cause analysis).
- Hands-on demonstration: prompting to automate IT and support tasks.
A programme built around your team.
Share your training goals and requirements.