FA-0546Agentic & Generative AIAI for Leaders & Business

Adapting to the Future of Technology

AI-aware skills and workplace adaptation for technical professionals

Explore AI-assisted ways of working, assess skill gaps and build a practical learning roadmap for changing technical roles.

Introduction

Why this course

This one-day awareness and planning workshop helps software, DevOps and data professionals evaluate changing tools and ways of working. It combines an accessible survey of AI and automation with practical prompting, AI-assisted workflow examples and a personal learning-roadmap activity.

The focus is on informed adaptation, collaboration and manageable next steps. Emerging technologies are introduced at a conceptual level; the workshop does not promise mastery of AI, cloud infrastructure or new professional roles in a single day.

Learning outcomes

The course teaches participants to:

Discuss how AI and automation can affect software, DevOps and data workflows without treating forecasts as guarantees.
Assess skill gaps and identify relevant learning priorities.
Practise prompt formulation and compare AI-assisted tools for a familiar work task.
Use reflective strategies for adapting to changing tools and collaborative practices.
Create a personal learning roadmap with milestones, peer support and regular self-assessment.

Prerequisites

A foundational understanding of current software development, DevOps, or tech workflows.
A willingness to embrace change and learn new concepts.
Basic knowledge of cloud computing and automation concepts (recommended but not mandatory).

Training outline

7 modules

011. Technology Landscape and Workflow Changes3 topics

Technology change: drivers, adoption choices and uncertainty.
Conceptual survey of AI, machine learning, blockchain, edge computing and quantum computing; distinguish practical adoption from speculative forecasts.
Industry-specific shifts:
- DevOps examples: evaluate where AI-assisted automation may support CI/CD.
- Software-development examples: code generation and AI-assisted programming.
- Data-science examples: automated insights and the need for domain review.

022. Growth Mindset and Adaptability3 topics

The psychology of change: Understanding resistance and overcoming it.
Cultivating curiosity and lifelong learning in tech.
Strategies for resilience: Staying motivated in a constantly shifting landscape.

033. Skills and AI-Tool Literacy3 topics

Technical learning priorities for the participant’s current role:
- AI and ML fundamentals for non-specialists.
- Automation tools for DevOps professionals (e.g., Ansible, Terraform, GitOps).
- Low-code and no-code platforms: useful applications and limitations.
Cross-disciplinary skills: Communication, problem-solving, and collaboration.
Introduction to "prompt engineering" for leveraging AI tools effectively.

044. Changing Ways of Working3 topics

The impact of AI on workflows: From manual tasks to intelligent automation.
Working with AI tools like GitHub Copilot, ChatGPT, and automated monitoring solutions.
Collaborative working models: adapt Agile practices to AI-assisted workflows.

055. Personal Learning Roadmap4 topics

Conducting a personal skills gap analysis.
Build a learning roadmap using suitable self-study platforms and, where relevant, independently evaluated certification pathways; no qualification is awarded or guaranteed by this workshop.
Networking and mentorship: find relevant professional communities.
Planning for adaptability: Setting milestones for regular self-assessment.

066. Illustrative Adaptation Scenarios1 topics

Clearly illustrative scenarios of professionals and teams responding to technology change.

Lessons from failure: Missteps to avoid when navigating change.

077. AI-Aware Toolkit Workshop1 topics

Guided exercises with AI-assisted development or DevOps tools; review output before relying on it.

Collaborating with peers to brainstorm solutions for adapting to specific challenges.

A programme built around your team.

Share your training goals and requirements.