Course overview
Agentic AI for Business and Organisations provides practical training in AI agents, intelligent automation, enterprise knowledge systems, AI-powered workflows and multi-agent technologies. Participants learn how to identify business processes suitable for AI automation, design AI-agent architectures, connect agents to organisational knowledge and applications, automate workflows, implement human-in-the-loop controls, and establish responsible AI governance. The programme is suitable for corporate, government, NGO and development-sector organisations seeking to integrate modern AI capabilities into their operations.
The course moves beyond conventional generative AI and chatbots to explore how organisations can use AI agents and intelligent workflows across operations, finance, HR, customer service, research, data analysis, project management, ICT and decision support.
Participants will work with modern AI platforms, agent-building tools, automation technologies, APIs, enterprise knowledge bases and workflow systems to develop practical organisational use cases.
Course objectives
- Understand the principles and architecture of Agentic AI. Distinguish traditional automation, chatbots, Generative AI and AI agents. Identify organisational processes suitable for AI-agent automation. Design AI-powered business workflows. Build practical AI agents using modern no-code, low-code and developer tools. Connect AI agents to organisational documents and knowledge bases. Implement Retrieval-Augmented Generation (RAG) for enterprise knowledge. Enable AI agents to use tools, APIs and business applications. Design human-in-the-loop approval and escalation processes. Apply AI agents to research, reporting and data analysis. Explore multi-agent systems and collaborative AI agents. Evaluate agent accuracy, reliability and performance. Identify security, privacy and data-protection risks. Develop organisational AI-agent governance frameworks. Create an Agentic AI adoption and implementation roadmap.
Who should attend
Executives and senior managers
ICT and digital-transformation teams
Business-process managers
Data analysts and data scientists
IT professionals
Software developers
Project and programme managers
Researchers and policy analysts
Monitoring and evaluation professionals
Finance and audit professionals
HR professionals
Knowledge-management teams
Customer-service teams
Government and public-sector professionals
NGO and development-sector professionals
Consultants and technology managers
Course content
- Module 1: Introduction to Agentic AI What is Agentic AI? Evolution from automation to intelligent agents Generative AI vs AI agents AI copilots vs autonomous agents Agent capabilities and limitations Organisational opportunities
- Module 2: AI Agent Architecture LLMs Instructions and prompts Reasoning and planning Memory Tools APIs Knowledge retrieval Actions Agent orchestration Human oversight
- Module 3: Identifying Organisational AI-Agent Use Cases Business-process mapping Identifying repetitive workflows Knowledge-intensive processes Decision-support processes Research workflows Document workflows Customer-service workflows Prioritising AI-ag
- Module 4: Designing Intelligent Workflows Workflow decomposition Trigger → reasoning → action Conditional workflows Agent decision points Approvals Escalation Human-in-the-loop design Error handling
- Module 5: Enterprise Knowledge and RAG Organisational knowledge bases Document ingestion Chunking Embeddings Vector databases Retrieval-Augmented Generation Grounded responses Document-based AI assistants
- Module 6: AI Agents for Business Productivity Practical use cases involving: Email Meetings Documents Reports Research Summarisation Information extraction Scheduling Task management Executive briefings
- Module 7: AI Agents for Data and Business Intelligence Natural-language data analysis Automated data exploration Report generation KPI monitoring Anomaly detection AI-assisted dashboards Automated management reports Connecting agents to analytical workfl
- Module 8: AI Agents and Business Process Automation Workflow automation API integration Forms and approvals Notifications Document processing Automated decision workflows Enterprise system integration
- Module 9: Microsoft AI Agent Ecosystem Practical exposure to relevant Microsoft technologies such as: Microsoft Copilot Copilot Studio Microsoft 365 Power Automate SharePoint Teams Power BI Dataverse Business applications
- Module 10: Multi-Agent Systems What are multi-agent systems? Agent roles Agent collaboration Task delegation Supervisor agents Specialist agents Agent orchestration Multi-agent business workflows
- Module 11: Building and Deploying AI Agents No-code/low-code agent development Developer-based agent development APIs Tool integration Authentication Deployment Testing Monitoring Version management
- Module 12: AI Agent Security and Governance Data privacy Access control Prompt injection Data leakage Excessive agent permissions Hallucinations Human oversight Auditability Responsible AI Governance policies
- Module 13: Evaluating AI Agents Accuracy Reliability Grounding Task completion Response quality Tool-use accuracy Failure analysis Evaluation datasets Monitoring agent performance
- Module 14: Agentic AI Strategy for Organisations AI maturity assessment Identifying strategic use cases Build vs buy AI operating models Workforce considerations Change management Governance ROI and business value Implementation roadmap
- Module 15: Capstone Organisational AI-Agent Project Participants design and prototype an AI-agent solution for a real organisational workflow. Examples: HR recruitment assistant Finance document-processing agent Research assistant Customer-service agen