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Most Malaysian companies have moved past AI awareness – staff have experimented with ChatGPT and attended introductory talks. But there is a massive gap between knowing AI exists and actually deploying AI agents that run business tasks automatically.
Teams are still copy-pasting between systems, AI tools are used ad-hoc by individuals, and management has approved AI budgets but nobody knows how to implement. The real gap is deployment – turning AI knowledge into working systems.
This 2-day programme teaches your team to build and deploy AI agents using n8n and ChatGPT API – agents that connect to your actual business tools, make decisions based on your rules, and run without constant human intervention. Every agent is built during the training itself.
Programme Benefits
What Your Team Will Achieve
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Business Objectives
- Identify manual processes within their department suitable for AI agent deployment
- Build and deploy at least 2 functional AI agents using no-code tools
- Connect AI agents to common business tools (email, spreadsheets, messaging platforms, CRM systems)
- Configure AI agents with proper guardrails including input validation, output review, and escalation rules
- Design multi-step AI agent workflows using structured prompt engineering and conditional logic
- Implement PDPA-compliant data handling for AI agent workflows
- Test, debug, and iterate AI agents to improve accuracy before production deployment
- Create a 30-day deployment roadmap with ROI justification for management approval
- Technical Foundations (Beginner-Friendly)
- Set up and configure n8n with ChatGPT API integration
- Use the Credential Store for secure API authentication
- Build conditional branching logic for agent decision-making
- Implement agent memory (short-term and long-term context management)
- Read and interpret n8n execution logs to diagnose failed agent runs
- Apply basic error monitoring, retry logic, and alert escalation
Key Content
Day 1
Time : 9.00am – 5.00pm
Break : 10:15am – 10:30am / 3:15pm – 3:30pm
Lunch : 1.00pm – 2.00pm
Understand AI agents, map your workflows, and build your first working agent
- AI chatbots vs AI agents vs traditional automation - the critical differences
- Why 2025/2026 is the deployment window for Malaysian businesses
- The AI agent stack: LLM + tools + memory + logic
- Live demo: A working AI agent handling a real business task
- Malaysian case studies: AI agents automating onboarding checklists and triaging customer enquiries across WhatsApp, email, and web forms
Activity: Identify 3 processes in your department suitable for AI agent deployment.
Learning Outcomes:- Distinguish between AI chatbots, AI agents, and traditional automation with clear criteria
- Explain the four components of an AI agent stack and how they work together
- Identify at least 3 real Malaysian business scenarios where AI agents can be deployed
- Workshop: Identify your team's top 10 repetitive tasks
- The Agent Readiness Matrix - scoring tasks by automation potential
- Which tasks are agent-ready vs which need human oversight
- Building your department's AI agent deployment shortlist
- Common mistakes: Tasks companies should NOT automate first
Activity: Complete the Agent Readiness Matrix for your department and produce a ranked shortlist of 3–5 deployment candidates.
Learning Outcomes:- Audit their own department's workflows and identify at least 10 repetitive tasks
- Score each task using the Agent Readiness Matrix to determine automation potential, risk, and priority
- Produce a ranked shortlist of 3–5 agent deployment candidates with justification
- Setting up n8n and ChatGPT API (no-code platform walkthrough)
- Anatomy of an AI agent: trigger → process → action → feedback
- Prompt engineering for agents: system instructions, persona, constraints
- Testing & debugging your first agent
Activity: Guided build - Email Triage Agent: incoming email → ChatGPT classifies (urgent/routine/spam) → routes to correct action → drafts response for review.
Learning Outcomes:- Set up and configure n8n with ChatGPT API integration independently
- Build a functional single-task AI agent that triggers, processes, and acts on business data
- Write effective system prompts that define agent persona, boundaries, and output format
- Test and debug an AI agent workflow by running edge-case inputs
- Why unguarded AI agents are a business risk - real failure examples
- Setting boundaries: what your agent can and cannot do
- Input validation, output review gates, and human-in-the-loop design
- PDPA compliance for AI agents: what personal data your agent can process, store, and share
- Data flow mapping: tracing where employee and customer data moves through your agent workflow
- Consent and disclosure requirements when AI agents interact with external parties
Activity: Add guardrails and PDPA-compliant data handling to your Day 1 agent. Create a data flow map showing compliance checkpoints.
Learning Outcomes:- Configure input validation and output review gates to prevent unreviewed agent actions
- Design a human-in-the-loop escalation pathway for tasks exceeding agent authority
- Identify which personal data categories under PDPA are handled by their agent and apply restrictions
- Create a data flow map showing where compliance checkpoints are needed
Day 2
Time : 9.00am – 5.00pm
Break : 10:15am – 10:30am / 3:15pm – 3:30pm
Lunch : 1.00pm – 2.00pm
Multi-step agents, department-specific builds, testing, and your deployment roadmap
- From single-task to multi-step agent workflows
- Connecting agents to Google Sheets, Gmail, Slack/Teams, and CRM systems
- Agent memory: short-term vs long-term context management
- Conditional logic: agents that make decisions based on business rules
- PDPA checkpoint: ensuring data passed between integrated tools complies with consent scope
Activity: Guided build - Report Generation Agent: scheduled trigger → pull data from Google Sheet → ChatGPT summarises → email distribution with conditional routing.
Learning Outcomes:- Build a multi-step AI agent that chains 3 or more actions across different business tools
- Configure conditional branching logic so the agent routes tasks based on business rules
- Implement short-term and long-term memory in an agent workflow
- Verify that data shared between integrated tools stays within PDPA consent boundaries
- HR Agent: Leave processing, onboarding task assignment, policy Q&A
- Operations Agent: Inventory alerts, vendor follow-up, SOP compliance checking
- Finance Agent: Invoice processing, expense categorisation, report compilation
- Customer Service Agent: Ticket triage, FAQ response, escalation routing
Activity: Workshop - Build an agent specific to YOUR department's actual workflow using real business data and processes.
Learning Outcomes:- Select the appropriate agent template for their department's primary workflow challenge
- Customise a department-specific agent using their own real business data and processes
- Configure agent logic to handle at least 3 different scenario branches
- Validate agent outputs against their department's actual quality and accuracy standards
- How to test AI agents before going live (sandbox approach)
- Setting KPIs for AI agents: accuracy rate, time saved, error rate, volume handled
- Monitoring agents in production: execution logs, failure alerts, and what to watch for
- PDPA audit trail: ensuring agent logs meet data retention and access requirements
- Iterating prompts and logic based on real output performance
- Building an agent maintenance schedule your team can follow
Activity: Sandbox test your department agent with edge-case inputs. Define KPIs and set up a weekly agent health check routine.
Learning Outcomes:- Execute a structured sandbox test using edge-case inputs before production deployment
- Define at least 4 measurable KPIs for their deployed agent
- Read and interpret n8n execution logs to diagnose failed agent runs
- Establish a weekly agent health check routine and maintenance schedule
- Verify that agent logging practices comply with PDPA data retention requirements
- Each team/participant builds their 30-day AI agent deployment plan
- Template: Agent Deployment Proposal for management approval
- ROI calculation: how to justify AI agent investment to leadership
- Group presentations: pitch your deployment plan to the room
- Q&A, next steps, and ongoing support options
Activity: Build your complete 30-day deployment roadmap. Present your plan to the group and receive peer feedback.
Learning Outcomes:- Produce a complete 30-day deployment roadmap with weekly milestones, owners, and success criteria
- Calculate projected ROI using time saved, error reduction, and cost metrics
- Present their deployment plan with confidence and justify the business case for management approval
- Identify the next 3 agent deployment opportunities beyond their initial build
Results You Can Expect
AI agent deployment results depend on your workflows and depth of implementation. Here is what participants typically experience:
| Timeframe | What You’ll Achieve |
|---|---|
| Within 1 week | First AI agent from training is deployed into production – handling real tasks like email triage, report compilation, or data routing. |
| Within 2 weeks | Department-specific agent is refined based on real-world outputs. Team identifies additional workflows for agent deployment. |
| Within 30 days | Using the deployment roadmap, teams report measurable workload reduction. KPIs are tracked and management can see ROI. |
| Within 90 days | With consistent execution, organisations typically deploy 3–5 additional agents across departments, creating compounding efficiency gains. |
Key Takeaways
What Participants Walk Away With
Every deliverable is built during the training. Participants leave with working agents and a clear deployment plan.
- 2 Working AI Agents
Built during training and ready to deploy immediately
- 30-Day Deployment Roadmap
With weekly milestones, owners, and success criteria
- Agent Readiness Matrix
10+ department tasks scored for automation potential
- ROI Calculation Worksheet
Customised to justify AI investment to management
- Deployment Proposal Template
Ready to present to leadership for approval
- PDPA Compliance Guide
Agent guardrail checklist and data flow template
- Prompt Engineering Templates
System instruction frameworks for agent personas
- Error-Handling Blueprint
Monitoring setup, retry logic, and alert escalation
Who Should Attend
Designed for Non-Technical Teams That Need AI Agents Working
METHODOLOGY
How We Teach
- 70% Practical Hands-on agent builds
- 30% Conceptual Framework & strategy
- Malaysian Local context & scenarios
- Immediate Agents ready to run
In-House Corporate Training
Customised for Your Organisation
This programme is delivered at your premises or online, fully customised to your industry, workflows, and business objectives. Every hands-on exercise uses your team’s actual processes.
- All agent templates, examples, and activities tailored to your sector and workflows
- 15-minute call with department heads to identify priority workflows for agent deployment
- Hands-on agent builds use your actual business data, tools, and processes
- Module 6 customised to your HR, operations, finance, or service workflows
- All agents include data privacy guardrails aligned with Malaysian PDPA requirements
- We handle all grant application paperwork and e-TRiS guidance
- Delivered on dates that suit your team’s availability
- Follow-up consultation to ensure successful agent deployment
Available Formats
- In-House Corporate
Delivered at your premises, customised to your workflows and team. Fully HRD Corp claimable. - 1-to-1 ExecutivePrivate sessions for senior leaders or department heads who need focused, personalised agent deployment guidance.
- Online (Zoom)
Live online sessions with screen sharing, breakout rooms, and full hands-on support.
Frequently Asked Questions
What are AI agents and how are they different from chatbots?
AI agents are autonomous workflows that can trigger actions, make decisions, and interact with multiple business tools without constant human input. Unlike chatbots that only respond to conversations, AI agents can monitor emails, classify data, route tasks, generate reports, and execute multi-step processes automatically. This training teaches you to build agents that run your business tasks on autopilot.
Do I need coding or technical experience to attend?
No. This programme is designed specifically for non-technical business professionals. All AI agents are built using n8n, a visual no-code platform where you connect nodes by dragging and dropping. The trainer guides every step, and no programming knowledge is required.
What tools are used in this training?
Participants use n8n (open-source visual workflow automation), ChatGPT via the OpenAI API (for AI reasoning and language processing), Google Workspace (Sheets, Gmail, Drive, Forms), and messaging platforms (WhatsApp, Telegram, Slack/Teams). All tools are selected for accessibility by non-technical users.
Is this training HRD Corp claimable?
Yes. This 2-day AI Agent training is fully HRD Corp claimable. Ommtech Digital Marketing Academy is an HRD Corp-approved training provider. We provide full documentation support and guide your HR team through the e-TRiS claim process.
What will participants actually build during the training?
Participants build at least 2 working AI agents during the training. Day 1 includes an email triage agent that classifies and routes emails automatically. Day 2 includes a department-specific agent customised to participants’ actual workflows – such as HR leave processing, operations reporting, finance invoice handling, or customer service ticket routing.
What is n8n and why is it used in this training?
n8n is an open-source visual workflow automation platform. It allows you to build complex AI agent workflows by connecting nodes (triggers, actions, conditions) without writing code. It integrates with hundreds of business tools including Google Workspace, Slack, email, CRMs, and AI models like ChatGPT. It is used in this training because it is accessible for non-technical users while being powerful enough for production deployment.
How does this training handle data privacy and PDPA compliance?
PDPA compliance is integrated throughout the programme, not treated as a single module. Participants learn data flow mapping, consent requirements when agents interact with external parties, how to restrict personal data categories in agent workflows, and PDPA-compliant logging and audit trail practices. Every hands-on agent build includes compliance checkpoints.
What results can I expect after the training?
Participants leave with at least 2 working AI agents ready for deployment, a 30-day deployment roadmap with ROI justification, and all templates and frameworks needed for continued implementation. Most organisations begin deploying their first agent within the first week after training, with measurable workload reduction visible within 30 days.
Can this training be customised for our industry?
Yes. We conduct a pre-training needs assessment and customise Module 6 (Department-Specific Agent Templates) to your actual business workflows. Whether you are in manufacturing, professional services, retail, healthcare, education, or any other sector, all hands-on exercises use your real processes and data.
What is the difference between this and the n8n Automation Mastery programme?
n8n Automation Mastery focuses on general workflow automation – connecting systems, automating data flows, and building scheduled workflows. AI Agent Deployment goes further by teaching participants to build autonomous AI agents that can reason, classify, decide, and act using ChatGPT as the intelligence layer. Think of n8n Mastery as automation fundamentals, and AI Agent Deployment as adding AI decision-making on top.
How many participants can attend per session?
We recommend up to 20 participants per session for optimal hands-on engagement. For larger teams, we customise with breakout groups and additional facilitators.
What do participants need to bring?
Each participant needs a laptop with internet access. All accounts and tool access (n8n, ChatGPT API) will be set up during Module 3 of the training.
Is this training available online?
Yes. We offer both in-person and online formats. In-person provides the best hands-on experience, but we also deliver effective online sessions via Zoom with screen sharing, breakout rooms, and live implementation support.
Is there a certificate?
Yes. Assessment is practical and project-based throughout both days. Upon successful completion, participants receive an Ommtech Digital Marketing Academy Certificate of Completion – no written examination is required.