Agentic AI Workflows Training Course: Design, Build and Govern AI Agents

Programme Summary

Agentic AI workflows are the subject of this one-week training course for digital transformation leads and heads of function, ending in a pilot agent design pack for one business process. Many organisations run isolated chatbot trials yet lack agents that plan steps, call tools and finish tasks under control. The programme moves from use case selection to agent design, guardrails, testing and launch, applying every tool to a process the participant owns. Mars Training Centre UK delivers this programme on agentic AI workflows to mixed-organisation cohorts.

The Business Case

An agent that acts on systems carries more risk than a tool that only drafts text, so weak scoping shows up as rework, unexplained actions and stalled pilots. Where agentic AI workflows are judged by demonstrations alone, leaders miss failure modes, permission gaps and unmeasured cost. Leaders who define tasks, limits and test evidence together can approve pilots with confidence and explain results to risk and finance colleagues.

• Process Cycle Time: Falls as suitable multi-step tasks are handed to agents with clear completion rules.
• Operational Risk Exposure: Falls as permissions, approvals and logging are set before launch.
• Pilot Conversion Rate: Improves as test sets and success measures decide what moves to production.

Principles and Evidence Base

• NIST AI Risk Management Framework: Its govern, map, measure and manage functions structure the risk work in Sessions 3 and 4.
• ISO/IEC 42001: The standard for AI management systems frames roles, controls and records for agents in Session 4.
• Human-in-the-loop oversight: Approval points and escalation rules guide the workflow patterns built in Session 3.

Intended Participants

• Digital transformation leads who select and sponsor automation pilots.
• Heads of function who own processes that agents would touch.
• Senior managers who must approve agent permissions and review results.
• Product and data leads who work with delivery teams on agent builds.
• Risk and control leaders who challenge how agents are tested.

Typical functions include finance operations, customer service, procurement and public sector service delivery.

Learning Outcomes

1. Participants will be able to evaluate business tasks for suitability to agentic delivery.
2. Participants will be able to construct an agent specification covering goal, memory, tools and limits.
3. Participants will be able to design a multi-step workflow with approval points and fallbacks.
4. Participants will be able to diagnose agent failures from test results and run logs.
5. Participants will be able to prioritise guardrails and permissions against risk.
6. Participants will be able to justify a pilot launch with measures a sponsor can review.

Programme Structure

Day 1: Agentic AI Workflows and Use Case Selection

Which business tasks suit an agent rather than a script or a person?

• Task Suitability Scorecard
• Agent Versus Automation Decision Table
• Process Step Map
• Value and Risk Matrix
• Success Measure Sheet

Day 2: Agent Anatomy and Tool Use

What does an agent need in order to plan and act?

• Goal and Instruction Brief
• Memory and Context Inventory
• Tool Catalogue and Access List
• Planning Loop Diagram
• Agent Specification Template

Day 3: Workflow Design and Orchestration

How are steps, hand-offs and human approvals arranged?

• Single and Multi-Agent Pattern Chart
• Approval Point Map
• Fallback and Escalation Rules
• Data Hand-Off Diagram
• Workflow Blueprint

Day 4: Guardrails, Testing and Governance

How is an agent shown to be safe and reliable enough to launch?

• Permission and Boundary Register
• Test Set and Scenario Library
• Failure Mode Log
• Action Logging and Audit Trail
• Risk Treatment Plan

Day 5: Applying the Tools to One Pilot Agent

Do the selection, design, workflow and control tools support one pilot?

• Applying the Session 1 Task Suitability Scorecard
• Completing the Session 2 Agent Specification Template
• Testing the Session 3 Workflow Blueprint
• Checking the Session 4 Permission and Boundary Register
• Completing the Pilot Agent Design Pack

Methodology

The programme uses a structured exercise method built on anonymised process descriptions, sample agent instructions, run logs and test results from finance, service and public sector settings. Participants work in peer groups on a shared process, challenge each other's agent specifications and receive written facilitator feedback on each exercise set.

• Suggested activity: Scoring five candidate tasks for agent suitability and defending the ranking.
• Suggested activity: Reading a run log to locate where an agent chose a wrong tool.
• Suggested activity: Setting approval points on a workflow that moves money or records.

Capstone Output

Each participant completes a pilot agent design pack for one business process. It holds a task suitability scorecard, an agent specification, a workflow blueprint, a permission register, a test plan and a launch measure sheet. The pack is used at work to brief a sponsor, brief delivery teams and request approval for a controlled pilot.

Frequently Asked Questions

Is agentic AI workflows training suitable for leaders who do not write code?

Yes. Agentic AI workflows training assumes familiarity with business processes and basic AI tools, and builds agent design and testing reasoning step by step without programming.

Which frameworks do agentic AI workflows rest on in this programme?

Agentic AI workflows rest on the NIST AI Risk Management Framework and ISO/IEC 42001, together with human-in-the-loop oversight for approval points.

How is the pack from agentic AI workflows used at work?

You use the pilot agent design pack to brief a sponsor, brief delivery teams and request approval for a controlled pilot.

How does agentic AI workflows training differ from general generative AI training?

Agentic AI workflows training centres on agents that plan, call tools and complete multi-step tasks under control, while general generative AI training centres on prompting and content drafting.