AI Agents and Low-Code AI Automation – AI Agents Lab: practical creation of agents, workflows and business automations

Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

Understand the AI agent role - You will learn when an AI agent creates more value than a chatbot or a basic automation, so you can choose the right approach for a specific process in your organization.

Select the right pilot process - You will learn how to map a process step by step and assess time, cost, risk, and business impact, so you can pick a pilot use case with clear automation potential.

Design a useful agent - You will practice defining the agent’s goal, users, scenarios, operating rules, and escalation paths, so you can build an assistant that supports real team workflows.

Explore low-code tools - You will compare tools such as Copilot Studio, Power Automate, Make, Zapier, and n8n, making it easier to match the platform to your process, budget, and integrations.

Connect AI with workflows - You will learn how to link an AI agent with approvals, tickets, reports, and notifications, helping you shorten handling time and reduce manual handoffs between people.

Organize data and knowledge - You will see how to prepare documents, knowledge bases, and data sources for an AI agent, so it can respond using current information instead of inconsistent or duplicate files.

Reduce delivery risk - You will learn safe data handling rules, access control, approval paths, and ways to limit AI hallucinations, so you can deploy solutions with stronger quality and governance.

Build an implementation plan - You will leave with a concept for your own solution, defined KPIs, a test scope, and a pilot plan, making it easier to justify deployment and schedule further improvements.

Training programme

1. Introduction to AI agents and process automation

what AI agents are and how they differ from chatbots and traditional automations,
the role of AI agents in a modern organization,
what the low-code/no-code approach is and when it is worth using,
examples of AI agent applications in sales, HR, administration, finance, customer service, IT, and operations,
business benefits: time savings, work standardization, error reduction, and better access to information.

2. Identification of processes for automation

how to identify processes that are worth automating,
analysis of repetitive, time-consuming and manual tasks,
mapping the process step by step,
defining inputs, outputs, decisions, exceptions and responsibilities,
assessment of automation potential: time, cost, risk, frequency and impact on the business,
selection of the process for the pilot.

3. Designing an AI agent

defining the purpose, scope and role of the AI agent,
identifying the user group and use scenarios,
designing the dialogue, instructions and operating principles of the agent,
creating the knowledge base and data sources for the agent,
establishing limitations, permissions and escalation rules,
designing the user experience: simplicity, usability and clear communication.

4. Low-code/no-code tools for creating agents and automation

overview of tools for building AI agents and process automation,
Copilot Studio, Power Automate, Make, Zapier, n8n and other no-code/low-code platforms,
integration of AI agents with forms, spreadsheets, email, Teams, SharePoint, CRM and other systems,
when to choose simple automation, and when an AI agent,
limitations of low-code/no-code tools and situations requiring IT support.

5. Building a simple AI agent – practical workshop

configuration of a basic AI agent,
creating system instructions and conversation scenarios,
adding knowledge sources and documents,
testing the agent's responses to sample user questions,
improving instructions, tone of communication and operating logic,
preparing the agent for use in a selected business process.

6. Business process automation

creating simple workflows without coding,
automation of notifications, approvals, requests, reports and reminders,
connecting an AI agent with process automation,
examples: handling inquiries, generating responses, classifying requests, creating summaries, assigning tasks,
designing rules, conditions and actions in the process,
handling exceptions and errors in automations.

7. Data, integrations and the agent's knowledge base

how to prepare data and documents for working with an AI agent,
structuring company knowledge,
working with files, websites, knowledge bases and internal systems,
updating knowledge sources and maintaining the quality of responses,
rules for granting access to data,
the most common data-related problems: outdatedness, inconsistency, duplicates, lack of an information owner.

8. Security, compliance and quality control

what data should not be provided to AI agents,
protection of personal data, confidential information and trade secrets,
user permissions and access control,
verification of responses generated by the agent,
AI hallucinations and ways to reduce the risk of incorrect responses,
activity logging, human oversight and approval paths,
principles of responsible deployment of AI agents in the organization.

9. Testing, deployment and optimization of the AI agent

plan of functional and business tests,
testing of typical and exceptional scenarios,
collecting feedback from users,
measurement of the effectiveness of the agent and automation,
KPI: handling time, number of automatically handled cases, quality of responses, reduction of errors,
iterative improvement of the agent and development of subsequent functions,
preparation of the organization for deployment.

10. Final workshop: design of your own AI solution

selection of the participants' business process,
designing the concept of an AI agent or automation,
defining the goal, users, input data and results,
preparing a process map and operating scenarios,
defining risks, limitations and security principles,
developing a pilot implementation plan.

What are the prerequisites for participating in the training?

Understanding of work processes - You should understand how core processes work in your area, so you can identify repetitive tasks, exceptions, responsibilities, and realistic opportunities for automation.

Confidence with office tools - You should be comfortable using email, spreadsheets, forms, and online documents, because the training relies on common business tools used across everyday workflows.

Process-oriented thinking - You should be able to describe a task as a sequence of steps, decisions, and outcomes, since you will map workflows and define the logic behind agents and automations.

Readiness for hands-on work - You should be ready to test solutions on your own, refine instructions, and review results, because the training is practical and built around workshop-based exercises.