Preparing Business Data for Responsible AI Use

Proposed five-day professional program. Approximately 25-30 training hours. Final arrangements are confirmed in the written proposal.

Course Overview

Identify data readiness gaps before using organizational information in AI workflows.

This proposed five-day program combines practical case analysis, guided exercises and peer discussion. Participants adapt the course concepts to organizational circumstances and prepare a ai data readiness checklist.

Learning Outcomes

Assess use-case data requirements.

Evaluate data quality and representativeness.

Apply a structured approach to sensitive information and access boundaries.

Develop practical recommendations for documentation and preparation checks.

Prepare and present a ai data readiness checklist.

Who Should Attend

Functional managers, business analysts, AI project coordinators and professionals planning AI-enabled work.

Relevant work experience is recommended. The participant profile, prerequisite knowledge and case complexity are reviewed during planning.

Training Methodology

Facilitated discussion, worked examples, anonymized case analysis, practical exercises, peer review and an applied final assignment.

Learning assessment may include a baseline discussion, review of exercise outputs and a final presentation. Attendance and completion requirements are confirmed in the proposal.

Course Tools and Templates

Use-case data requirements worksheet – proposed exercise document.

Data quality and representativeness worksheet – proposed exercise document.

Sensitive information and access boundaries worksheet – proposed exercise document.

Documentation and preparation checks worksheet – proposed exercise document.

AI data readiness checklist – proposed exercise document.

Delivery Requirements

Classroom, live online and in-house delivery can be arranged by agreement. The trainer, language, venue or platform, timetable and required materials are confirmed in writing.

A laptop may be needed for analytical or planning activities. Software availability, licenses and access requirements are agreed before delivery.

Course Customization

The indicative five-day sequence can be adapted to participant experience, industry context and agreed learning objectives. Final dates, fees, agenda, certificate details and delivery arrangements are confirmed in the written proposal.

Proposed Five-Day Course Outline

Day 1 – Use-case data requirements

Define the business context, assess current practices and clarify the decisions relating to use-case data requirements.

Practical output: Use-case data requirements worksheet

Day 2 – Data quality and representativeness

Interpret representative information and compare practical approaches to data quality and representativeness.

Practical output: Data quality and representativeness worksheet

Day 3 – Sensitive information and access boundaries

Use the course tools in a realistic case focused on sensitive information and access boundaries, documenting assumptions and recommendations.

Practical output: Sensitive information and access boundaries worksheet

Day 4 – Documentation and preparation checks

Review responsibilities, risks and follow-up measures through a practical exercise on documentation and preparation checks.

Practical output: Documentation and preparation checks worksheet

Day 5 – AI data readiness assessment

Integrate the learning through ai data readiness assessment, present the final assignment and propose workplace actions.

Practical output: AI data readiness checklist