Decision-Making Under Uncertainty with AI
Organizations increasingly face situations where important decisions about the development of products, services, or processes need to be made before complete information is available.
During this training, you will learn a practical approach to structuring uncertainty, identifying the most important assumptions, and using customer research, experiments, and artificial intelligence (AI) to make better-informed decisions. You will also have an opportunity to work on one of your own practical initiatives.
Raitis Linde
Work experience: Raitis has worked in the telecommunications, finance, and productivity sectors, as well as led training sessions at conferences and organizations.
Teaching approach: Pays attention to collaboration, participant engagement, and the practical application of knowledge.
Course Target
Developing the skills needed to make more thoughtful business decisions in situations where complete information is not available, including:
- framing the problem before looking for a solution;
- identifying the most critical assumptions and risks;
- selecting the most appropriate research methods for a specific decision;
- using AI as a thinking and analysis partner;
- designing small experiments to reduce uncertainty;
- preparing evidence-based recommendations for stakeholders.
Audience
Anyone who makes important decisions about the development of products or services, including professionals working in:
- product management;
- project management;
- business analysis;
- innovation and digital transformation;
- UX and service design;
- team leadership.
At Course Completion you will be able to
- Clearly define the decision that needs to be made within an organization.
- Distinguish facts from assumptions.
- Choose the most effective way to reduce uncertainty.
- Use AI for customer research, interview analysis, and data synthesis.
- Plan small experiments before making major investments.
- Prepare well-reasoned recommendations for management.
Prerequisites
Previous experience in product, service, or process development is desirable, but this training will be useful for anyone who wants to practice structured decision-making using modern tools and approaches.
Training materials
As Part of the Training, You Will Receive:
- a Decision Case workbook;
- examples of AI prompts for research and synthesis;
- a practical experiment catalogue;
- course presentations;
- examples of practical assignments.
Certification Exam
Not intended.
Course outline
1. Decision-Making Under Uncertainty
- Why do organizations sometimes make poorly grounded decisions?
- Common thinking traps.
- Solution bias.
- Key challenges of the AI era.
2. Effective Problem Framing
- Defining the business problem.
- Stakeholder perspectives.
- Identifying assumptions.
- Desired outcomes.
3. Gathering Evidence
- Interviews.
- Observation.
- Analytics.
- Usability testing.
- AI-powered synthesis.
4. Experiment Design
- Low-cost ways to reduce uncertainty.
- Prototypes.
- Smoke tests.
- Wizard of Oz experiments.
- AI support.
5. Preparing Recommendations
- Building the case for a decision.
- Comparing alternatives.
- Communicating with management.
- Next steps.
If you want to get more information about this course, contact us by phone +371 67505091 or send an e-mail at mrn@bda.lv.
