Certified Artificial Intelligence Strategist (CAIS)
5 DaysCertified Artificial Intelligence Strategist (CAIS)
Course Methodology
The course is built around simple, visual frameworks that help participants think about AI in a structured way, without technical complexity. Short presentations are followed by practical exercises where participants map opportunities, prioritize use cases, and sketch AI roadmaps for their own organization. Real case studies from different sectors are used to highlight what works, what fails, and why, making the concepts concrete and relatable. Throughout the course, participants work in small groups to co-create strategy elements, present their ideas, and receive feedback in a safe and collaborative environment.
Course Objectives
By the end of the course, participants will be able to:
- Identify and prioritize AI use cases that align with organizational goals and real pain points
- Assess basic data, people, and process readiness for AI initiatives
- Design a simple AI roadmap, including phases, quick wins, and longer-term initiatives
- Outline governance, risk, and change management elements required for sustainable AI adoption
- Envision and forecast new technical possibilities in the GenAI field in the short and medium-term
Target Audience
This course is designed for professionals and managers from any function who are involved in decisions about innovation, digital transformation or service improvement. It is suitable for non-technical participants who want to understand how to move from experimenting with AI tools to leading structured AI initiatives. The course is relevant for individuals in areas such as operations, HR, finance, strategy, customer experience, policy, data, and program management. It is also valuable for those who act as bridges between business teams and technical or IT teams, and who need a shared language and clear frameworks for AI.
Target Competencies
- AI literacy and strategic thinking
- AI opportunity identification and prioritization
- AI governance and risk awareness
- Change management and stakeholder alignment
Course Outline
- Artificial Intelligence (AI) Basics for Strategic Thinking
- Key AI concepts
- Artificial Intelligence
- Machine Learning
- Generative AI (GenAI)
- How AI creates value
- Cost
- Quality
- Speed
- Experience
- Common patterns of AI use
- Automation
- Decision support
- Personalization
- Search
- Real-world examples of successful and failed AI initiatives
- Key AI concepts
- Finding AI Opportunities
- Customer, citizen, and employee journey mapping to identify pain points
- Writing clear and effective AI use cases using a simple template
- Separating “nice to have” ideas from real business problems
- Creating an AI opportunity map for a specific organizational context
- Evaluating Value, Feasibility, and Risk
- What AI initiatives require
- Data
- People
- Tools
- Partners
- Estimating value
- Impact on cost, time, quality, and experience
- Key risks in AI initiatives
- Data sensitivity
- Fairness
- Security
- Reputation
- Prioritization techniques for quick wins and strategic investments
- What AI initiatives require
- Designing an AI Roadmap and Operating Model
- From pilots to scale
- Planning AI implementation journeys
- Roles and responsibilities across business, IT, and data teams
- Build vs. buy decisions
- In-house development versus external vendors
- Creating an AI roadmap
- From pilots to scale
- Governance, Ethics, and Change
- AI governance
- Rules
- Oversight
- Decision-making structures
- Principles of ethical and responsible AI use
- Communication and training strategies to build trust and reduce resistance
- First 90-day action plan for AI strategy and implementation
- AI governance
Mawred Certificate
Mawred Certificate courses by Al mawred Training & Consulting are designed for those willing to challenge themselves and go the extra distance...
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