Length: 2 Days
The Strategic AI Sourcing Certification (SASC) course equips professionals with advanced skills in AI procurement strategies and market analysis. Developed by Tonex, this certification program offers comprehensive training to excel in sourcing AI technologies effectively.
Learning Objectives:
- Understand the fundamentals of AI procurement.
- Master strategic sourcing techniques tailored for AI.
- Analyze AI market trends and opportunities.
- Implement effective negotiation strategies in AI sourcing.
- Evaluate AI vendors and solutions efficiently.
- Develop actionable plans for integrating AI into business operations.
Audience: Professionals seeking expertise in AI procurement and strategic sourcing, including procurement managers, supply chain professionals, project managers, and business analysts.
Course Outline:
Module 1: Introduction to AI Procurement
- Fundamentals of AI sourcing
- Importance of strategic AI procurement
- Role of AI in modern business operations
- Key challenges in AI procurement
- Regulatory considerations in AI sourcing
- Case studies on successful AI procurement projects
Module 2: Strategic Sourcing Techniques for AI
- Identification of AI sourcing requirements
- Understanding organizational AI needs
- Market research methodologies for AI solutions
- Supplier selection criteria for AI solutions
- Risk assessment in AI sourcing
- Cost-benefit analysis of AI procurement options
Module 3: AI Market Analysis
- Analysis of current AI market trends
- Emerging technologies in AI
- Identification of key AI vendors and offerings
- Benchmarking AI solutions
- Evaluating industry-specific AI applications
- Forecasting future AI market developments
Module 4: Negotiation Strategies in AI Sourcing
- Techniques for negotiating AI contracts
- Establishing negotiation objectives
- Building leverage in AI procurement negotiations
- Handling vendor negotiations effectively
- Mitigating risks through negotiation tactics
- Resolving disputes in AI procurement contracts
Module 5: Vendor Evaluation for AI Solutions
- Evaluation criteria for AI vendors
- Assessing vendor capabilities in AI development
- Technical evaluation of AI solutions
- Evaluating vendor reliability and support
- Considerations for scalability and integration
- Conducting due diligence on AI vendors
Module 6: Integration of AI into Business Operations
- Developing implementation plans for AI solutions
- Identifying AI integration opportunities
- Creating change management strategies for AI adoption
- Training staff for AI implementation
- Monitoring and optimizing AI performance
- Continuous improvement in AI-enabled processes
Exam Domains:
- Fundamentals of AI Sourcing
- Understanding of artificial intelligence and its applications in sourcing.
- Knowledge of basic AI terminology and concepts relevant to sourcing.
- AI Tools and Platforms
- Familiarity with popular AI tools and platforms used in sourcing.
- Ability to assess and compare different AI tools for sourcing purposes.
- Data Management and Analysis
- Understanding of data management principles in the context of AI sourcing.
- Proficiency in data analysis techniques relevant to sourcing tasks.
- AI Sourcing Strategies
- Knowledge of effective strategies for integrating AI into sourcing processes.
- Ability to develop AI-driven sourcing strategies tailored to specific organizational needs.
- Ethical and Legal Considerations
- Awareness of ethical issues related to AI sourcing, including bias and privacy concerns.
- Understanding of relevant legal regulations and compliance requirements.
Question Types:
- Multiple Choice Questions (MCQs):
- Assessing knowledge of AI sourcing terminology and concepts.
- Testing understanding of AI tools and platforms.
- Scenario-based Questions:
- Presenting real-world sourcing scenarios and asking how AI can be applied to solve them.
- Evaluating the ability to identify appropriate AI sourcing strategies.
- Case Studies:
- Analyzing case studies involving AI sourcing implementation.
- Identifying challenges, opportunities, and best practices.
- Practical Exercises:
- Hands-on tasks requiring the use of AI sourcing tools or platforms.
- Demonstrating data analysis skills in sourcing contexts.
Passing Criteria:
- To pass the SASC Training exam, candidates must achieve a minimum score of 70%.
- Each exam domain contributes to the overall score, with varying weights based on importance and complexity.
- Candidates must demonstrate competency across all exam domains, showing proficiency in both theoretical knowledge and practical application of AI sourcing principles.
This structure ensures that certified individuals possess a comprehensive understanding of strategic AI sourcing, including its fundamental concepts, practical applications, ethical considerations, and legal requirements.