AI Procurement and Vendor Governance Training Course
AI Procurement and Vendor Governance Training Course is designed to equip professionals with advanced knowledge and practical skills for managing the rapidly evolving landscape of Artificial Intelligence (AI) procurement, third-party AI risk management, vendor lifecycle governance, and responsible technology sourcing.
Course Overview
AI Procurement and Vendor Governance Training Course
Introduction
AI Procurement and Vendor Governance Training Course is designed to equip professionals with advanced knowledge and practical skills for managing the rapidly evolving landscape of Artificial Intelligence (AI) procurement, third-party AI risk management, vendor lifecycle governance, and responsible technology sourcing. As organizations increasingly adopt AI solutions, machine learning platforms, generative AI tools, automation systems, and intelligent business applications, effective procurement strategies are essential to ensure security, compliance, transparency, ethical AI adoption, cost optimization, and strategic vendor partnerships. This course explores modern frameworks for evaluating AI vendors, assessing AI capabilities, negotiating AI contracts, managing supplier risks, and establishing governance models aligned with global standards.
The course provides a comprehensive approach to AI supplier management, procurement intelligence, algorithmic accountability, AI governance frameworks, data protection, cybersecurity assurance, regulatory compliance, and vendor performance optimization. Participants will learn how to build sustainable AI procurement strategies, conduct AI due diligence, evaluate vendor maturity, manage contractual obligations, and implement continuous monitoring mechanisms. Through practical exercises and real-world case studies, learners will develop the expertise required to create responsible, scalable, and future-ready AI procurement ecosystems.
Course Duration
5 days
Course Objectives
By the end of this course, participants will be able to:
- Understand AI procurement strategies and emerging intelligent technology sourcing models.
- Develop AI vendor governance frameworks aligned with organizational objectives.
- Apply AI risk assessment methodologies for third-party technology providers.
- Evaluate AI vendors using technical, ethical, security, and compliance criteria.
- Design effective AI procurement policies and governance standards.
- Implement AI supplier lifecycle management practices.
- Conduct AI due diligence and vendor capability assessments.
- Manage AI contracts, service-level agreements (SLAs), and regulatory obligations.
- Apply responsible AI procurement principles for ethical technology adoption.
- Establish AI vendor monitoring and performance measurement frameworks.
- Identify and mitigate third-party AI security and privacy risks.
- Develop strategies for AI cost optimization and procurement innovation.
- Build organizational capabilities for future-ready AI sourcing and governance.
Target Audience
- Chief Procurement Officers (CPOs) and procurement managers
- AI strategy leaders and digital transformation executives
- IT sourcing and technology acquisition professionals
- Vendor relationship managers and supplier governance teams
- Risk management and compliance professionals
- Cybersecurity and data protection officers
- Legal professionals involved in technology contracts
- Government and public sector procurement specialists
Course Modules
Module 1: Fundamentals of AI Procurement and Vendor Governance
- Understanding the AI procurement ecosystem and market trends
- Differences between traditional procurement and AI sourcing
- AI vendor landscape and technology categories
- Strategic importance of AI supplier governance
- Building AI procurement maturity models
- Case Study: Enterprise AI Platform Selection
Module 2: AI Vendor Assessment and Due Diligence
- AI vendor capability evaluation frameworks
- Assessing AI models, infrastructure, and technical architecture
- Reviewing vendor AI maturity levels
- Evaluating data handling and privacy practices
- Conducting responsible AI vendor assessments
- Case Study: Healthcare AI Vendor Review
Module 3: AI Procurement Strategy and Policy Development
- Creating enterprise AI procurement policies
- Aligning AI purchases with business strategy
- Developing AI sourcing roadmaps
- Establishing procurement approval workflows
- Integrating AI governance principles into procurement processes
- Case Study: Financial Services AI Procurement Policy
Module 4: AI Contract Management and Legal Governance
- AI-specific contract requirements
- Managing intellectual property and ownership issues
- AI data usage and licensing agreements
- Defining vendor responsibilities and liabilities
- Negotiating AI service-level agreements (SLAs)
- Case Study: Generative AI Contract Negotiation
Module 5: Third-Party AI Risk Management
- Identifying AI vendor cybersecurity risks
- Managing algorithmic and operational risks
- Conducting AI risk assessments
- Implementing vendor risk scoring models
- Establishing continuous AI risk monitoring
- Case Study: AI Supply Chain Risk Management
Module 6: AI Vendor Performance and Relationship Management
- Measuring AI vendor performance
- Creating AI supplier scorecards
- Managing vendor service quality
- Improving vendor collaboration strategies
- Building long-term AI partnerships
- Case Study: AI Vendor Optimization Program
Module 7: Responsible AI Procurement and Compliance
- Ethical AI sourcing principles
- AI transparency and accountability requirements
- Regulatory compliance considerations
- Bias and fairness evaluation in vendor solutions
- Responsible AI governance practices
- Case Study: Public Sector AI Acquisition
Module 8: Future Trends in AI Procurement and Vendor Governance
- Generative AI procurement strategies
- Autonomous AI systems and vendor challenges
- AI marketplace evolution
- Emerging AI governance standards
- Building future-ready procurement capabilities
- Case Study: AI Innovation Ecosystem Development
Training Methodology
- Interactive lectures and presentations.
- Group discussions and brainstorming sessions.
- Hands-on exercises using real-world datasets.
- Role-playing and scenario-based simulations.
- Analysis of case studies to bridge theory and practice.
- Peer-to-peer learning and networking.
- Expert-led Q&A sessions.
- Continuous feedback and personalized guidance.
Register as a group from 3 participants for a Discount
Send us an email: info@datastatresearch.org or call +254724527104
Certification
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.