CAIM®
Certified Artificial Intelligence Manager
Lead AI Strategy. Govern Responsibly. Manage Risk. Deliver Enterprise Value.
Artificial Intelligence is moving rapidly from experimentation to enterprise-wide adoption.
Lead AI Strategy. Govern Adoption. Deliver Outcomes.
Advanced Manager Level
For ai leaders, managers and decision-makers
Vendor-Neutral
Skills and knowledge that apply across platforms and tools
Global Recognition
Recognized internationally across industries and regions
Digital Credential
Shareable, verifiable credential and certificate
What You Will Learn
The CAIM® Body of Knowledge is organized into eight integrated management modules.
AI Operating Models & Team Design
AI Portfolio & Investment Management
AI Governance, Policy & Compliance
Risk, Ethics & Trustworthy AI
AI Program & Vendor Oversight
Change Management & AI Adoption
AI Value & Performance Measurement
Why CAIM® Stands Out
- AI Strategy
- Investment & Portfolio Management
- Generative AI
- Enterprise Architecture
- AI Agents
- Program Management
- Responsible AI
- Cybersecurity
- Risk Management
- MLOps & LLMOps
- Workforce Transformation
- Executive Leadership
Career Opportunities
CAIM® can support professional development toward roles such as:
- Artificial Intelligence Manager
- AI Program Manager
- AI Governance Manager
- Responsible AI Manager
- AI Risk Manager
- AI Transformation Manager
- Generative AI Program Manager
- Enterprise AI Manager
- Data and AI Manager
- AI Product Manager
- AI Operations Manager
- Technology Manager
- Digital Transformation Manager
- AI Strategy Consultant
- AI Governance Consultant
- Technology Risk Manager
- Director of Artificial Intelligence
- Director of Data and AI
- Director of AI Governance
- Head of AI Programs
- Head of Responsible AI
- Enterprise AI Leader
- Technology Director
- AI Transformation Director
Actual role eligibility will depend on employer requirements, experience, education, technical background, and leadership experience.
View Career Outlook
About the credential
Become an Artificial Intelligence professional the market trusts.
Organizations now need leaders who can do more than understand AI technologies. They need professionals who can develop AI strategy, evaluate investments, govern AI responsibly, manage security and risk, lead implementation, oversee Generative AI and agentic systems, and translate AI initiatives into measurable organizational value.
The Certified Artificial Intelligence Manager (CAIM®) is an advanced professional certification designed for technology managers, AI leaders, digital transformation professionals, consultants, governance specialists, program managers, risk professionals, and decision-makers responsible for leading Artificial Intelligence initiatives within modern organizations.
Offered by the:
Advanced Manager level — Three-year certification cycle with continuing professional education
CAIM®
Why Earn the CAIM® Certification?
AI adoption is no longer only a technical issue.
Successful enterprise AI requires professionals who can align technology with business strategy, establish governance, evaluate risks, oversee vendors, lead cross-functional teams, manage investments, address regulatory obligations, and ensure that AI systems produce sustainable value.
The CAIM® certification is designed to demonstrate that you possess the advanced knowledge and professional judgment required to manage these responsibilities.
CAIM® helps you demonstrate competency in:
- Enterprise AI strategy
- AI leadership and organizational alignment
- AI maturity and readiness assessment
- AI investment and business case development
- AI portfolio management
- Generative AI and foundation-model strategy
- Large Language Model governance
- Retrieval-Augmented Generation
- AI agent and intelligent automation governance
- Enterprise AI architecture
- AI technology and vendor selection
- AI program and project management
- Responsible AI
- AI governance and accountability
- Privacy and regulatory compliance
- AI cybersecurity
- Enterprise AI risk management
- MLOps and LLMOps governance
- AI lifecycle management
- Workforce transformation
- Change management
- Executive communication
- AI performance and value realization
CAIM®
Who Should Earn CAIM®?
The CAIM® certification is designed for experienced professionals who lead, manage, govern, oversee, advise, or make decisions about Artificial Intelligence and technology-enabled transformation.
CAIM® Is Especially Relevant For:
- Artificial Intelligence Managers
- AI Program Managers
- AI Governance Managers
- Responsible AI Managers
- AI Risk Managers
- AI Transformation Managers
- Generative AI Program Managers
- Technology Managers
- Information Technology Managers
- Information Systems Managers
- Data and Analytics Managers
- Cybersecurity Managers
- Digital Transformation Leaders
- Technology Risk Managers
- Data Governance Managers
- Enterprise Architects
- Product Managers
- Program Managers
- Project Managers
- Innovation Managers
- Technology Consultants
- AI Strategy Consultants
- Business Transformation Managers
- Technology Directors
- Heads of AI
- Directors of Data and AI
- Directors of AI Governance
- Chief Information Office professionals
- Chief Technology Office professionals
- Chief Data Office professionals
- Chief AI Office professionals
- Senior technical professionals transitioning into management
CAIM®
Who Is CAIM® Designed For?
CAIM® is particularly valuable if you:
- Lead or support enterprise AI initiatives
- Manage technology or digital transformation programs
- Evaluate AI investments
- Oversee AI vendors or cloud platforms
- Manage data, cybersecurity, or technology risk
- Participate in AI governance committees
- Develop AI policies or controls
- Lead AI implementation projects
- Oversee Generative AI adoption
- Manage AI-enabled products or services
- Advise executives on AI strategy
- Need to understand AI risk without becoming a model developer
- Are progressing from technical AI competency into management
CAIM®
CAIM® Course Learning Outcomes
Upon successful completion of the Certified Artificial Intelligence Manager (CAIM®) course, participants will be able to:
-
01
Develop and Align Enterprise AI Strategy
Formulate AI strategies that align with organizational goals, business priorities, technology capabilities, digital transformation initiatives, and measurable enterprise outcomes.
-
02
Evaluate AI Investments, Business Cases, and Portfolio Priorities
Assess AI opportunities, costs, benefits, feasibility, ROI, total cost of ownership, organizational readiness, and strategic value to support informed investment and prioritization decisions.
-
03
Manage Enterprise AI Technologies and Architecture Decisions
Evaluate AI platforms, cloud services, foundation models, Large Language Models, Retrieval-Augmented Generation, AI agents, data architectures, integration models, and emerging technologies from a managerial perspective.
-
04
Lead AI Programs, Projects, Vendors, and Implementation Initiatives
Plan and oversee AI programs, allocate resources, manage stakeholders, evaluate vendors, coordinate cross-functional teams, control implementation risks, and support successful enterprise adoption.
-
05
Establish Responsible AI, Governance, Privacy, and Compliance Practices
Design and apply governance mechanisms addressing fairness, accountability, transparency, explainability, privacy, human oversight, regulatory obligations, documentation, and responsible AI principles.
-
06
Manage AI Security, Cybersecurity, and Enterprise Risk
Identify, assess, prioritize, and mitigate AI-related cybersecurity, model, data, operational, third-party, reputational, legal, and strategic risks.
-
07
Oversee AI Operations, MLOps, LLMOps, and Lifecycle Performance
Manage AI deployment, model inventories, monitoring, performance, drift, change control, incident response, maintenance, continuous improvement, and model retirement.
-
08
Lead AI-Enabled Organizational Transformation and Value Realization
Guide workforce transformation, human-AI collaboration, AI literacy, change management, stakeholder engagement, executive communication, adoption, and measurement of enterprise AI value.
CAIM®
CAIM® Certification Testing Outcomes — Skills and Competencies Tested
The Certified Artificial Intelligence Manager (CAIM®) certification assessment is designed to evaluate advanced managerial knowledge, professional judgment, strategic thinking, governance capability, risk awareness, and enterprise decision-making across the complete AI management lifecycle.
Candidates are expected to demonstrate competency in the following eight certification domains:
CAIM®
The CAIM®–IBACTP® Advanced Management Competency Model
The CAIM®–IBACTP® Advanced Management Competency Model is structured around eight integrated management domains.
These domains define the capabilities expected of professionals responsible for enterprise Artificial Intelligence leadership.
1. Strategic AI Leadership
Develop AI strategies that align with organizational goals, operating models, competitive priorities, technology capabilities, and enterprise transformation objectives.
2. AI Investment and Value Management
Evaluate AI opportunities, develop business cases, prioritize investments, assess total costs and benefits, manage portfolios, and measure organizational value.
3. AI Technology and Architecture Management
Evaluate AI architectures, platforms, foundation models, LLMs, RAG environments, AI agents, cloud services, integration approaches, and emerging technology options.
4. AI Program and Implementation Management
Lead AI programs, projects, resources, vendors, stakeholders, implementation activities, adoption initiatives, and benefits realization.
5. Responsible AI and Governance
Establish governance, accountability, ethical controls, privacy requirements, human oversight, explainability, compliance, and AI assurance.
6. AI Security and Enterprise Risk
Manage cybersecurity, adversarial AI, model risk, data risk, third-party risk, operational risk, reputational risk, and organizational exposure.
7. AI Operations and Lifecycle Governance
Oversee production AI, MLOps, LLMOps, monitoring, performance management, change controls, incident response, continuous improvement, and model retirement.
8. AI Transformation and Executive Leadership
Lead workforce transformation, organizational adoption, AI literacy, human-AI collaboration, change management, executive communication, and strategic decision-making.
CAIM® Management Progression
Analyze → Prioritize → Govern → Decide → Lead → Measure → Improve
CAIM®
Applied CAIM® Capstone Project
Candidates choosing the project-based assessment pathway complete a comprehensive:
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CAIM® Enterprise Artificial Intelligence Management Capstone (Instructor-Led Training)
The capstone demonstrates the candidate's ability to integrate strategy, governance, security, implementation, transformation, and value management.
Capstone Part 1: Enterprise AI Strategy, Investment, and Roadmap
Candidates:
- Define organizational objectives
- Assess AI maturity
- Identify AI opportunities
- Prioritize use cases
- Develop business cases
- Evaluate technology alternatives
- Define sourcing strategies
- Establish investment priorities
- Create an enterprise AI roadmap
Expected Outcome
A strategically aligned and financially defensible enterprise AI initiative or portfolio.
Capstone Part 2: Governance, Security, Risk, and Responsible AI
Candidates:
- Establish AI governance
- Define decision rights
- Assess enterprise AI risks
- Address cybersecurity
- Evaluate privacy
- Assess bias and fairness
- Establish explainability requirements
- Define human oversight
- Address compliance
- Recommend risk controls
Expected Outcome
A structured governance and risk-management framework for responsible enterprise AI.
Capstone Part 3: Implementation, Transformation, and Value Realization
Candidates:
- Develop implementation strategy
- Establish program governance
- Define resource requirements
- Establish MLOps/LLMOps oversight
- Develop workforce strategy
- Plan change management
- Establish KPIs
- Define monitoring requirements
- Measure value
- Present recommendations to executives
Expected Outcome
An executive-level AI implementation and transformation plan designed to generate sustainable organizational value.
CAIM®
Option 2 — Applied CAIM® Capstone Project
Candidates may demonstrate advanced competency through the CAIM® Enterprise Artificial Intelligence Management Capstone Project.
The project evaluates:
- Strategic AI planning
- Organizational readiness
- AI investment
- Business value
- Technology selection
- Governance
- Cybersecurity
- Responsible AI
- Risk management
- Implementation
- Workforce transformation
- Executive communication
- Value realization
CAIM®
CAIM® Certification Competency Standard
CAIM® is designed to assess more than theoretical understanding.
Successful candidates should demonstrate the ability to apply advanced managerial judgment to realistic enterprise AI scenarios.
The CAIM® assessment framework emphasizes the following progression:
Understand → Analyze → Evaluate → Prioritize → Govern → Decide → Lead → Measure
Candidates may be assessed through scenario-based examination questions, applied management exercises, or the CAIM® Enterprise Artificial Intelligence Management Capstone Project.
The assessment is designed to determine whether a candidate can make defensible professional decisions involving:
- AI strategy
- Technology investment
- Enterprise architecture
- Governance
- Responsible AI
- Cybersecurity
- Risk
- Implementation
- Operations
- Workforce transformation
- Business value
- Executive leadership
CAIM®
What CAIM® Validates
Earning the Certified Artificial Intelligence Manager (CAIM®) designation demonstrates that a professional has been assessed against an advanced competency framework covering both the technological and managerial dimensions of enterprise Artificial Intelligence.
CAIM® validates the candidate's ability to:
This advanced competency profile differentiates CAIM® from practitioner-level AI certifications by emphasizing the ability to lead and govern AI at the organizational level, not simply using or developing AI technologies.
- Strategize AI
- Evaluate AI Investments
- Select and Govern Technology
- Lead AI Programs
- Manage AI Security and Risk
- Establish Responsible AI Governance
- Oversee AI Operations
- Lead Organizational Transformation
- Deliver and Measure Enterprise Value
Assessment
Flexible CAIM® Assessment Options
CAIM® provides two advanced assessment pathways.
Candidates may demonstrate competency through either:
Assessment
Option 1 — CAIM® Certification Examination
The certification examination is designed to assess advanced managerial knowledge and professional judgment.
CAIM®
Recommended Prerequisites
CAIM® is an advanced managerial-level certification.
Candidates should preferably possess relevant professional experience in one or more areas such as:
A bachelor's degree or equivalent professional education is beneficial but may not be mandatory where a candidate possesses substantial professional experience.
The Certified Artificial Intelligence Professional (CAIP®) may serve as a recommended pathway into CAIM®.
Candidates who do not hold CAIP® should possess equivalent foundational knowledge of:
- Artificial Intelligence
- Information Technology
- Information Systems
- Data and Analytics
- Cybersecurity
- Digital Transformation
- Project or Program Management
- Technology Risk
- Enterprise Architecture
- Technology Consulting
- Innovation Management
- AI Governance
- Artificial Intelligence
- Machine learning
- Generative AI
- Large Language Models
- Data concepts
- AI security
- Responsible AI
- Enterprise technology
CAIM®
Recommended Training Duration · Certification Validity · 3 Years · Continuing Professional Education
Recommended Training Duration
The CAIM® program is designed as a comprehensive:
Certification Validity
The recommended CAIM® certification cycle is:
3 Years
Credential holders should maintain current professional competency throughout the certification period.
Continuing Professional Education
The recommended recertification requirement is:
CAIM®
40 CPE Credits Every Three Years
Qualifying professional development may include:
- Advanced AI courses
- AI governance training
- Cybersecurity education
- Executive education
- Conferences
- Workshops
- Academic coursework
- Teaching
- Research
- Publications
- Professional presentations
- AI project leadership
- Standards activities
- Professional service
- Advanced certifications
Where it leads
Professional Designation
Successful candidates earn the advanced professional designation:
CAIM®
ISO and International Framework Alignment
The CAIM® Body of Knowledge is designed with consideration of internationally recognized standards and frameworks relevant to AI management, risk, cybersecurity, privacy, governance, and professional certification.
ISO/IEC 42001 — Artificial Intelligence Management Systems
CAIM® incorporates management concepts that support understanding of AI management systems, governance structures, accountability, organizational objectives, risk management, performance monitoring, and continual improvement.
ISO/IEC 23894 — Artificial Intelligence Risk Management
CAIM® addresses concepts related to:
- AI risk identification
- Risk analysis
- Risk evaluation
- Risk treatment
- Risk monitoring
- Communication
- Organizational AI risk management
ISO/IEC 22989 — Artificial Intelligence Concepts and Terminology
Provides internationally standardized AI terminology and conceptual foundations relevant to enterprise AI management.
ISO/IEC 27001 — Information Security Management Systems
Supports CAIM® knowledge areas involving:
- Information security governance
- AI security controls
- Access management
- Risk assessment
- Security monitoring
- Incident response
- Business resilience
ISO/IEC 27701 — Privacy Information Management
Supports privacy management concepts relevant to enterprise AI, including:
- Personally identifiable information
- Data-processing accountability
- Privacy governance
- Organizational controls
- Responsible use of personal information
ISO 31000 — Risk Management
Supports enterprise approaches to:
- Risk principles
- Risk governance
- Risk assessment
- Risk treatment
- Risk ownership
- Monitoring and communication
ISO/IEC 17024 — Certification of Persons
CAIM® credentialing processes should be designed with consideration of internationally recognized personnel-certification principles addressing:
- Defined competencies
- Impartiality
- Assessment reliability
- Certification decisions
- Examination security
- Recertification
- Professional conduct
- Appeals
- Complaints
- Continuous improvement
NIST AI Risk Management Framework
CAIM® includes management concepts relevant to the NIST AI RMF approach for governing, mapping, measuring, and managing AI risks.
Candidates learn how structured AI risk frameworks can support organizational decision-making.
Artificial Intelligence
Global, Vendor-Neutral Focus
CAIM® is designed as an internationally relevant, vendor-neutral professional certification.
The Body of Knowledge focuses on transferable enterprise AI management capabilities rather than one specific:
This enables CAIM® competencies to be applied across diverse organizational and technology environments.
- Cloud provider
- AI vendor
- Foundation model
- Software platform
- Programming language
- Consulting methodology
Artificial Intelligence
Global Recognition and Professional Portability
CAIM® is designed to support international professional relevance and career portability.
Its competency framework addresses management capabilities that are transferable across countries, industries, organizational structures, and technology environments.
The certification is intended to help credential holders demonstrate advanced AI management competency to employers, clients, professional peers, and organizational stakeholders.
Recognition or acceptance of any professional certification remains subject to the requirements of individual:
Accordingly, CAIM® should be positioned as a globally relevant professional credential, while avoiding unsupported claims of universal employer acceptance.
- Employers
- Government agencies
- Educational institutions
- Professional organizations
- Regulators
- Licensing authorities
- Other organizations
CAIM®
Accreditation and Credentialing Alignment
The CAIM® certification framework is designed with consideration of professional credentialing and personnel-certification principles associated with:
The CAIM® certification program should incorporate practices involving:
Formal accreditation by any specific body should only be stated after such accreditation has officially been granted.
- ISO/IEC 17024
- ANSI National Accreditation Board (ANAB)
- National Commission for Certifying Agencies (NCCA)
- Institute for Credentialing Excellence (I.C.E.)
- International conformity-assessment practices
- Professional personnel-certification best practices
- Job Task Analysis
- Defined eligibility requirements
- Validated Body of Knowledge
- Examination blueprint
- Subject Matter Expert involvement
- Psychometric review
- Examination security
- Identity verification
- Impartial certification decisions
- Appeals processes
- Complaints procedures
- Conflict-of-interest controls
- Professional code of conduct
- Continuing Professional Education
- Recertification
- Certification verification
- Periodic program review
- Continuous improvement
CAIM®
CAIM® Assessment Pathways
CAIM®
CAIP® vs. CAIM®
| Area | CAIP® | CAIM® |
|---|---|---|
| Level | Professional | Advanced / Manager |
| Focus | Applied AI competency | Enterprise AI leadership |
| AI Strategy | Foundational | Advanced |
| Machine Learning | Applied understanding | Management oversight |
| Generative AI | Applied use | Enterprise adoption |
| AI Architecture | Working knowledge | Strategic decision-making |
| Governance | Awareness and application | Leadership accountability |
| AI Security | Threat and control awareness | Enterprise risk management |
| Vendor Management | Limited | Advanced |
| AI Investment | Basic business value | Portfolio and ROI management |
| MLOps/LLMOps | Operational understanding | Governance and oversight |
| Workforce Transformation | Awareness | Major emphasis |
| Executive Leadership | Limited | Core competency |
| Primary Outcome | AI practitioner | Enterprise AI manager |
CAIM®
Choose Your Next Step
APPLY FOR CAIM® CERTIFICATION
Ready to validate your advanced AI management competency?
APPLY NOW →
REGISTER FOR THE CAIM® EXAM
Already prepared?
Demonstrate your strategic, governance, risk, and enterprise AI management competency through the CAIM® Certification Examination.
REGISTER FOR THE EXAM →
ENROLL IN CAIM® TRAINING
Build advanced capabilities across all eight CAIM® enterprise AI management domains.
ENROLL NOW →
CHOOSE THE CAIM® CAPSTONE PATHWAY
Prefer applied assessment?
Demonstrate your advanced competency through the Enterprise Artificial Intelligence Management Capstone Project.
START YOUR CAPSTONE →
DOWNLOAD THE CAIM® CERTIFICATION GUIDE
Review:
DOWNLOAD PROGRAM GUIDE →
- Eligibility requirements
- Body of Knowledge
- Training structure
- Assessment options
- Exam requirements
- Capstone expectations
- Certification policies
- Renewal requirements
CAIM®
Built for AI Leaders — Not Just AI Users
CAIM® is designed to move beyond operational familiarity with AI.
The certification focuses on the management questions that organizations increasingly need leaders to answer:
CAIM® is built around these enterprise-level management challenges.
- Where should we invest in AI?
- Which AI initiatives should receive priority?
- Should we build, buy, partner, or use a managed AI platform?
- How should Generative AI and AI agents be governed?
- How do we manage AI cybersecurity and enterprise risk?
- How should AI performance be monitored?
- What controls should exist around high-impact AI decisions?
- How do we demonstrate ROI and organizational value?
- How should AI change our workforce and operating model?
- How do executives communicate AI opportunities, limitations, and risks responsibly?
CAIM®
Module 1: Enterprise AI Strategy, Leadership, and Organizational Readiness
Learn how to develop and manage an enterprise AI strategy aligned with business objectives, technology capabilities, organizational maturity, and competitive priorities.
Key Topics
- Enterprise AI strategy and strategic alignment
- AI maturity and organizational readiness
- AI opportunity identification and prioritization
- AI operating models and leadership structures
- Executive AI decision-making and leadership accountability
You Will Learn To:
- Assess organizational AI maturity
- Develop an enterprise AI vision
- Identify strategic AI priorities
- Create AI roadmaps
- Evaluate organizational readiness
- Establish leadership and governance responsibilities
- Align AI investments with enterprise objectives
CAIM®
Module 2: AI Investment, Portfolio, and Business Value Management
Learn how to evaluate AI investments, develop strong business cases, prioritize AI initiatives, and measure enterprise value.
Key Topics
- AI business case development
- AI investment and financial evaluation
- AI portfolio management
- AI performance and value measurement
- Scaling AI across the enterprise
You Will Learn To:
- Evaluate the economic value of AI initiatives
- Estimate benefits and total cost considerations
- Compare competing AI investments
- Prioritize enterprise AI projects
- Develop measurable success criteria
- Establish AI portfolio governance
- Track benefits realization
- Scale successful AI solutions
CAIM®
Module 3: Enterprise AI Architecture, Generative AI, and Technology Management
Develop the management competency needed to evaluate modern AI platforms, architectures, foundation models, Generative AI, RAG, intelligent agents, and emerging technologies.
Key Topics
- Enterprise AI architecture and platforms
- Generative AI and foundation-model strategy
- RAG, AI agents, and intelligent automation
- Build, buy, partner, and vendor selection
- AI economics and emerging technologies
You Will Learn To:
- Evaluate enterprise AI architectures
- Compare AI platforms
- Assess foundation-model options
- Understand RAG architectures
- Evaluate AI agents and agentic workflows
- Compare commercial and open models
- Make build-versus-buy decisions
- Assess cloud and infrastructure requirements
- Evaluate emerging AI capabilities
- Consider AI technology obsolescence and technical debt
CAIM®
Module 4: AI Program, Project, Vendor, and Implementation Management
Learn how to govern enterprise AI implementation from planning through deployment and adoption.
Key Topics
- AI program and project governance
- AI requirements and stakeholder management
- Resource and cross-functional team management
- AI vendor and third-party management
- Implementation, adoption, and benefits realization
You Will Learn To:
- Establish AI program governance
- Define milestones and accountability
- Manage AI requirements
- Lead cross-functional teams
- Coordinate technical and business stakeholders
- Evaluate AI vendors
- Manage third-party dependencies
- Oversee pilot-to-production transitions
- Manage adoption
- Track expected business outcomes
CAIM®
Module 5: Responsible AI, Governance, Privacy, and Compliance
Learn how to establish governance structures that support responsible, transparent, accountable, and compliant use of AI.
Key Topics
- Enterprise AI governance frameworks
- Responsible AI and ethical leadership
- Bias, explainability, and human oversight
- Privacy, data governance, and regulatory compliance
- AI assurance, standards, and audit readiness
You Will Learn To:
- Establish AI governance committees
- Develop AI policies
- Define accountability
- Create AI model inventories
- Assess high-impact AI use cases
- Evaluate fairness and bias
- Establish human oversight controls
- Address explainability requirements
- Protect personal and sensitive information
- Prepare AI programs for internal and external assurance activities
CAIM®
Module 6: AI Security, Cybersecurity, and Enterprise Risk Management
Develop advanced competency in managing AI-related threats, vulnerabilities, enterprise exposures, and organizational risk.
Key Topics
- Enterprise AI risk management
- AI and machine learning security
- Generative AI and agentic AI security
- Third-party, cloud, and operational AI risk
- AI incident management and resilience
You Will Learn To:
- Establish AI risk categories
- Evaluate adversarial AI threats
- Assess data poisoning risks
- Address prompt injection
- Evaluate model-extraction risks
- Manage AI data leakage
- Assess agentic AI risks
- Manage third-party AI exposure
- Establish AI incident processes
- Improve AI operational resilience
CAIM®
Module 7: AI Operations, MLOps, LLMOps, and Lifecycle Governance
Learn how to govern production AI systems after implementation.
Key Topics
- Production AI and operational governance
- MLOps and LLMOps management
- AI monitoring and performance management
- AI change, configuration, and incident control
- AI lifecycle, continuous improvement, and retirement
You Will Learn To:
- Establish production AI controls
- Manage model inventories
- Oversee MLOps and LLMOps processes
- Monitor AI reliability and performance
- Track drift
- Monitor bias and safety metrics
- Govern prompt and RAG changes
- Manage model updates
- Establish rollback procedures
- Determine when models should be retrained or retired
CAIM®
Module 8: AI Transformation, Workforce, and Professional Leadership
Learn how to lead organizational transformation in an AI-enabled enterprise.
Key Topics
- AI-enabled organizational transformation
- Workforce strategy and human-AI collaboration
- AI literacy and capability development
- Change management and stakeholder engagement
- Executive communication and professional leadership
You Will Learn To:
- Redesign AI-enabled processes
- Evaluate workforce impacts
- Develop human-AI operating models
- Build AI literacy programs
- Plan AI workforce development
- Lead organizational change
- Manage employee adoption
- Build trust in AI
- Communicate AI risk to executives
- Present AI value to leadership and boards
CAIM®
Tools, Technologies, and Enterprise Platforms Covered
CAIM® is designed as a vendor-neutral management certification.
Candidates are not expected to become experts in every AI product. Instead, they learn how to evaluate, govern, select, integrate, and manage technologies used in enterprise AI environments.
Depending on the approved training environment, candidates may encounter examples involving:
CAIM®
Enterprise AI Applications Covered
CAIM® focuses on the management of AI across real organizational environments.
Applications may include:
- Enterprise Generative AI
- AI-powered customer service
- Intelligent process automation
- Fraud detection
- Predictive analytics
- Cybersecurity analytics
- Threat detection
- Intelligent document processing
- Recommendation systems
- Financial forecasting
- Risk analytics
- Supply chain optimization
- Demand forecasting
- Predictive maintenance
- Healthcare AI
- Human resources analytics
- AI-powered decision support
- Marketing intelligence
- Intelligent search
- RAG-based knowledge systems
- AI-powered software development
- AI agents
- Autonomous workflow systems
- Enterprise copilots
- Digital transformation initiatives
CAIM®
Practical Management Labs (Instructor-Led Training)
CAIM® training can include five applied management-level laboratories.
Lab 1: Enterprise AI Maturity Assessment and Strategic Roadmap
Assess a simulated organization's AI maturity and develop an enterprise AI roadmap.
Activities
- Evaluate organizational readiness
- Identify capability gaps
- Assess governance maturity
- Prioritize AI opportunities
- Develop a phased implementation roadmap
CAIM®
Lab 2: AI Business Case and Portfolio Prioritization
Evaluate several competing AI initiatives and determine which should receive investment priority.
Activities
- Assess strategic alignment
- Evaluate feasibility
- Compare expected benefits
- Estimate costs
- Assess risk
- Rank AI investments
- Present portfolio recommendations
CAIM®
Lab 3: Generative AI Governance and Vendor Evaluation
Evaluate an enterprise Generative AI solution and proposed vendor.
Activities
- Compare solution alternatives
- Assess LLM architecture
- Evaluate RAG requirements
- Analyze vendor dependence
- Assess privacy and cybersecurity
- Evaluate contractual and third-party risks
- Develop governance recommendations
CAIM®
Lab 4: AI Security, Risk, and Responsible AI Assessment
Conduct a management-level assessment of an enterprise AI system.
Activities
- Identify cybersecurity threats
- Evaluate AI risk
- Review bias and fairness
- Assess privacy
- Examine explainability
- Determine human oversight
- Recommend risk-treatment controls
CAIM®
Lab 5: Executive AI Performance and Transformation Review
Evaluate an AI program and present executive recommendations.
Activities
- Review AI KPIs
- Evaluate ROI
- Assess adoption
- Analyze operational performance
- Identify workforce impacts
- Evaluate risk
- Recommend continuation, remediation, scaling, or retirement
CAIM®
The CAIM®–IBACTP® Enterprise AI Management Framework
The CAIM® management framework integrates eight dimensions:
- STRATEGY
- INVESTMENT
- TECHNOLOGY
- IMPLEMENTATION
- GOVERNANCE
- SECURITY & RISK
- OPERATIONS
- TRANSFORMATION & VALUE
This integrated model reflects the responsibilities of an enterprise AI manager from initial strategy through long-term value realization.
CAIM®
Responsible AI and Governance Focus
CAIM® gives substantial emphasis to the responsible management of Artificial Intelligence.
Managers must understand how to establish controls around:
Responsible AI is treated as an enterprise management responsibility — not simply a technical feature.
- AI accountability
- Fairness
- Bias
- Transparency
- Explainability
- Reliability
- Safety
- Privacy
- Data governance
- Human oversight
- Regulatory requirements
- Auditability
- Documentation
- Model inventories
- Approval processes
- AI risk classification
- High-impact AI use cases
CAIM®
AI Cybersecurity and Risk Focus
Modern AI systems create new attack surfaces and operational risks.
CAIM® prepares managers to understand and oversee risks such as:
Candidates learn how to translate these technical risks into governance and management decisions.
- Data poisoning
- Adversarial attacks
- Model extraction
- Model theft
- Prompt injection
- Indirect prompt injection
- Jailbreaking
- Sensitive data exposure
- Insecure AI outputs
- Excessive agency
- Agent misuse
- Third-party AI risk
- Cloud AI dependencies
- AI supply-chain risk
- Intellectual property exposure
- Business continuity
- AI incident management
CAIM®
Generative AI Management Focus
CAIM® recognizes that Generative AI has become a major enterprise-management responsibility.
The program addresses:
- Foundation-model selection
- LLM evaluation
- Enterprise GenAI use cases
- RAG
- Embeddings
- Vector databases
- Knowledge grounding
- AI agents
- Agentic workflows
- Model customization
- Fine-tuning considerations
- GenAI cybersecurity
- Prompt governance
- Privacy
- Intellectual property
- Human oversight
- Cost management
- Vendor dependence
- GenAI performance monitoring
CAIM®
AI Agent and Agentic AI Governance
As AI systems become more autonomous, CAIM® prepares managers to evaluate:
The goal is to help organizations capture the value of AI agents without losing appropriate management control.
- Agent permissions
- Tool access
- Workflow autonomy
- Human approval
- Escalation
- Identity and authentication
- Authorization
- Agent monitoring
- Multi-agent environments
- Excessive agency
- Operational safeguards
- Accountability
CAIM®
Enterprise AI Vendor Management
CAIM® prepares managers to evaluate third-party AI providers.
Areas include:
- Vendor due diligence
- Data handling
- Model ownership
- Licensing
- Security controls
- Privacy
- Service availability
- Model transparency
- Subprocessors
- Intellectual property
- Data residency
- Contract terms
- Exit strategies
- Concentration risk
- Vendor monitoring
CAIM®
Industry Applications
CAIM® management competencies can be relevant across industries such as:
- Artificial Intelligence
- Information Technology
- Banking and Financial Services
- Insurance
- Cybersecurity
- Healthcare
- Government
- Telecommunications
- Manufacturing
- Energy
- Oil and Gas
- Education
- Retail
- Supply Chain
- Logistics
- Transportation
- Consulting
- Professional Services
- Software
- Data and Analytics
- Information Systems
CAIM®
Certified Artificial Intelligence Manager (CAIM®)
Active credential holders may use the designation after their names according to applicable IBACTP® certification policies.
Example
Jane Smith, CAIM®
The CAIM® designation signifies demonstrated advanced competency in:
- AI strategy
- AI governance
- AI investment
- AI security
- Enterprise risk
- AI implementation
- AI operations
- Responsible AI
- Organizational transformation
- Executive AI leadership
CAIM®
From AI Professional to AI Leader
CAIM® serves as the advanced managerial credential in the IBACTP® AI certification pathway.
Certified Artificial Intelligence Professional
Professional-level competency in:
- AI technologies
- Machine learning
- Generative AI
- Prompt engineering
- RAG
- AI security
- Responsible AI
- AI implementation
Certified Artificial Intelligence Manager
Advanced competency in:
- Enterprise AI strategy
- AI leadership
- Investment management
- Portfolio management
- AI governance
- Cybersecurity
- Enterprise risk
- Vendor management
- MLOps/LLMOps governance
- Workforce transformation
- Executive decision-making
- Business value
CAIM®
One Advanced Credential. Eight Enterprise AI Leadership Domains.
8 Advanced Modules
Enterprise AI strategy through transformation.
5 Applied Management Labs
Practice strategic, governance, security, and executive decision-making.
2 Assessment Pathways
Certification Examination or Enterprise Capstone Project.
1 Advanced Professional Designation
CAIM® — Certified Artificial Intelligence Manager
CAIM®
Lead the AI-Driven Enterprise
Don't just understand Artificial Intelligence.
Strategize it. Invest in it. Govern it. Secure it. Scale it. Lead it.
CAIM®
Certified Artificial Intelligence Manager (CAIM®)
Offered by the International Board of AI, Cybersecurity & Technology Professionals (IBACTP®)
Enterprise AI Leadership. Responsible Governance. Strategic Value.
Below are two polished, conversion-focused landing-page drafts—one for CGAIP® and one for CGAIM®—with ISO alignment, competency models, tools and technologies, global relevance, accreditation positioning, FAQ, and strong calls to action.
The examination
Exam & Certification Details
Everything you need to plan your sitting.
CAIM-200
Exam code for the Advanced Manager-level Artificial Intelligence credential.
100 questions (maximum)
Multiple choice, completed in 120 minutes.
700 out of 1000
Passing score. Delivered in English.
Recommended experience
A minimum of five years of experience, including two years in a supervisory, lead or management role.
Where you sit it
IBACTP® approved testing centers and online proctored delivery
Staying certified
Three-year certification cycle with continuing professional education
Choose your route
Four ways to enroll. One credential.
Every route leads to the same CAIM® examination and the same designation.
Progression
Your Certification Pathway
Start as a Professional. Advance as a Leader.
Get started
Ready to certify as a CAIM®?
Self-Paced Learning
Exam fee only, with complimentary course materials provided — $400 USD.
Virtual Instructor-Led Training
4 days, 2 hours daily online. All course materials + Exam — $1,200 USD.
Bootcamps & Intensives
10 days, 2 hours daily. All course materials + Exam — $1,800 USD.
Corporate Training
Certify a whole team on a schedule that suits your organization. Fees negotiable.
Questions
Frequently Asked Questions — CAIM®
1. What is the CAIM® certification?
The Certified Artificial Intelligence Manager (CAIM®) is an advanced professional certification designed to validate competency in enterprise AI strategy, leadership, governance, investment, cybersecurity, risk management, implementation, operations, and organizational transformation.
2. Who offers CAIM®?
CAIM® is offered by the:
International Board of AI, Cybersecurity & Technology Professionals (IBACTP®).
3. Is CAIM® a technical AI certification?
CAIM® includes technical AI concepts, but its primary purpose is advanced management and leadership.
Candidates are expected to understand technologies sufficiently to make informed decisions about strategy, governance, risk, investment, implementation, and operations.
4. Do I need to be a programmer?
Programming may be helpful, but CAIM® is not designed primarily as a software-development credential.
The program emphasizes management, governance, strategy, risk, technology evaluation, and enterprise implementation.
No.
5. Do I need CAIP® before CAIM®?
CAIP® is a recommended pathway but does not necessarily have to be mandatory.
Candidates with equivalent AI knowledge and relevant professional experience may qualify according to applicable eligibility requirements.
6. Is CAIM® suitable for IT managers?
CAIM® is highly relevant for IT managers, Information Systems managers, data managers, cybersecurity managers, digital transformation leaders, and other professionals responsible for enterprise technology.
Yes.
7. Does CAIM® cover Generative AI?
Topics include:
- Yes.
- Generative AI is a major part of the curriculum.
- LLMs
- Foundation models
- RAG
- Embeddings
- AI agents
- Agentic workflows
- Enterprise GenAI
- Vendor selection
- GenAI security
- Governance
- Cost management
- Monitoring
8. Does CAIM® cover AI agents?
The curriculum addresses agentic AI from a managerial and governance perspective, including autonomy, tool access, permissions, human oversight, security, accountability, monitoring, and enterprise adoption.
Yes.
9. Is CAIM® vendor-neutral?
The certification emphasizes transferable AI management competencies rather than one commercial platform.
Yes.
10. How long is CAIM® training?
The recommended training duration is approximately:
60 Hours
11. How is CAIM® assessed?
Candidates may choose either:
- CAIM® Certification Examination
- OR
- CAIM® Enterprise AI Management Capstone Project
12. What is the exam format?
The recommended examination includes:
- 100 questions
- Multiple-choice and scenario-based questions
- 150 minutes
- Closed book
- Secure proctoring
- Recommended passing score: 70%
13. What does Capstone involve?
The Capstone requires candidates to develop an enterprise AI management solution involving:
- Strategy
- Investment
- Technology
- Governance
- Security
- Risk
- Implementation
- Workforce transformation
- Performance
- Business value
14. Which ISO standards are relevant?
The CAIM® curriculum is designed with consideration of frameworks such as:
- ISO/IEC 42001
- ISO/IEC 23894
- ISO/IEC 22989
- ISO/IEC 27001
- ISO/IEC 27701
- ISO 31000
- ISO/IEC 17024
- NIST AI Risk Management Framework
15. Is CAIM® globally relevant?
Yes, CAIM® is designed to develop vendor-neutral competencies applicable across industries and geographic markets.
Actual recognition remains subject to individual employer, institutional, regulatory, or government requirements.
16. Is CAIM® accredited by ANAB or NCCA?
Formal accreditation should only be stated if such accreditation has officially been granted.
CAIM® may be designed with consideration of personnel-certification principles associated with ISO/IEC 17024, ANAB, NCCA, I.C.E., and recognized credentialing best practices.
17. What designation can I use?
Successful candidates may use:
after their names according to IBACTP® certification policies.
Example:
- CAIM®
- Jane Smith, CAIM®
18. How long is the certification valid?
The recommended certification cycle is:
Three years
19. How many CPE credits are required?
The recommended recertification requirement is:
40 CPE credits every three years
20. Is CAIM® only for AI managers?
The certification is also relevant for professionals in:
No.
- IT management
- Information Systems management
- Data leadership
- Cybersecurity
- Risk
- Governance
- Consulting
- Project management
- Program management
- Enterprise architecture
- Digital transformation
- Technology leadership
CAIM®
Ready to Lead AI at the Enterprise Level?
Become a Certified Artificial Intelligence Manager
Become CAIM® Certified.
AI Leadership for the Enterprise Era
Strategy • Governance • Generative AI • Security • Risk • Operations • Transformation • Value
Artificial Intelligence is creating a new generation of technology leadership roles.
Organizations need professionals who can:
CAIM® is designed to validate those capabilities.
Lead AI Strategy. Govern Responsibly. Deliver Measurable Value.
CAIM® validates advanced managerial competency across the complete enterprise AI lifecycle — from strategy, investment, and technology selection through governance, cybersecurity, deployment, organizational transformation, performance management, and value realization.
- Set Strategy
- Prioritize Investment
- Select Technology
- Govern AI
- Manage Cybersecurity
- Control Risk
- Lead Implementation
- Transform the Workforce
- Measure Enterprise Value
Certified Artificial Intelligence Manager (CAIM®) · International Board of AI, Cybersecurity & Technology Professionals (IBACTP®)
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