AI Productivity and Agentic Collaboration Specialist (AIPACS)

It is recommended that candidates complete approximately 150 hours of structured instruction or equivalent hands-on practice using AI tools in professional and workplace scenarios before attempting the AI Productivity and Agentic Collaboration Specialist (AIPACS) Certification exam.

The exam measures readiness across eight core domains and 37 objectives covering practical, professional AI use. Candidates demonstrate their ability to select and direct AI tools, engineer effective prompts, collaborate with AI on real-world work, verify research and analysis, design safe agentic workflows, work with data and multimodal content, apply responsible AI practices, and measure the impact of AI-supported processes.

1. AI Foundations for Professional Work

• Explain the capabilities and limitations of generative AI, copilots, and AI agents
• Distinguish between different types of AI tools and select appropriate tools for workplace tasks
• Identify tasks that are well suited to AI assistance and those requiring human expertise or judgment
• Evaluate how AI is changing workplace tasks, professional roles, and skill requirements

2. Prompt Engineering & Instruction Design

• Construct effective prompts using clear roles, tasks, context, constraints, formats, and success criteria
• Apply advanced prompting strategies to improve the quality and reliability of AI-generated outputs
• Provide relevant documents, examples, background information, and prior decisions as context
• Request structured outputs such as tables, checklists, rubrics, plans, and templates
• Diagnose weak AI responses and iteratively refine prompts to produce more accurate and usable results

3. AI as a Co-Worker & Collaboration Partner

• Use AI to support professional communication, including emails, reports, agendas, plans, and stakeholder updates
• Collaborate iteratively with AI to develop, review, and improve workplace deliverables
• Maintain human ownership, judgment, and accountability for AI-assisted work
• Distinguish productive AI assistance from inappropriate overreliance on AI
• Use AI as a coach, reviewer, and collaborative partner while continuing to develop independent professional skills

4. Research, Analysis & Complex Problem Solving

• Use AI to conduct structured research and synthesize information from multiple sources
• Identify hallucinations, unsupported claims, and other weaknesses in AI-generated information
• Evaluate source credibility and trace important claims back to reliable original sources
• Break complex problems into structured questions, evidence, alternatives, and defensible decisions

5. Agentic AI & Workflow Automation

• Explain how AI agents plan, use tools, take actions, and execute multi-step tasks
• Identify business processes and repetitive tasks appropriate for AI-assisted automation
• Design agentic workflows with clear goals, instructions, permissions, and boundaries
• Establish human approval checkpoints, monitoring, and rollback procedures for AI-driven actions
• Recognize agentic risks including excessive autonomy, prompt injection, inappropriate permissions, and insufficient human oversight

6. AI Tools, Data & Multimodal Workflows

• Use AI effectively with workplace documents, spreadsheets, presentations, images, charts, transcripts, and other content
• Apply AI to extract, organize, analyze, transform, and communicate information across different formats
• Compare AI tools based on accuracy, capabilities, privacy, integrations, and suitability for specific tasks
• Evaluate how AI tools access, process, retain, and protect organizational and personal data

7. Responsible, Ethical & Secure AI Use

• Apply principles of fairness, transparency, accountability, and responsible AI use
• Protect confidential, personal, proprietary, and sensitive information when working with AI systems
• Recognize copyright, intellectual property, bias, privacy, disclosure, and security considerations
• Classify AI use cases according to risk and determine appropriate levels of human review
• Apply organizational AI governance principles, including acceptable, restricted, and prohibited uses and escalation procedures

8. Implementation, Evaluation & Continuous Improvement

• Develop practical plans for introducing AI-supported workflows within a team or organization
• Evaluate AI-assisted work against defined quality standards, rubrics, and performance criteria
• Measure productivity gains, time savings, costs, and return on investment from AI-supported workflows
• Account for review time, errors, implementation costs, and other factors when evaluating AI’s actual business value
• Support responsible AI adoption through communication, training, feedback, measurement, and continuous improvement

The minimum system requirements are:

• Operating system: Windows 7/8/10 OS, MacOS X 10.0x or newer, Linux OS
• Minimum RAM: 1GB or more depending on the Operating System
• Minimum processor: 1.0 Ghz or more depending on the operating system and the architecture
• A color monitor with minimum display resolution: 1366px by 768px
• Internet access
• The latest version of the Chrome browser
• Automatic updates, notifications, other popup windows, and anything that can disrupt the examination process should be disabled