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Collaborative AI for Leaders: Build Human-AI Teams at Work

Design human-AI workflows, decision rights, trust and team performance with a practical Role Play and manager toolkit

Created byCrystal Hutchinson

Last updated 8/2026

English

What you'll learn

Design human-AI collaboration by deciding what AI should automate, assist, or leave to human judgment and accountability.
Build human-AI workflows with clear roles, handoffs, review points, context transfer, escalation paths, and ownership.
Define decision rights between people and AI, including who may recommend, review, approve, override, escalate, and remain accountable.
Recognize bias, unsupported assumptions, missing context, false confidence, and AI-generated conclusions that require human challenge.
Calibrate trust in AI using evidence, experience, psychological safety, employee feedback, and appropriate human oversight.
Diagnose human-AI workflow breakdowns, repeated overrides, unclear responsibilities, trust issues, and capability gaps.
Build AI-ready teams through stronger judgment, verification, adaptability, responsible AI use, exception handling, and escalation.
Measure whether human-AI collaboration improves quality, efficiency, rework, employee experience, stakeholder impact, and results.
Apply course concepts using a Collaborative AI Team Toolkit and Role Play focused on resolving a realistic human-AI team breakdown.

Course content

6 sections • 16 lectures • 1h 9m total length

Collaborative AI for Leaders: Human-AI Team Strategy and Course Roadmap2:36
What does effective human-AI collaboration actually require from leaders? This course introduction maps the journey from AI adoption to human-AI team design, including workflows, decision rights, trust, human judgment, exceptions and performance. Discover how the course, toolkit and Role Play develop practical AI leadership skills for today’s workplace.
Collaborative AI Team Toolkit: Apply Human-AI Leadership at Work1:37
Turn human-AI collaboration principles into practical workplace action with the Collaborative AI Team Toolkit. Learn how to use the workbook throughout the course to examine AI work allocation, workflows, decision rights, trust, exceptions, stakeholder impact and results using one real team process, decision or AI-enabled workflow.
AI Work Allocation: What to Automate, Assist or Keep Human5:09
Should AI automate the task, assist an employee or leave the work human? Explore a practical approach to AI work allocation that protects human judgment, employee experience and accountability while identifying appropriate opportunities for automation and augmentation. Build a stronger foundation for responsible human-AI collaboration and AI-enabled work.
AI Use Case Selection: Choose High-Value Work for Human-AI Collaboration5:26
Not every process becomes better because AI is added to it. Learn how leaders can identify high-value AI opportunities, evaluate workflows before automation and distinguish promising AI use cases from processes that should be improved first. Strengthen AI strategy, workflow management and human-AI collaboration by choosing the right work.

Human-AI Workflow Design: Review, Control and Human Oversight4:37
How do you build an AI-enabled workflow without losing human control? Explore human-AI workflow design through review points, oversight, exceptions and accountability. Learn what leaders should consider when integrating Generative AI into business processes so efficiency does not quietly replace judgment, ownership or responsible decision-making.
Human-AI Handoffs: Design Clear Team Workflows With AI5:04
Human-AI teamwork can break down when work moves between technology and people without enough context or clear responsibility. Learn how leaders can design stronger AI workflow handoffs, review points and escalation paths while coordinating human and AI contributions across team processes. Build collaboration that works beyond the AI output itself.
AI as a Thinking Partner: Explore Options Without Outsourcing Decisions4:44
How can leaders use Generative AI to improve thinking without surrendering judgment? Explore AI as a thinking partner for examining options, scenarios and tradeoffs while preserving human decision-making and accountability. Develop a more sophisticated approach to AI-assisted leadership, problem solving and collaborative decision-making at work.

AI Decision Rights: Review, Approval, Override and Accountability4:04
When AI contributes to a decision, who actually has authority? Learn how leaders can clarify AI decision rights across recommendation, review, approval, override, escalation and accountability. Prevent AI recommendations from quietly becoming decisions and create clearer human oversight for AI-enabled workflows, teams and business processes.
Challenge AI Outputs: Bias, Assumptions and Unsupported Conclusions5:11
AI-generated recommendations can appear confident even when important context, evidence or assumptions deserve another look. Learn how to recognize AI bias, unsupported conclusions, missing information and false confidence so human review becomes meaningful. Strengthen critical thinking, responsible AI use and human judgment in AI-assisted decisions.

Trust in AI Teams: Calibrate Reliance, Challenge and Learning4:05
Should employees trust AI more, or question it more? Effective human-AI teams need neither blind reliance nor automatic rejection. Explore calibrated trust, psychological safety, speaking up, AI error reporting and team learning so employees can challenge questionable outputs while still benefiting from useful AI-supported work.
Responsible AI Stakeholders: Who Benefits, Bears Risk and Can Challenge5:22
Responsible AI leadership requires looking beyond the organization deploying the technology. Explore stakeholder impact in AI decisions by examining who benefits, who bears risk, who may be overlooked, who has a voice and who can challenge an outcome. Strengthen human-centered AI governance, accountability and responsible decision-making.
Employee Feedback for AI Adoption: Improve Human-AI Collaboration5:23
Employees working inside AI-enabled processes often see friction, exceptions and unintended consequences before leaders do. Learn why employee feedback is essential to AI adoption, change management and human-AI collaboration. Explore how leaders can use workforce experience to improve workflows, build trust and strengthen AI implementation over time.

AI Exception Management: Diagnose Human-AI Breakdowns and Workarounds5:09
What should a manager do when employees and AI repeatedly disagree? Explore AI exception management, recurring overrides, informal workarounds and human-AI workflow breakdowns. Learn how leaders can diagnose whether the real issue involves technology, context, review, decision rights, capability or process design before choosing the response.
Build AI-Ready Teams: Judgment, Adaptability and Human-AI Skills4:00
AI-ready teams need more than prompt skills. Explore the human capabilities required for effective AI-enabled work, including judgment, verification, questioning, adaptability, exception handling and escalation. Learn how leaders can develop workforce capability as Generative AI changes workflows, responsibilities and expectations without removing human accountability.

Measure AI Collaboration: Quality, Rework, Adoption and Business Results4:40
AI adoption does not automatically mean AI success. Learn how leaders can evaluate whether human-AI collaboration is improving the work through quality, rework, efficiency, employee experience, adoption and business outcomes. Move beyond usage metrics and assess whether an AI-enabled workflow is delivering measurable organizational value.
Resolve a Human-AI Team Breakdown
Collaborative AI Leadership: Turn Human-AI Team Design Into Results2:36
Complete your Collaborative AI journey by connecting human-AI workflow design, decision rights, trust, human judgment, exception management, team capability and performance measurement. Reinforce the leadership principles needed to build human-AI teams that are not simply using Generative AI, but working with it deliberately and effectively.

Requirements

No technical AI, programming, data science, or prompt engineering experience is required. This course is designed for leaders and professionals who want practical skills for managing human-AI collaboration, AI-enabled teams, Generative AI workflows, responsible AI use, human judgment, decision rights, and AI adoption at work. Bring one real team process, workflow, or decision you would like to improve. The included Collaborative AI Team Toolkit will help you apply the course frameworks to your own work as you learn.

Description

This course contains the use of Artificial Intelligence.

Learn to Lead Human-AI Teams, Not Just Use AI

Most AI courses teach prompts, productivity, or tools.

This course teaches the harder leadership skill:

How to design work when people and AI are both contributing.

You will learn how to decide what AI should automate, where it should assist, where human judgment should lead, and how to build human-AI workflows with clear roles, handoffs, review points, decision rights, and accountability.

You will also learn how to:

Define who can recommend, review, approve, override, and escalate
Know when AI-supported conclusions should be challenged
Build trust without creating blind reliance
Handle breakdowns, repeated overrides, and workarounds
Strengthen team judgment and AI-ready capability
Measure whether human-AI collaboration is actually improving performance

What Makes This Course Different

You do not just watch lectures.

You receive a practical Collaborative AI Team Toolkit you can use with your own workflows, decisions, and teams.

The toolkit includes tools for:

Human-AI work allocation
Workflow and handoff design
Decision rights
Trust and learning
Exception management
Stakeholder impact
Collaboration measurement

You will also complete an interactive Role Play where you must resolve a realistic human-AI team breakdown and apply what you have learned in a real leadership conversation.

That means you leave with more than AI knowledge.

You leave with a practical system for leading human-AI collaboration.

Why This Skill Matters Now

As AI becomes embedded in everyday work, leaders need answers to questions that prompt engineering cannot solve.

Who should do the work?

Who should decide?

Where should humans review?

When should AI be challenged?

What happens when the workflow breaks?

How do we know the new way of working is actually better?

Those are leadership questions.

And they are becoming more important as AI moves from experimentation into real team workflows.

Learn From an Experienced Online Instructor

I’m Crystal Hutchinson Tummala, founder of Pursuing Wisdom Academy.

More than 100,000 students have enrolled in my courses worldwide.

My focus is practical learning that helps professionals understand complex workplace challenges and turn them into clear, usable action.

Choose the Course Built for Human-AI Team Leadership

If you are comparing AI leadership courses, look closely at what they actually teach.

If you want another general AI course, you have many options.

If you want to learn how to design human-AI workflows, define decision rights, manage trust, handle breakdowns, strengthen team capability, and measure results, this course was built specifically for that challenge.

You will also get the Collaborative AI Team Toolkit and an interactive Role Play so you can practice and apply the skill, not just hear about it.

Enroll now and start building a clearer, stronger, more effective way for people and AI to work together.

Who this course is for:

Aspiring leaders and aspiring managers who want future-ready leadership skills for managing people and AI in an increasingly AI-enabled workplace. Team leaders, supervisors, managers, people managers, department managers, and senior managers responsible for introducing AI into team workflows or improving how employees work with Generative AI. Executives and organizational leaders who need a practical framework for human-AI collaboration, AI leadership, decision rights, human oversight, accountability, trust, and responsible AI-enabled work. Project managers, program managers, operations leaders, product leaders, and process owners who need to design better human-AI workflows, handoffs, review points, escalation paths, and team operating practices. Human resources, learning and development, talent management, change management, and employee experience professionals helping teams build AI capability, adaptability, trust, and responsible AI practices. AI implementation, digital transformation, governance, risk, compliance, and business professionals who need to understand how human judgment, stakeholder impact, employee voice, and accountability fit into AI-supported work. Professionals who influence work without holding a formal management title and want to understand how high-performing human-AI teams coordinate decisions, challenge AI recommendations, handle exceptions, and continuously improve. Anyone looking for more than a basic AI productivity or prompting course and who wants practical tools for designing, leading, evaluating, and improving human-AI collaboration at work.

Collaborative AI for Leaders: Build Human-AI Teams at Work

What you'll learn

Explore related topics

Course content

Human-AI Collaboration Strategy: Choose Where AI Adds Value4 lectures • 15min

Human-AI Workflow Design: Roles, Handoffs and Human Control3 lectures • 14min

AI Decision Rights: Human Judgment, Accountability and Challenge2 lectures • 9min

Trust in AI Teams: Voice, Feedback and Responsible Collaboration3 lectures • 15min

Human-AI Team Resilience: Exceptions, Breakdowns and AI Skills2 lectures • 9min

Measure Human-AI Collaboration: Performance, Results and Practice3 lectures • 7min

Requirements

Description

Who this course is for: