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AI Agents for Business: Build the Agentic Organization
New
15 students
AI Agents for Business: Build the Agentic Organization
Design, govern, measure, and scale AI agents, multi-agent systems, and human-AI workflows for responsible business value
Created byDr. Law Payne
Last updated 10/2026
English
What you'll learn
- Explain how AI agents differ from chatbots, copilots, automation tools, and traditional generative-AI systems.
- Analyze the goals, context, tools, memory, reasoning, permissions, and control mechanisms that form an AI agent.
- Redesign business workflows around effective human-agent collaboration rather than merely automating existing jobs.
- Allocate decision rights among employees, leaders, AI agents, and governance functions.
- Design multi-agent systems using specialized roles, shared context, orchestration, and visible control points.
- Apply identity, least-privilege access, monitoring, auditability, incident response, and recourse to autonomous AI.
- Build a practical ninety-day roadmap for identifying, piloting, evaluating, and responsibly scaling an agentic workflow.
- Measure agent performance across effectiveness, efficiency, reliability, human experience, business value, and risk.
- Identify evaluation drift, silent failure, fragile dependencies, and emerging governance problems.
- Build an organizational control plane connecting technical visibility with business ownership and executive accountability.
- Develop workforce capabilities for supervising, challenging, evaluating, and improving agentic systems.
- Scale agentic systems while preserving human judgment, stakeholder trust, institutional learning, and responsible leadership.
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Course content
2 sections • 7 lectures • 54m total length
Requirements
- No programming, data-science, or AI-engineering experience is required.
- A basic interest in business strategy, leadership, digital transformation, or artificial intelligence is recommended.
- Learners should be prepared to think critically about organizational design, authority, risk, and human judgment.
- Professional experience in management, operations, consulting, technology, or organizational change is helpful but not required.
Description
This course contains the use of artificial intelligence.
AI agents are changing the role of artificial intelligence inside organizations. Instead of only generating answers, summaries, or recommendations, agentic systems can use tools, access business information, coordinate tasks, make decisions, and take action across real workflows.
That shift creates an important leadership challenge. Organizations must learn how to capture the value of autonomous AI without surrendering visibility, accountability, human judgment, or organizational control.
In **AI Agents for Business: Build the Agentic Organization**, Professor Law provides a practical and advanced introduction to the design, governance, measurement, and responsible scaling of AI agents in business.
The course begins by moving beyond the chatbot mindset. Students examine the anatomy of an AI agent, the transition from assistance to delegated authority, and the organizational capabilities required when AI can act.
Students then learn how to redesign work around human-AI teams. The course distinguishes jobs from workflows, introduces four modes of human-agent collaboration, and explains why decision rights, escalation paths, expertise, and professional judgment must be deliberately designed.
The course expands from individual agents to the multi-agent enterprise. Students examine specialized agents, shared context, orchestration, system control, and the operating model required to coordinate multiple autonomous capabilities.
Governance receives dedicated attention. Students learn how identity, access, permission, monitoring, auditability, incident response, recourse, and human accountability should shape autonomous action.
The final portion of the course translates these concepts into practice. Students receive a ninety-day roadmap for diagnosing opportunities, designing pilots, learning from evidence, and scaling responsibly. An advanced second section then teaches students how to measure business value, identify drift and silent failure, conduct agent value reviews, build an organizational control plane, strengthen workforce capability, and scale the agentic enterprise without losing control.
This course combines doctoral-level organizational leadership concepts with accessible explanations, realistic business scenarios, visual models, and the continuing Meridian Group case.
By the end of the course, students will possess an integrated framework for designing agentic workflows that are valuable, measurable, governable, and worthy of stakeholder trust.
Who this course is for:
- Managers and executives responsible for AI adoption, digital transformation, strategy, operations, or organizational change.
- Graduate and doctoral students studying business, leadership, management, technology, or organizational development.
- Consultants, educators, analysts, product leaders, and transformation professionals advising organizations on AI.
- Business professionals who want to understand AI agents without needing to become software engineers.
- Technical professionals who want a stronger understanding of organizational design, governance, and leadership.
- Current and aspiring leaders who want to introduce autonomous AI responsibly while preserving accountability and human agency.