Skip to main content
Image coming soon

GEN7369 Leading AI Agents and Automation for Senior Leaders

$201.00
Adding to cart… The item has been added

The Executive Diagnostic and Governance Toolkit

Leading AI Agents and Automation for Senior Leaders

Score your own function red, amber or green, find out which part is weakest, and walk into the next budget round able to defend what you want to fix. Built for leaders reviewing the routing, chasing and re-keying between systems that nobody owns.

$199 one-time
30-day money-back guarantee Verified against latest insights, updated access provided within 24h

Each order is checked and updated against the latest insights before delivery. That is why access takes up to 24 hours rather than being instant.

What you walk out with
A scored, ranked picture of your own function, and a defensible answer to what to fix first.
1 You stop guessing where you stand.
You finish with a score, not an opinion: every part of your function rated red, amber or green, with the weakest ranked first. Evidence: a Quick Scan for the shape of it, then seven domain assessments of 30 scored questions each, 210 in all, rolled into one scorecard, plus a maturity radar and a current-versus-target gap analysis.
2 You can defend the decision.
You walk into the budget round with the gap named, the owner named and done defined, instead of a case built on instinct. Evidence: project charter, scope statement, RACI, requirements traceability and work breakdown structure, pre-filled in your domain's language.
3 The work actually moves.
The month after the decision is already built, so nothing stalls waiting for someone to design a form. Evidence: more than 60 project templates across all five PMBOK process groups, plus runbooks, SOPs, a KPI framework, audit checklists and a risk matrix. 55 to 65 files in total.
4 You use it the day it lands.
No blank templates to interpret. Every workbook opens with what it is, who uses it, when, how, a 1 to 5 scoring guide, what good looks like, and a worked example you delete and type over.
The Quick Scan is one sitting. You will know your weakest area before the day is out.
Nothing in it is generic project management: the build rejects any file that could belong to another course. Updated after you enrol, so it reflects where the work stands now. The 144-chapter course is included behind it, for the parts you want to go deeper on.
You’re accountable for work that no one owns.

The situation this is built for

Every day, critical tasks fall through the cracks because they live between systems, not inside them. Your teams re-enter data, chase approvals, and route requests across platforms that don’t speak to each other. The work gets done — slowly, manually, inconsistently — because no single role or system is responsible. This invisible tax erodes velocity, increases risk, and frustrates high performers. Now, AI agents promise to automate it, but no one is asking who should control the decisions, handoffs, and governance of those agents. You’re left wondering: is this really solvable, or just another layer of complexity?

Who this is for

Senior leaders responsible for end-to-end outcomes in complex, cross-system environments — including operations, compliance, IT governance, and digital transformation. They own functions where work spans CRM, ERP, ticketing, identity, and security platforms, but no single team owns the full flow.

Who this is not for

Individual contributors looking to build AI agents, technical teams seeking implementation blueprints, or vendors selling automation tools. This is not for those wanting a technical deep dive or product demo.

What you walk away with

  • See the hidden cost of unowned work across systems
  • Distinguish between automatable work and owned work
  • Map where AI agents create control risks or opportunities
  • Lead decisions on agent behavior, escalation, and audit
  • Design governance that scales with autonomous systems

How this maps to your situation

  • Unowned work across systems
  • Agent-driven decision flows
  • Boundary-spanning tasks
  • Leadership in hybrid human-agent environments

Before vs. after

Before
You inherit fragmented workflows, invisible handoffs, and growing pressure to 'automate.' No one owns the full chain, and mistakes accumulate silently. You lack a framework to assess what should change — or how to lead it.
After
You have a clear map of where automation adds control, not chaos. You lead with a decision framework, governance standards, and a playbook to guide real change across systems and teams.

What's included with your purchase

  • 12 modules with 12 chapters each (144 chapters)
  • Downloadable templates and worked examples for every module
  • Hand-built implementation playbook delivered alongside course access
  • 30-day money-back guarantee

Delivery and format

  • Course and learning environment access provisioned within 24 hours of purchase
  • Hand-built implementation playbook delivered alongside course access

Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.

Time investment: Approximately 3 hours per module, designed for senior leaders with variable availability. Total commitment: 36 hours over 6–12 weeks.

If nothing changes
Without intervention, unowned work will increasingly be delegated to AI agents without governance, creating hidden risk, compliance gaps, and loss of accountability. Leaders who do not shape this shift will inherit systems they cannot control.

How this compares to the alternatives

Unlike vendor-led training or technical bootcamps, this course focuses exclusively on leadership decisions, governance, and cross-system ownership. It does not teach coding or promote tools. It equips you to lead in environments where AI agents act, without requiring technical expertise.

Also included: the full course, for when you want the reasoning behind a finding (12 modules, 144 chapters)

Depth reference. The diagnostic and the templates stand on their own; this is what to read when you want the reasoning behind a finding.

Module 1. The Unowned Work Problem
Identify the invisible tasks that fall between systems and roles, creating drag across your organization.
12 chapters in this module
  1. Understanding the gap between system ownership and work ownership
  2. Mapping where tasks get stuck between platforms
  3. Recognizing the cost of manual handoffs in real time
  4. Diagnosing who is blamed when work fails
  5. Identifying recurring tasks with no single owner
  6. Seeing the difference between process and flow
  7. Documenting re-keying as a symptom of system misalignment
  8. Tracking how long tasks wait between actions
  9. Assessing the risk of inconsistent execution
  10. Interviewing teams about invisible coordination work
  11. Classifying tasks that never reach formal workflows
  12. Measuring the effort spent on tracking instead of doing
Module 2. The Rise of Agentic Systems
Understand how AI agents operate independently across systems and what that means for control.
12 chapters in this module
  1. Defining agentic behavior in enterprise environments
  2. Distinguishing agents from scripts and bots
  3. Observing how agents make autonomous decisions
  4. Tracing agent-initiated actions across platforms
  5. Identifying agent roles in approval and routing
  6. Analyzing how agents handle exceptions
  7. Reviewing examples of agent-driven task completion
  8. Assessing agent memory and context retention
  9. Mapping agent access across identity domains
  10. Evaluating how agents log their own actions
  11. Understanding agent escalation protocols
  12. Documenting agent decision criteria in real cases
Module 3. Work That Crosses Boundaries
Analyze tasks that span departments, systems, and compliance zones.
12 chapters in this module
  1. Identifying cross-functional workflows in daily operations
  2. Tracking data movement between secure and open systems
  3. Mapping approval chains that cross role boundaries
  4. Documenting compliance handoffs between teams
  5. Observing how access policies affect task flow
  6. Analyzing where work stalls at boundary points
  7. Classifying tasks that require multiple system logins
  8. Measuring delay at departmental interfaces
  9. Reviewing audit trails for boundary-crossing tasks
  10. Interviewing staff about inter-team dependencies
  11. Identifying redundant verification steps at handoffs
  12. Assessing risk accumulation at system edges
Module 4. The Illusion of Full Automation
Recognize where automation claims mask ongoing manual intervention.
12 chapters in this module
  1. Spotting workflows labeled automated but requiring human fixes
  2. Identifying tasks with high exception rates
  3. Reviewing logs for frequent manual overrides
  4. Documenting where automation fails silently
  5. Assessing the effort behind ‘set and forget’ systems
  6. Interviewing teams about hidden maintenance work
  7. Measuring time spent monitoring automated flows
  8. Tracing escalations from bots to humans
  9. Evaluating the cost of false automation promises
  10. Mapping where human judgment is still required
  11. Analyzing why some tasks resist full automation
  12. Classifying tasks with unstable automation outcomes
Module 5. Ownership and Accountability Gaps
Clarify who is responsible when AI agents act on behalf of the organization.
12 chapters in this module
  1. Defining accountability for agent-driven decisions
  2. Mapping decision rights in agent-managed workflows
  3. Identifying who approves agent behavior rules
  4. Reviewing escalation paths when agents fail
  5. Documenting audit requirements for agent actions
  6. Assessing liability for agent errors
  7. Clarifying ownership of agent-generated data
  8. Establishing review cycles for agent performance
  9. Defining consequences for unapproved agent actions
  10. Interviewing legal and compliance on agent risks
  11. Mapping stakeholder expectations for agent conduct
  12. Creating role definitions for agent supervision
Module 6. Control Without Ownership
Design oversight mechanisms for systems you don’t directly manage.
12 chapters in this module
  1. Establishing visibility into cross-system workflows
  2. Creating dashboards for unowned task tracking
  3. Defining thresholds for intervention in agent flows
  4. Implementing audit trails for agent decisions
  5. Setting up alerts for anomalous behavior
  6. Reviewing access logs for agent activity
  7. Documenting change requests in agent logic
  8. Assessing consistency of agent output over time
  9. Mapping dependencies for agent reliability
  10. Evaluating backup plans for agent failure
  11. Designing feedback loops from end users
  12. Balancing autonomy with governance needs
Module 7. The Governance of Autonomous Actions
Build frameworks to govern what AI agents are allowed to do.
12 chapters in this module
  1. Defining acceptable agent behavior by function
  2. Classifying actions requiring human approval
  3. Establishing rules for data access by agents
  4. Reviewing agent permissions across systems
  5. Creating policies for agent-to-agent communication
  6. Documenting compliance constraints on automation
  7. Mapping regulatory requirements to agent tasks
  8. Assessing ethical implications of agent decisions
  9. Designing revocation protocols for rogue agents
  10. Implementing time limits on agent authority
  11. Reviewing agent actions against policy standards
  12. Updating governance as agent capabilities evolve
Module 8. Designing for Handoff Integrity
Ensure reliability when work passes between people, systems, and agents.
12 chapters in this module
  1. Mapping all handoff points in critical workflows
  2. Defining required information at each transition
  3. Validating data completeness before handoff
  4. Establishing ownership at each stage
  5. Designing confirmation protocols for task receipt
  6. Tracking handoff success rates over time
  7. Identifying common failure modes in transitions
  8. Creating fallback procedures for missed handoffs
  9. Measuring latency between handoff events
  10. Reviewing audit logs for handoff anomalies
  11. Training teams on handoff expectations
  12. Automating handoff verification where possible
Module 9. Measuring What Automation Changes
Track the real impact of AI agents beyond efficiency claims.
12 chapters in this module
  1. Defining success metrics for agent deployment
  2. Measuring changes in task completion time
  3. Tracking error rates before and after automation
  4. Assessing impact on employee workload
  5. Evaluating shifts in decision ownership
  6. Monitoring changes in rework frequency
  7. Documenting changes in escalation patterns
  8. Reviewing user satisfaction with automated flows
  9. Analyzing audit trail completeness
  10. Measuring compliance adherence over time
  11. Comparing cost per task pre and post agent
  12. Identifying unintended consequences of automation
Module 10. Building Organizational Readiness
Prepare teams and structures to work alongside AI agents.
12 chapters in this module
  1. Assessing team understanding of agent roles
  2. Identifying skills gaps in agent collaboration
  3. Designing training for agent interaction
  4. Communicating changes in work ownership
  5. Establishing feedback channels for agent issues
  6. Reviewing role definitions in hybrid workflows
  7. Creating documentation for agent behavior
  8. Preparing teams for agent-driven escalations
  9. Conducting simulations of agent failures
  10. Building trust through transparency
  11. Aligning incentives with automated outcomes
  12. Evaluating cultural readiness for autonomy
Module 11. Creating a Decision Framework for Automation
Develop a repeatable method to decide what should be automated.
12 chapters in this module
  1. Defining criteria for automation eligibility
  2. Assessing risk level of task automation
  3. Evaluating task frequency and volume
  4. Reviewing historical accuracy of manual execution
  5. Determining data availability for agent use
  6. Mapping dependencies for reliable automation
  7. Assessing impact on customer experience
  8. Reviewing compliance implications of automation
  9. Estimating maintenance effort for automated tasks
  10. Prioritizing automation candidates by value
  11. Creating decision logs for automation choices
  12. Establishing review cycles for automation rules
Module 12. Leading the Future of Work
Take ownership of how AI agents reshape work in your organization.
12 chapters in this module
  1. Defining your role in the agent era
  2. Setting expectations for cross-system accountability
  3. Communicating vision for human-agent collaboration
  4. Establishing oversight for autonomous systems
  5. Reviewing progress on automation goals
  6. Adjusting governance based on real outcomes
  7. Sharing lessons from automation pilots
  8. Incorporating feedback into agent design
  9. Planning for scaling successful automations
  10. Addressing ethical concerns in agent behavior
  11. Building resilience into agent-dependent workflows
  12. Documenting your automation leadership journey

Frequently asked

Who is this course designed for?
Senior leaders responsible for outcomes across systems — including operations, compliance, IT governance, and transformation — where work spans platforms but no single team owns the end-to-end flow.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this course require technical knowledge?
No. It is designed for leaders who must govern and lead change, not build or code AI agents.
What will I receive upon enrollment?
Immediate access to all 12 modules, downloadable templates, worked examples, and a tailored implementation playbook delivered alongside course access.
Can I share the course with my team?
Each enrollment is for individual use. Team licenses are available by request.
What formats do the templates come in?
The implementation playbook downloads as PDF and editable XLSX. The course reads in your learning environment and exports to PDF for offline use. The files are yours to keep.
Can I share this with my team?
The licence is per person. Team pricing opens from three seats: reply to the order confirmation with TEAM and we will set it up.
How quickly can I start?
The diagnostic is one sitting and the templates work straight out of the kit. Account access takes up to 24 hours rather than being instant, because every order is checked and updated against the latest sources before it is delivered.
$199 one-time. Approximately 3 hours per module, designed for senior leaders with variable availability. Total commitment: 36 hours over 6–12 weeks..

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

30-day money-back guarantee·Know your weakest area today·210 scored questions·Course included· Account access within 24 hours
30-day money-back guarantee, no questions asked.
Thousands of organisations have bought from The Art of Service since 2000.
!