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GEN1797 Leading AI Agents and Automation at Work

$199.00
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The Executive Diagnostic and Governance Toolkit

Leading AI Agents and Automation at Work

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 own the work that falls between systems—routing, chasing, re-keying—because no one else does.

The situation this is built for

Every day, your team spends hours moving data across platforms, chasing updates, and correcting errors introduced by handoffs. These tasks don’t appear in org charts, but they consume real time and erode trust. Now AI agents promise to automate exactly this work—without human intervention. But if you don’t lead the transition, someone else will define your role in it.

Who this is for

Senior leaders responsible for cross-functional operations where work slips through gaps in system ownership—service delivery, IT operations, customer support, and internal enablement.

Who this is not for

This is not for technical implementers, software buyers, or innovation teams focused on pilot programs. It is for those who must sustain outcomes when automation changes how work flows.

What you walk away with

  • Map where AI agents will replace manual coordination tasks
  • Identify which workflows are at risk of full automation
  • Redesign roles and responsibilities around AI-handled processes
  • Lead organizational change as agents take over routine work
  • Maintain accountability in systems where no person owns the whole path

How this maps to your situation

  • You are responsible for work that slips between systems
  • You manage teams that chase, route, and re-key data
  • You are accountable for outcomes no single system owns
  • You must lead through automation that changes how work flows

Before vs. after

Before
Work moves slowly between systems. Your team spends effort on re-keying, chasing, and fixing handoff errors. You feel pressure to improve speed and accuracy but lack ownership of the full chain.
After
AI agents handle routing and coordination. You lead oversight, exception management, and continuous improvement. Work flows reliably, and your team focuses on judgment-intensive tasks.

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 completion over 12 weeks with practical application between modules.

If nothing changes
If you do not lead the integration of AI agents, automation will be implemented without regard for your team’s role, accountability gaps will widen, and your influence over workflow outcomes will diminish.

How this compares to the alternatives

Unlike vendor-led training or technical AI courses, this program focuses exclusively on the leadership, operational, and coordination challenges of integrating AI agents into real-world workflows owned by senior leaders.

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. Understanding the Scope of Invisible Work
Identify the tasks that fall between systems and teams, which are now targets for automation.
12 chapters in this module
  1. Defining the work that exists between owned systems
  2. Mapping recurring tasks that involve manual re-keying
  3. Identifying points where work gets delayed or lost
  4. Tracing ownership gaps in current workflow design
  5. Recognizing patterns in exception handling and follow-up
  6. Documenting the cost of unresolved coordination gaps
  7. Analyzing how ticket routing creates invisible labor
  8. Surveying team time spent on handoff management
  9. Classifying tasks by system dependency and ownership
  10. Uncovering hidden dependencies in cross-team workflows
  11. Measuring effort spent on status chasing and updates
  12. Establishing a baseline for pre-automation workload
Module 2. Recognizing the Rise of Autonomous Agents
Understand how AI agents operate independently across systems without direct supervision.
12 chapters in this module
  1. Explaining how agents perform tasks without human input
  2. Identifying agent capabilities in data retrieval and entry
  3. Understanding agent decision-making in ticket triage
  4. Observing how agents handle routine escalations automatically
  5. Mapping agent interactions across multiple platforms
  6. Reviewing examples of autonomous workflow completion
  7. Assessing how agents reduce dependency on human memory
  8. Analyzing agent response times versus manual processes
  9. Evaluating agent accuracy in context-aware routing
  10. Documenting agent behavior during system outages
  11. Comparing agent consistency with human variability
  12. Predicting agent adoption in high-volume task areas
Module 3. Diagnosing Workflow Fragility
Evaluate where current processes break down and create opportunities for agent intervention.
12 chapters in this module
  1. Identifying workflows that rely on manual follow-up
  2. Pinpointing steps requiring cross-system re-entry
  3. Detecting handoff failures between departments
  4. Measuring delay accumulation across process stages
  5. Tracing root causes of duplicated effort
  6. Assessing reliance on individual knowledge holders
  7. Evaluating error rates in multi-step coordination
  8. Mapping communication loops that delay resolution
  9. Uncovering dependencies on outdated notification methods
  10. Analyzing escalation patterns for preventable issues
  11. Reviewing audit trails for missing handoff records
  12. Calculating opportunity cost of unresolved bottlenecks
Module 4. Assessing Organizational Readiness
Determine whether your team and structure can adapt to agent-led workflows.
12 chapters in this module
  1. Evaluating team comfort with autonomous task handling
  2. Assessing leadership understanding of agent capabilities
  3. Reviewing current roles for agent-compatible responsibilities
  4. Measuring clarity in escalation and override protocols
  5. Identifying resistance points in proposed automation
  6. Surveying stakeholder perceptions of AI reliability
  7. Analyzing reporting structures for agent oversight
  8. Determining accountability models for agent errors
  9. Reviewing training materials for agent interaction
  10. Assessing documentation completeness for handoff logic
  11. Evaluating change management capacity in teams
  12. Benchmarking readiness against peer organizations
Module 5. Mapping Agent Integration Points
Locate specific process steps where AI agents can take over without disruption.
12 chapters in this module
  1. Identifying routine ticket classification opportunities
  2. Locating data sync tasks between disconnected systems
  3. Finding repetitive status update requirements
  4. Pinpointing rule-based approval workflows
  5. Mapping customer inquiry response patterns
  6. Detecting scheduled reporting and alerting tasks
  7. Analyzing standard incident resolution paths
  8. Reviewing onboarding checklist execution steps
  9. Identifying cross-departmental notification needs
  10. Locating periodic reconciliation activities
  11. Assessing service request intake and routing
  12. Documenting common exception resolution templates
Module 6. Evaluating Human Oversight Needs
Determine which decisions must remain under human control and why.
12 chapters in this module
  1. Defining thresholds for human-in-the-loop requirements
  2. Classifying decisions by risk and reversibility
  3. Establishing criteria for escalation from agents
  4. Designing override mechanisms for agent actions
  5. Mapping judgment-dependent workflow branches
  6. Reviewing compliance requirements for human review
  7. Assessing customer sensitivity in automated responses
  8. Evaluating reputational risk of agent errors
  9. Determining auditability of agent decision trails
  10. Setting escalation response time expectations
  11. Identifying edge cases beyond agent training
  12. Creating feedback loops for agent performance
Module 7. Redefining Roles and Responsibilities
Update job scopes and team functions to reflect agent-augmented work.
12 chapters in this module
  1. Revising role descriptions to exclude automated tasks
  2. Designing new responsibilities around agent monitoring
  3. Updating performance metrics for changed workflows
  4. Creating agent supervision checklists
  5. Redefining escalation ownership and response duties
  6. Adjusting shift patterns based on agent coverage
  7. Reassigning staff from routine to complex tasks
  8. Developing career paths in an automated environment
  9. Updating onboarding for agent collaboration
  10. Aligning incentives with agent-handled outcomes
  11. Revising team dashboards for agent activity
  12. Establishing routines for agent performance review
Module 8. Designing Change Sequencing
Plan the rollout of AI agents to minimize disruption and build confidence.
12 chapters in this module
  1. Selecting pilot workflows for initial agent deployment
  2. Setting success criteria for early automation
  3. Building stakeholder communication timelines
  4. Creating parallel run protocols for validation
  5. Developing rollback procedures for agent failures
  6. Scheduling training for agent interaction
  7. Phasing agent introduction by process complexity
  8. Integrating agent metrics into management reports
  9. Coordinating cross-team alignment before launch
  10. Establishing feedback collection during rollout
  11. Adjusting timelines based on observed agent behavior
  12. Planning full integration based on pilot results
Module 9. Ensuring Accountability in Agent Systems
Maintain ownership of outcomes even when agents perform the work.
12 chapters in this module
  1. Defining ownership of agent-managed workflows
  2. Establishing clear audit trails for agent actions
  3. Creating escalation paths for unresolved agent issues
  4. Assigning human sponsors for agent performance
  5. Documenting decision logic used by agents
  6. Reviewing agent logs for compliance alignment
  7. Setting up regular oversight review meetings
  8. Developing agent incident response protocols
  9. Ensuring transparency in agent-driven decisions
  10. Maintaining version control for agent logic updates
  11. Reporting agent performance to governance bodies
  12. Updating risk registers to include agent dependencies
Module 10. Measuring Impact and Value
Track how agent integration affects efficiency, quality, and cost.
12 chapters in this module
  1. Defining KPIs for automated workflow performance
  2. Measuring time saved in cross-system coordination
  3. Tracking reduction in manual re-entry errors
  4. Calculating staffing impact of agent adoption
  5. Assessing customer satisfaction with faster resolution
  6. Evaluating first-contact resolution rates
  7. Monitoring agent uptime and reliability
  8. Reviewing cost per resolved ticket over time
  9. Analyzing workload redistribution across teams
  10. Benchmarking agent performance against human peers
  11. Calculating return on process automation efforts
  12. Reporting automation impact to executive leadership
Module 11. Scaling Across Functions
Extend agent integration beyond pilots to enterprise-wide operations.
12 chapters in this module
  1. Identifying common patterns across departments
  2. Standardizing agent interfaces for reuse
  3. Developing cross-functional agent governance
  4. Creating shared libraries of agent workflows
  5. Aligning security policies for agent access
  6. Establishing naming and tracking standards
  7. Building centralized monitoring dashboards
  8. Coordinating updates across agent instances
  9. Managing versioning of agent logic
  10. Scaling training for broader agent use
  11. Integrating agent data into enterprise reporting
  12. Planning capacity for growing agent deployments
Module 12. Leading the Future of Work Coordination
Shape the long-term evolution of human-agent collaboration in your organization.
12 chapters in this module
  1. Anticipating new coordination challenges with agents
  2. Designing hybrid human-agent decision frameworks
  3. Evolving leadership skills for agent oversight
  4. Preparing for fully autonomous workflow segments
  5. Rethinking service level agreements with agents
  6. Adapting culture to value oversight over execution
  7. Investing in agent performance analytics
  8. Balancing automation with human judgment
  9. Shaping ethical guidelines for agent behavior
  10. Guiding organizational identity in automated times
  11. Planning for continuous agent capability growth
  12. Defining your lasting impact on future workflows

Frequently asked

Who is this course for?
Senior leaders responsible for cross-functional workflows that involve routing, chasing, and re-keying data across systems with no single owner.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this course cover specific AI tools or platforms?
No. The course focuses on the work, not the vendors or technologies enabling automation.
Will I receive practical resources?
Yes. Each module includes downloadable templates and worked examples, plus a hand-built implementation playbook delivered at enrollment.
What if I need to pause the course?
Access remains available for 12 months, allowing you to learn at your own pace while applying concepts to your role.
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 completion over 12 weeks with practical application between modules..

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.
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