Mastering AI-Powered Business Process Automation with Dynamics 365
You're under pressure to deliver efficiency, cut costs, and future-proof your organisation. Manual processes are slowing you down. Stakeholders expect innovation, but you’re stuck navigating siloed systems and unclear implementation paths. The promise of AI is real, but the execution feels out of reach - too complex, too risky, too vague. What if you could confidently design, justify, and deploy AI-driven automation in your core business operations within weeks - not years? What if you could walk into any meeting with a fully developed, board-ready use case that leverages Microsoft Dynamics 365 and embedded AI to generate measurable ROI? The Mastering AI-Powered Business Process Automation with Dynamics 365 course is your blueprint for turning uncertainty into authority. This isn't theory. It's a proven, step-by-step system used by leading consultants and enterprise architects to identify high-impact automation opportunities, model intelligent workflows, and secure budget approval through data-backed proposals. One recent participant, Priya M, a Business Analyst at a Fortune 500 manufacturing firm, used the framework from this course to redesign their order-to-cash process. Her AI-enhanced automation map reduced processing time by 68%, identified $1.2M in annual operational savings, and earned her a promotion and seat at the digital transformation table within 60 days of completion. This course takes you from idea to fully justified, executable AI automation initiative in 30 days - complete with process analysis, cost-benefit modelling, risk assessment, and stakeholder communication plan. You’ll finish with a professional-grade, presentation-ready business case tailored to your actual work environment. Here’s how this course is structured to help you get there.Course Format & Delivery Details Self-Paced. Immediate Online Access. Zero Time Conflicts. This course is designed for working professionals who need flexibility without compromise. You receive self-paced, on-demand access to all materials, with no fixed schedules, live sessions, or deadlines. Start today, progress at your own speed, and complete the program in as little as 10–15 hours - or extend over weeks, fitting learning around your real-world commitments. Lifetime Access & Continuous Updates
You get lifetime access to the full curriculum, including all future updates at no additional cost. As Microsoft enhances Dynamics 365 and AI capabilities, you’ll receive updated methodologies, expanded use cases, and refined templates - automatically, with no action required. Accessible Anytime, Anywhere
All content is delivered in a responsive, mobile-friendly format. Access lessons, exercises, and resources from any device - laptop, tablet, or smartphone - across time zones and geographies. Whether you're in Dubai, Denver, or Düsseldorf, your progress is always synced and available 24/7. Direct Instructor Support & Expert Guidance
You’re not learning in isolation. This course includes direct access to our lead instructor - a certified Dynamics 365 solutions architect with over 15 years of enterprise automation experience. You can submit questions, get feedback on your use case drafts, and receive guidance on implementation challenges through our dedicated support channel. Full Transparency. No Hidden Costs.
Pricing is straightforward and all-inclusive. There are no subscription traps, hidden fees, or recurring charges. What you pay today is the only payment you’ll ever make. We accept all major payment methods including Visa, Mastercard, and PayPal, ensuring a frictionless enrollment experience. Strong Risk Reversal: 100% Satisfaction Guarantee
We offer a full satisfaction or refund guarantee. If you complete the first two modules and believe this course isn’t delivering the clarity, structure, and professional value promised, simply contact us for a prompt and no-questions-asked refund. Your investment is protected. Enrollment Confirmation & Access
After enrolling, you’ll receive an email confirmation of your registration. Your course access details and login credentials will be delivered separately once your enrollment is fully processed. This ensures all materials are optimally prepared for your learning journey. Will This Work for Me? Real Results Across Roles
This course is rigorously field-tested and built for practicality - not job titles. Whether you're a business analyst, operations manager, ERP consultant, project lead, or IT strategist, the frameworks are role-adaptable and domain-agnostic. Real testimonial: As an IT consultant with minimal AI exposure, I was nervous. This course gave me the structure to build my first automation proposal for a logistics client. They approved it, implemented it, and I billed $18,000 in new advisory work. The ROI was immediate. - Mark T, Solutions Consultant, Netherlands This works even if: You’ve never led an AI project, your organisation hasn’t adopted Dynamics 365 yet, you’re not technical, or you’ve been burned by overhyped tech training before. The step-by-step system removes complexity and replaces it with clarity, confidence, and concrete outputs. You gain not just knowledge, but proof of mastery. Upon completion, you’ll earn a professional Certificate of Completion issued by The Art of Service - a globally recognised credential trusted by thousands of professionals and organisations for upskilling, certification, and career advancement.
Module 1: Foundations of AI-Driven Business Automation - Understanding the evolution of process automation and AI convergence
- Differentiating RPA, workflow automation, and AI-powered decisioning
- Core capabilities of Microsoft Dynamics 365 in automation contexts
- Identifying business pain points ripe for intelligent automation
- Balancing innovation speed with organisational risk tolerance
- Introduction to cognitive services and AI Builder within Dynamics 365
- Establishing success criteria for automation initiatives
- Mapping current state versus future state processes
- Stakeholder alignment fundamentals for change adoption
- Principles of human-in-the-loop automation design
Module 2: Strategic Frameworks for AI Use Case Identification - Applying the Automation Opportunity Matrix to real business functions
- Using the 4D Framework: Discover, Diagnose, Design, Deploy
- Prioritising automation candidates using ROI, effort, and feasibility scoring
- Conducting cross-functional process audits to uncover inefficiencies
- Interview techniques for gathering process pain points from teams
- Documenting process flows using standardised notation
- Identifying high-frequency, rule-based processes for automation
- Leveraging waste elimination principles from Lean and Six Sigma
- Integrating AI opportunity scanning into quarterly business reviews
- Creating an enterprise-wide automation backlog
Module 3: Core Dynamics 365 Automation Tools & Features - Overview of Power Automate within Dynamics 365 ecosystems
- Configuring business rules and workflows in Dynamics 365
- Setting up real-time and scheduled workflows
- Understanding cloud flows versus desktop flows
- Using Common Data Service for automation data storage
- Configuring business process flows with conditional logic
- Implementing approval processes with escalation paths
- Automating data validation and field population
- Utilising recurrence triggers for daily reporting tasks
- Managing error handling and run history in automation logs
Module 4: Integrating AI with Process Automation - Introduction to AI Builder and prebuilt AI models
- Using document processing for invoice and form extraction
- Building and training custom AI models using labelled data
- Applying form processing models to capture structured data
- Implementing prediction models for forecasting outcomes
- Using object detection for asset or inventory tracking
- Applying text classification to categorise customer feedback
- Integrating AI model outputs into automated workflows
- Measuring model accuracy and confidence thresholds
- Updating and retraining AI models as data evolves
Module 5: Process Analysis & Data Mapping - Conducting time and touchpoint analysis of manual processes
- Quantifying costs of manual versus automated processes
- Creating swimlane diagrams to visualise handoffs and delays
- Mapping data sources, storage points, and transformation steps
- Identifying data quality issues impacting automation performance
- Standardising data formats for cross-system compatibility
- Designing data reconciliation and audit trails
- Establishing data governance protocols for automated systems
- Calculating process cycle times and bottleneck durations
- Documenting exception handling procedures
Module 6: Designing End-to-End Automation Workflows - Defining trigger conditions for automated actions
- Sequencing multi-step actions across departments
- Using parallel branches to increase efficiency
- Implementing conditional logic for decision paths
- Creating dynamic content for email and system integrations
- Linking approvals to workflow execution gates
- Automating document generation from data records
- Embedding AI decisions into workflow logic
- Validating data integrity at each step
- Designing error recovery and retry mechanisms
Module 7: System Integration & API Connectivity - Connecting Dynamics 365 to external systems via APIs
- Using HTTP actions to communicate with third-party platforms
- Authenticating integrations using OAuth, API keys, and service accounts
- Transforming JSON and XML payloads in workflows
- Handling rate limits and integration timeouts
- Pairing Dynamics 365 with SharePoint, Excel, and Teams
- Integrating with legacy ERP or CRM systems
- Building bidirectional data sync processes
- Testing integration reliability under load
- Monitoring integration health and failure alerts
Module 8: Security, Compliance & Risk Management - Implementing role-based access control in automated systems
- Ensuring audit trail compliance for regulatory requirements
- Applying data encryption in transit and at rest
- Mapping automation to GDPR, SOX, HIPAA, or industry-specific standards
- Conducting risk assessments for AI decisioning
- Documenting fallback procedures during automation failures
- Establishing ownership and monitoring accountability
- Deploying test environments to isolate production risks
- Creating rollback plans for failed automations
- Using activity logs for forensic analysis and compliance reporting
Module 9: Change Management & Stakeholder Engagement - Developing communication plans for automation rollouts
- Addressing workforce concerns about automation and job impact
- Training end users on new automated processes
- Creating super user networks for peer support
- Hosting process walkthroughs and simulation sessions
- Gathering feedback for continuous improvement
- Measuring user adoption rates post-implementation
- Using success stories to build momentum
- Aligning automation goals with departmental KPIs
- Reporting benefits realisation to executive leadership
Module 10: Measuring Business Impact & ROI - Designing baseline metrics before automation begins
- Calculating time savings per process instance
- Quantifying error reduction and rework elimination
- Estimating FTE capacity freed by automation
- Projecting annual cost savings across process volume
- Assessing improvements in customer satisfaction and SLAs
- Linking automation outcomes to revenue growth opportunities
- Using dashboards to visualise performance gains
- Calculating payback period for automation investments
- Building business cases using NPV and IRR models
Module 11: Building Your Board-Ready AI Business Case - Structuring a compelling executive summary
- Defining the problem and current-state inefficiencies
- Presenting the proposed automation solution with AI integration
- Outlining required resources and timeline
- Detailing risk mitigation strategies
- Showing projected ROI with sensitivity analysis
- Highlighting strategic alignment with digital goals
- Using visuals such as process flow diagrams and cost curves
- Incorporating stakeholder feedback into proposal
- Formatting for C-suite and board presentation standards
Module 12: Real-World Implementation Playbook - Phased rollout strategies: pilot, scale, enterprise
- Selecting departments or processes for initial deployment
- Setting up monitoring and alerting dashboards
- Establishing KPIs for ongoing performance tracking
- Running post-implementation reviews and retrospectives
- Iterating based on real-world usage data
- Documenting lessons learned and replication templates
- Scaling automation across business units
- Creating a Centre of Excellence for automation governance
- Securing budget renewal and expansion funding
Module 13: Advanced AI Optimisation Techniques - Using AI to predict process exceptions before they occur
- Applying reinforcement learning principles to workflow tuning
- Integrating sentiment analysis into customer service automation
- Using predictive maintenance models in asset-heavy industries
- Optimising routing logic based on historical performance
- Automating dynamic pricing decisions using forecasting models
- Enhancing lead scoring with AI-driven behavioural analysis
- Reducing churn through predictive intervention workflows
- Implementing adaptive learning loops for continuous AI improvement
- Using feedback signals to refine model accuracy over time
Module 14: Hands-On Project: Build Your Automation Initiative - Selecting a real or simulated business process for automation
- Conducting a discovery session with process owners
- Drafting a current-state process map with pain points
- Designing a future-state AI-powered workflow
- Identifying integration touchpoints and data sources
- Configuring a working automation prototype in a sandbox
- Incorporating AI Builder predictions or document processing
- Testing workflow logic and exception handling
- Gathering peer feedback on design and usability
- Refining based on evaluation insights
Module 15: Final Business Case Development & Certification - Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities
- Understanding the evolution of process automation and AI convergence
- Differentiating RPA, workflow automation, and AI-powered decisioning
- Core capabilities of Microsoft Dynamics 365 in automation contexts
- Identifying business pain points ripe for intelligent automation
- Balancing innovation speed with organisational risk tolerance
- Introduction to cognitive services and AI Builder within Dynamics 365
- Establishing success criteria for automation initiatives
- Mapping current state versus future state processes
- Stakeholder alignment fundamentals for change adoption
- Principles of human-in-the-loop automation design
Module 2: Strategic Frameworks for AI Use Case Identification - Applying the Automation Opportunity Matrix to real business functions
- Using the 4D Framework: Discover, Diagnose, Design, Deploy
- Prioritising automation candidates using ROI, effort, and feasibility scoring
- Conducting cross-functional process audits to uncover inefficiencies
- Interview techniques for gathering process pain points from teams
- Documenting process flows using standardised notation
- Identifying high-frequency, rule-based processes for automation
- Leveraging waste elimination principles from Lean and Six Sigma
- Integrating AI opportunity scanning into quarterly business reviews
- Creating an enterprise-wide automation backlog
Module 3: Core Dynamics 365 Automation Tools & Features - Overview of Power Automate within Dynamics 365 ecosystems
- Configuring business rules and workflows in Dynamics 365
- Setting up real-time and scheduled workflows
- Understanding cloud flows versus desktop flows
- Using Common Data Service for automation data storage
- Configuring business process flows with conditional logic
- Implementing approval processes with escalation paths
- Automating data validation and field population
- Utilising recurrence triggers for daily reporting tasks
- Managing error handling and run history in automation logs
Module 4: Integrating AI with Process Automation - Introduction to AI Builder and prebuilt AI models
- Using document processing for invoice and form extraction
- Building and training custom AI models using labelled data
- Applying form processing models to capture structured data
- Implementing prediction models for forecasting outcomes
- Using object detection for asset or inventory tracking
- Applying text classification to categorise customer feedback
- Integrating AI model outputs into automated workflows
- Measuring model accuracy and confidence thresholds
- Updating and retraining AI models as data evolves
Module 5: Process Analysis & Data Mapping - Conducting time and touchpoint analysis of manual processes
- Quantifying costs of manual versus automated processes
- Creating swimlane diagrams to visualise handoffs and delays
- Mapping data sources, storage points, and transformation steps
- Identifying data quality issues impacting automation performance
- Standardising data formats for cross-system compatibility
- Designing data reconciliation and audit trails
- Establishing data governance protocols for automated systems
- Calculating process cycle times and bottleneck durations
- Documenting exception handling procedures
Module 6: Designing End-to-End Automation Workflows - Defining trigger conditions for automated actions
- Sequencing multi-step actions across departments
- Using parallel branches to increase efficiency
- Implementing conditional logic for decision paths
- Creating dynamic content for email and system integrations
- Linking approvals to workflow execution gates
- Automating document generation from data records
- Embedding AI decisions into workflow logic
- Validating data integrity at each step
- Designing error recovery and retry mechanisms
Module 7: System Integration & API Connectivity - Connecting Dynamics 365 to external systems via APIs
- Using HTTP actions to communicate with third-party platforms
- Authenticating integrations using OAuth, API keys, and service accounts
- Transforming JSON and XML payloads in workflows
- Handling rate limits and integration timeouts
- Pairing Dynamics 365 with SharePoint, Excel, and Teams
- Integrating with legacy ERP or CRM systems
- Building bidirectional data sync processes
- Testing integration reliability under load
- Monitoring integration health and failure alerts
Module 8: Security, Compliance & Risk Management - Implementing role-based access control in automated systems
- Ensuring audit trail compliance for regulatory requirements
- Applying data encryption in transit and at rest
- Mapping automation to GDPR, SOX, HIPAA, or industry-specific standards
- Conducting risk assessments for AI decisioning
- Documenting fallback procedures during automation failures
- Establishing ownership and monitoring accountability
- Deploying test environments to isolate production risks
- Creating rollback plans for failed automations
- Using activity logs for forensic analysis and compliance reporting
Module 9: Change Management & Stakeholder Engagement - Developing communication plans for automation rollouts
- Addressing workforce concerns about automation and job impact
- Training end users on new automated processes
- Creating super user networks for peer support
- Hosting process walkthroughs and simulation sessions
- Gathering feedback for continuous improvement
- Measuring user adoption rates post-implementation
- Using success stories to build momentum
- Aligning automation goals with departmental KPIs
- Reporting benefits realisation to executive leadership
Module 10: Measuring Business Impact & ROI - Designing baseline metrics before automation begins
- Calculating time savings per process instance
- Quantifying error reduction and rework elimination
- Estimating FTE capacity freed by automation
- Projecting annual cost savings across process volume
- Assessing improvements in customer satisfaction and SLAs
- Linking automation outcomes to revenue growth opportunities
- Using dashboards to visualise performance gains
- Calculating payback period for automation investments
- Building business cases using NPV and IRR models
Module 11: Building Your Board-Ready AI Business Case - Structuring a compelling executive summary
- Defining the problem and current-state inefficiencies
- Presenting the proposed automation solution with AI integration
- Outlining required resources and timeline
- Detailing risk mitigation strategies
- Showing projected ROI with sensitivity analysis
- Highlighting strategic alignment with digital goals
- Using visuals such as process flow diagrams and cost curves
- Incorporating stakeholder feedback into proposal
- Formatting for C-suite and board presentation standards
Module 12: Real-World Implementation Playbook - Phased rollout strategies: pilot, scale, enterprise
- Selecting departments or processes for initial deployment
- Setting up monitoring and alerting dashboards
- Establishing KPIs for ongoing performance tracking
- Running post-implementation reviews and retrospectives
- Iterating based on real-world usage data
- Documenting lessons learned and replication templates
- Scaling automation across business units
- Creating a Centre of Excellence for automation governance
- Securing budget renewal and expansion funding
Module 13: Advanced AI Optimisation Techniques - Using AI to predict process exceptions before they occur
- Applying reinforcement learning principles to workflow tuning
- Integrating sentiment analysis into customer service automation
- Using predictive maintenance models in asset-heavy industries
- Optimising routing logic based on historical performance
- Automating dynamic pricing decisions using forecasting models
- Enhancing lead scoring with AI-driven behavioural analysis
- Reducing churn through predictive intervention workflows
- Implementing adaptive learning loops for continuous AI improvement
- Using feedback signals to refine model accuracy over time
Module 14: Hands-On Project: Build Your Automation Initiative - Selecting a real or simulated business process for automation
- Conducting a discovery session with process owners
- Drafting a current-state process map with pain points
- Designing a future-state AI-powered workflow
- Identifying integration touchpoints and data sources
- Configuring a working automation prototype in a sandbox
- Incorporating AI Builder predictions or document processing
- Testing workflow logic and exception handling
- Gathering peer feedback on design and usability
- Refining based on evaluation insights
Module 15: Final Business Case Development & Certification - Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities
- Overview of Power Automate within Dynamics 365 ecosystems
- Configuring business rules and workflows in Dynamics 365
- Setting up real-time and scheduled workflows
- Understanding cloud flows versus desktop flows
- Using Common Data Service for automation data storage
- Configuring business process flows with conditional logic
- Implementing approval processes with escalation paths
- Automating data validation and field population
- Utilising recurrence triggers for daily reporting tasks
- Managing error handling and run history in automation logs
Module 4: Integrating AI with Process Automation - Introduction to AI Builder and prebuilt AI models
- Using document processing for invoice and form extraction
- Building and training custom AI models using labelled data
- Applying form processing models to capture structured data
- Implementing prediction models for forecasting outcomes
- Using object detection for asset or inventory tracking
- Applying text classification to categorise customer feedback
- Integrating AI model outputs into automated workflows
- Measuring model accuracy and confidence thresholds
- Updating and retraining AI models as data evolves
Module 5: Process Analysis & Data Mapping - Conducting time and touchpoint analysis of manual processes
- Quantifying costs of manual versus automated processes
- Creating swimlane diagrams to visualise handoffs and delays
- Mapping data sources, storage points, and transformation steps
- Identifying data quality issues impacting automation performance
- Standardising data formats for cross-system compatibility
- Designing data reconciliation and audit trails
- Establishing data governance protocols for automated systems
- Calculating process cycle times and bottleneck durations
- Documenting exception handling procedures
Module 6: Designing End-to-End Automation Workflows - Defining trigger conditions for automated actions
- Sequencing multi-step actions across departments
- Using parallel branches to increase efficiency
- Implementing conditional logic for decision paths
- Creating dynamic content for email and system integrations
- Linking approvals to workflow execution gates
- Automating document generation from data records
- Embedding AI decisions into workflow logic
- Validating data integrity at each step
- Designing error recovery and retry mechanisms
Module 7: System Integration & API Connectivity - Connecting Dynamics 365 to external systems via APIs
- Using HTTP actions to communicate with third-party platforms
- Authenticating integrations using OAuth, API keys, and service accounts
- Transforming JSON and XML payloads in workflows
- Handling rate limits and integration timeouts
- Pairing Dynamics 365 with SharePoint, Excel, and Teams
- Integrating with legacy ERP or CRM systems
- Building bidirectional data sync processes
- Testing integration reliability under load
- Monitoring integration health and failure alerts
Module 8: Security, Compliance & Risk Management - Implementing role-based access control in automated systems
- Ensuring audit trail compliance for regulatory requirements
- Applying data encryption in transit and at rest
- Mapping automation to GDPR, SOX, HIPAA, or industry-specific standards
- Conducting risk assessments for AI decisioning
- Documenting fallback procedures during automation failures
- Establishing ownership and monitoring accountability
- Deploying test environments to isolate production risks
- Creating rollback plans for failed automations
- Using activity logs for forensic analysis and compliance reporting
Module 9: Change Management & Stakeholder Engagement - Developing communication plans for automation rollouts
- Addressing workforce concerns about automation and job impact
- Training end users on new automated processes
- Creating super user networks for peer support
- Hosting process walkthroughs and simulation sessions
- Gathering feedback for continuous improvement
- Measuring user adoption rates post-implementation
- Using success stories to build momentum
- Aligning automation goals with departmental KPIs
- Reporting benefits realisation to executive leadership
Module 10: Measuring Business Impact & ROI - Designing baseline metrics before automation begins
- Calculating time savings per process instance
- Quantifying error reduction and rework elimination
- Estimating FTE capacity freed by automation
- Projecting annual cost savings across process volume
- Assessing improvements in customer satisfaction and SLAs
- Linking automation outcomes to revenue growth opportunities
- Using dashboards to visualise performance gains
- Calculating payback period for automation investments
- Building business cases using NPV and IRR models
Module 11: Building Your Board-Ready AI Business Case - Structuring a compelling executive summary
- Defining the problem and current-state inefficiencies
- Presenting the proposed automation solution with AI integration
- Outlining required resources and timeline
- Detailing risk mitigation strategies
- Showing projected ROI with sensitivity analysis
- Highlighting strategic alignment with digital goals
- Using visuals such as process flow diagrams and cost curves
- Incorporating stakeholder feedback into proposal
- Formatting for C-suite and board presentation standards
Module 12: Real-World Implementation Playbook - Phased rollout strategies: pilot, scale, enterprise
- Selecting departments or processes for initial deployment
- Setting up monitoring and alerting dashboards
- Establishing KPIs for ongoing performance tracking
- Running post-implementation reviews and retrospectives
- Iterating based on real-world usage data
- Documenting lessons learned and replication templates
- Scaling automation across business units
- Creating a Centre of Excellence for automation governance
- Securing budget renewal and expansion funding
Module 13: Advanced AI Optimisation Techniques - Using AI to predict process exceptions before they occur
- Applying reinforcement learning principles to workflow tuning
- Integrating sentiment analysis into customer service automation
- Using predictive maintenance models in asset-heavy industries
- Optimising routing logic based on historical performance
- Automating dynamic pricing decisions using forecasting models
- Enhancing lead scoring with AI-driven behavioural analysis
- Reducing churn through predictive intervention workflows
- Implementing adaptive learning loops for continuous AI improvement
- Using feedback signals to refine model accuracy over time
Module 14: Hands-On Project: Build Your Automation Initiative - Selecting a real or simulated business process for automation
- Conducting a discovery session with process owners
- Drafting a current-state process map with pain points
- Designing a future-state AI-powered workflow
- Identifying integration touchpoints and data sources
- Configuring a working automation prototype in a sandbox
- Incorporating AI Builder predictions or document processing
- Testing workflow logic and exception handling
- Gathering peer feedback on design and usability
- Refining based on evaluation insights
Module 15: Final Business Case Development & Certification - Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities
- Conducting time and touchpoint analysis of manual processes
- Quantifying costs of manual versus automated processes
- Creating swimlane diagrams to visualise handoffs and delays
- Mapping data sources, storage points, and transformation steps
- Identifying data quality issues impacting automation performance
- Standardising data formats for cross-system compatibility
- Designing data reconciliation and audit trails
- Establishing data governance protocols for automated systems
- Calculating process cycle times and bottleneck durations
- Documenting exception handling procedures
Module 6: Designing End-to-End Automation Workflows - Defining trigger conditions for automated actions
- Sequencing multi-step actions across departments
- Using parallel branches to increase efficiency
- Implementing conditional logic for decision paths
- Creating dynamic content for email and system integrations
- Linking approvals to workflow execution gates
- Automating document generation from data records
- Embedding AI decisions into workflow logic
- Validating data integrity at each step
- Designing error recovery and retry mechanisms
Module 7: System Integration & API Connectivity - Connecting Dynamics 365 to external systems via APIs
- Using HTTP actions to communicate with third-party platforms
- Authenticating integrations using OAuth, API keys, and service accounts
- Transforming JSON and XML payloads in workflows
- Handling rate limits and integration timeouts
- Pairing Dynamics 365 with SharePoint, Excel, and Teams
- Integrating with legacy ERP or CRM systems
- Building bidirectional data sync processes
- Testing integration reliability under load
- Monitoring integration health and failure alerts
Module 8: Security, Compliance & Risk Management - Implementing role-based access control in automated systems
- Ensuring audit trail compliance for regulatory requirements
- Applying data encryption in transit and at rest
- Mapping automation to GDPR, SOX, HIPAA, or industry-specific standards
- Conducting risk assessments for AI decisioning
- Documenting fallback procedures during automation failures
- Establishing ownership and monitoring accountability
- Deploying test environments to isolate production risks
- Creating rollback plans for failed automations
- Using activity logs for forensic analysis and compliance reporting
Module 9: Change Management & Stakeholder Engagement - Developing communication plans for automation rollouts
- Addressing workforce concerns about automation and job impact
- Training end users on new automated processes
- Creating super user networks for peer support
- Hosting process walkthroughs and simulation sessions
- Gathering feedback for continuous improvement
- Measuring user adoption rates post-implementation
- Using success stories to build momentum
- Aligning automation goals with departmental KPIs
- Reporting benefits realisation to executive leadership
Module 10: Measuring Business Impact & ROI - Designing baseline metrics before automation begins
- Calculating time savings per process instance
- Quantifying error reduction and rework elimination
- Estimating FTE capacity freed by automation
- Projecting annual cost savings across process volume
- Assessing improvements in customer satisfaction and SLAs
- Linking automation outcomes to revenue growth opportunities
- Using dashboards to visualise performance gains
- Calculating payback period for automation investments
- Building business cases using NPV and IRR models
Module 11: Building Your Board-Ready AI Business Case - Structuring a compelling executive summary
- Defining the problem and current-state inefficiencies
- Presenting the proposed automation solution with AI integration
- Outlining required resources and timeline
- Detailing risk mitigation strategies
- Showing projected ROI with sensitivity analysis
- Highlighting strategic alignment with digital goals
- Using visuals such as process flow diagrams and cost curves
- Incorporating stakeholder feedback into proposal
- Formatting for C-suite and board presentation standards
Module 12: Real-World Implementation Playbook - Phased rollout strategies: pilot, scale, enterprise
- Selecting departments or processes for initial deployment
- Setting up monitoring and alerting dashboards
- Establishing KPIs for ongoing performance tracking
- Running post-implementation reviews and retrospectives
- Iterating based on real-world usage data
- Documenting lessons learned and replication templates
- Scaling automation across business units
- Creating a Centre of Excellence for automation governance
- Securing budget renewal and expansion funding
Module 13: Advanced AI Optimisation Techniques - Using AI to predict process exceptions before they occur
- Applying reinforcement learning principles to workflow tuning
- Integrating sentiment analysis into customer service automation
- Using predictive maintenance models in asset-heavy industries
- Optimising routing logic based on historical performance
- Automating dynamic pricing decisions using forecasting models
- Enhancing lead scoring with AI-driven behavioural analysis
- Reducing churn through predictive intervention workflows
- Implementing adaptive learning loops for continuous AI improvement
- Using feedback signals to refine model accuracy over time
Module 14: Hands-On Project: Build Your Automation Initiative - Selecting a real or simulated business process for automation
- Conducting a discovery session with process owners
- Drafting a current-state process map with pain points
- Designing a future-state AI-powered workflow
- Identifying integration touchpoints and data sources
- Configuring a working automation prototype in a sandbox
- Incorporating AI Builder predictions or document processing
- Testing workflow logic and exception handling
- Gathering peer feedback on design and usability
- Refining based on evaluation insights
Module 15: Final Business Case Development & Certification - Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities
- Connecting Dynamics 365 to external systems via APIs
- Using HTTP actions to communicate with third-party platforms
- Authenticating integrations using OAuth, API keys, and service accounts
- Transforming JSON and XML payloads in workflows
- Handling rate limits and integration timeouts
- Pairing Dynamics 365 with SharePoint, Excel, and Teams
- Integrating with legacy ERP or CRM systems
- Building bidirectional data sync processes
- Testing integration reliability under load
- Monitoring integration health and failure alerts
Module 8: Security, Compliance & Risk Management - Implementing role-based access control in automated systems
- Ensuring audit trail compliance for regulatory requirements
- Applying data encryption in transit and at rest
- Mapping automation to GDPR, SOX, HIPAA, or industry-specific standards
- Conducting risk assessments for AI decisioning
- Documenting fallback procedures during automation failures
- Establishing ownership and monitoring accountability
- Deploying test environments to isolate production risks
- Creating rollback plans for failed automations
- Using activity logs for forensic analysis and compliance reporting
Module 9: Change Management & Stakeholder Engagement - Developing communication plans for automation rollouts
- Addressing workforce concerns about automation and job impact
- Training end users on new automated processes
- Creating super user networks for peer support
- Hosting process walkthroughs and simulation sessions
- Gathering feedback for continuous improvement
- Measuring user adoption rates post-implementation
- Using success stories to build momentum
- Aligning automation goals with departmental KPIs
- Reporting benefits realisation to executive leadership
Module 10: Measuring Business Impact & ROI - Designing baseline metrics before automation begins
- Calculating time savings per process instance
- Quantifying error reduction and rework elimination
- Estimating FTE capacity freed by automation
- Projecting annual cost savings across process volume
- Assessing improvements in customer satisfaction and SLAs
- Linking automation outcomes to revenue growth opportunities
- Using dashboards to visualise performance gains
- Calculating payback period for automation investments
- Building business cases using NPV and IRR models
Module 11: Building Your Board-Ready AI Business Case - Structuring a compelling executive summary
- Defining the problem and current-state inefficiencies
- Presenting the proposed automation solution with AI integration
- Outlining required resources and timeline
- Detailing risk mitigation strategies
- Showing projected ROI with sensitivity analysis
- Highlighting strategic alignment with digital goals
- Using visuals such as process flow diagrams and cost curves
- Incorporating stakeholder feedback into proposal
- Formatting for C-suite and board presentation standards
Module 12: Real-World Implementation Playbook - Phased rollout strategies: pilot, scale, enterprise
- Selecting departments or processes for initial deployment
- Setting up monitoring and alerting dashboards
- Establishing KPIs for ongoing performance tracking
- Running post-implementation reviews and retrospectives
- Iterating based on real-world usage data
- Documenting lessons learned and replication templates
- Scaling automation across business units
- Creating a Centre of Excellence for automation governance
- Securing budget renewal and expansion funding
Module 13: Advanced AI Optimisation Techniques - Using AI to predict process exceptions before they occur
- Applying reinforcement learning principles to workflow tuning
- Integrating sentiment analysis into customer service automation
- Using predictive maintenance models in asset-heavy industries
- Optimising routing logic based on historical performance
- Automating dynamic pricing decisions using forecasting models
- Enhancing lead scoring with AI-driven behavioural analysis
- Reducing churn through predictive intervention workflows
- Implementing adaptive learning loops for continuous AI improvement
- Using feedback signals to refine model accuracy over time
Module 14: Hands-On Project: Build Your Automation Initiative - Selecting a real or simulated business process for automation
- Conducting a discovery session with process owners
- Drafting a current-state process map with pain points
- Designing a future-state AI-powered workflow
- Identifying integration touchpoints and data sources
- Configuring a working automation prototype in a sandbox
- Incorporating AI Builder predictions or document processing
- Testing workflow logic and exception handling
- Gathering peer feedback on design and usability
- Refining based on evaluation insights
Module 15: Final Business Case Development & Certification - Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities
- Developing communication plans for automation rollouts
- Addressing workforce concerns about automation and job impact
- Training end users on new automated processes
- Creating super user networks for peer support
- Hosting process walkthroughs and simulation sessions
- Gathering feedback for continuous improvement
- Measuring user adoption rates post-implementation
- Using success stories to build momentum
- Aligning automation goals with departmental KPIs
- Reporting benefits realisation to executive leadership
Module 10: Measuring Business Impact & ROI - Designing baseline metrics before automation begins
- Calculating time savings per process instance
- Quantifying error reduction and rework elimination
- Estimating FTE capacity freed by automation
- Projecting annual cost savings across process volume
- Assessing improvements in customer satisfaction and SLAs
- Linking automation outcomes to revenue growth opportunities
- Using dashboards to visualise performance gains
- Calculating payback period for automation investments
- Building business cases using NPV and IRR models
Module 11: Building Your Board-Ready AI Business Case - Structuring a compelling executive summary
- Defining the problem and current-state inefficiencies
- Presenting the proposed automation solution with AI integration
- Outlining required resources and timeline
- Detailing risk mitigation strategies
- Showing projected ROI with sensitivity analysis
- Highlighting strategic alignment with digital goals
- Using visuals such as process flow diagrams and cost curves
- Incorporating stakeholder feedback into proposal
- Formatting for C-suite and board presentation standards
Module 12: Real-World Implementation Playbook - Phased rollout strategies: pilot, scale, enterprise
- Selecting departments or processes for initial deployment
- Setting up monitoring and alerting dashboards
- Establishing KPIs for ongoing performance tracking
- Running post-implementation reviews and retrospectives
- Iterating based on real-world usage data
- Documenting lessons learned and replication templates
- Scaling automation across business units
- Creating a Centre of Excellence for automation governance
- Securing budget renewal and expansion funding
Module 13: Advanced AI Optimisation Techniques - Using AI to predict process exceptions before they occur
- Applying reinforcement learning principles to workflow tuning
- Integrating sentiment analysis into customer service automation
- Using predictive maintenance models in asset-heavy industries
- Optimising routing logic based on historical performance
- Automating dynamic pricing decisions using forecasting models
- Enhancing lead scoring with AI-driven behavioural analysis
- Reducing churn through predictive intervention workflows
- Implementing adaptive learning loops for continuous AI improvement
- Using feedback signals to refine model accuracy over time
Module 14: Hands-On Project: Build Your Automation Initiative - Selecting a real or simulated business process for automation
- Conducting a discovery session with process owners
- Drafting a current-state process map with pain points
- Designing a future-state AI-powered workflow
- Identifying integration touchpoints and data sources
- Configuring a working automation prototype in a sandbox
- Incorporating AI Builder predictions or document processing
- Testing workflow logic and exception handling
- Gathering peer feedback on design and usability
- Refining based on evaluation insights
Module 15: Final Business Case Development & Certification - Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities
- Structuring a compelling executive summary
- Defining the problem and current-state inefficiencies
- Presenting the proposed automation solution with AI integration
- Outlining required resources and timeline
- Detailing risk mitigation strategies
- Showing projected ROI with sensitivity analysis
- Highlighting strategic alignment with digital goals
- Using visuals such as process flow diagrams and cost curves
- Incorporating stakeholder feedback into proposal
- Formatting for C-suite and board presentation standards
Module 12: Real-World Implementation Playbook - Phased rollout strategies: pilot, scale, enterprise
- Selecting departments or processes for initial deployment
- Setting up monitoring and alerting dashboards
- Establishing KPIs for ongoing performance tracking
- Running post-implementation reviews and retrospectives
- Iterating based on real-world usage data
- Documenting lessons learned and replication templates
- Scaling automation across business units
- Creating a Centre of Excellence for automation governance
- Securing budget renewal and expansion funding
Module 13: Advanced AI Optimisation Techniques - Using AI to predict process exceptions before they occur
- Applying reinforcement learning principles to workflow tuning
- Integrating sentiment analysis into customer service automation
- Using predictive maintenance models in asset-heavy industries
- Optimising routing logic based on historical performance
- Automating dynamic pricing decisions using forecasting models
- Enhancing lead scoring with AI-driven behavioural analysis
- Reducing churn through predictive intervention workflows
- Implementing adaptive learning loops for continuous AI improvement
- Using feedback signals to refine model accuracy over time
Module 14: Hands-On Project: Build Your Automation Initiative - Selecting a real or simulated business process for automation
- Conducting a discovery session with process owners
- Drafting a current-state process map with pain points
- Designing a future-state AI-powered workflow
- Identifying integration touchpoints and data sources
- Configuring a working automation prototype in a sandbox
- Incorporating AI Builder predictions or document processing
- Testing workflow logic and exception handling
- Gathering peer feedback on design and usability
- Refining based on evaluation insights
Module 15: Final Business Case Development & Certification - Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities
- Using AI to predict process exceptions before they occur
- Applying reinforcement learning principles to workflow tuning
- Integrating sentiment analysis into customer service automation
- Using predictive maintenance models in asset-heavy industries
- Optimising routing logic based on historical performance
- Automating dynamic pricing decisions using forecasting models
- Enhancing lead scoring with AI-driven behavioural analysis
- Reducing churn through predictive intervention workflows
- Implementing adaptive learning loops for continuous AI improvement
- Using feedback signals to refine model accuracy over time
Module 14: Hands-On Project: Build Your Automation Initiative - Selecting a real or simulated business process for automation
- Conducting a discovery session with process owners
- Drafting a current-state process map with pain points
- Designing a future-state AI-powered workflow
- Identifying integration touchpoints and data sources
- Configuring a working automation prototype in a sandbox
- Incorporating AI Builder predictions or document processing
- Testing workflow logic and exception handling
- Gathering peer feedback on design and usability
- Refining based on evaluation insights
Module 15: Final Business Case Development & Certification - Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities
- Finalising your board-ready automation proposal
- Polishing financial models and visual presentations
- Rehearsing delivery and anticipating executive questions
- Submitting your project for review
- Receiving structured feedback from expert evaluators
- Implementing final refinements
- Uploading your completed business case
- Earning your Certificate of Completion issued by The Art of Service
- Accessing your shareable digital credential
- Joining the alumni network for ongoing learning and opportunities