AI-Enhanced Operations Manager
AI-enhanced management training from DU&T Consulting.
Course overview
This course equips operations managers to use artificial intelligence to improve process visibility, service delivery, resource use and operational decision preparation. Participants examine practical applications in planning, workflow analysis, scheduling, quality and performance reporting.
The course emphasises evidence-based decisions, safe experimentation and accountable human oversight. No programming experience is required.
Learning objectives
- Identify operational processes where AI can create measurable value.
- Use AI to map workflows and identify bottlenecks, waste and delays.
- Support demand, capacity and resource planning with scenario analysis.
- Improve standard operating procedures, handovers and management reports.
- Use AI-assisted analysis for service, quality and performance monitoring.
- Evaluate automation opportunities, costs, risks and dependencies.
- Apply governance controls for accuracy, security and accountability.
- Develop a practical operations AI improvement roadmap.
Who should attend
Operations Managers; Service Delivery Managers; Business Process Managers; Logistics and Supply Chain Managers; Facilities Managers; Team Leaders; Continuous Improvement professionals; and managers responsible for operational performance.
Course modules
Module 1: AI Fundamentals for Operations
Capabilities, limitations and common operational use cases; identifying decisions that require human ownership.
Module 2: Process Mapping and Improvement
Documenting current workflows, finding bottlenecks and root causes, and generating improvement options for validation.
Module 3: Demand Capacity and Resource Planning
Using scenarios to examine workload, staffing, inventory and capacity assumptions without treating forecasts as guarantees.
Module 4: Scheduling Workflow and Coordination
Supporting work allocation, shift or task planning, handovers and cross-functional coordination.
Module 5: Quality Service and Customer Operations
Analysing recurring issues, drafting corrective actions and improving service consistency while verifying evidence.
Module 6: Operational Data and Performance Reporting
Summarising operational data, interpreting KPIs, preparing dashboards and management narratives, and checking data quality.
Module 7: Automation Risk and Governance
Assessing automation candidates, integration and supplier risks, cybersecurity, privacy, resilience, approvals and exception handling.
Module 8: Implementation and Continuous Improvement
Prioritising pilots, defining baselines and measures, managing change, learning from results and scaling responsibly.
Training methodology
Training uses interactive instruction, demonstrations, process-mapping workshops, operational case studies and scenario exercises.
Participants practise analysing fictional or authorised workflows, preparing improvement proposals and reviewing AI outputs against real operating constraints.
The course concludes with an operational improvement plan that defines the target process, expected benefit, resources, controls, owners and performance measures.