Role-Based Programme
RB1561

AI-Powered Project Controls & Reporting

Smarter Schedule Analysis, Performance Tracking & Management Reporting

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Project Controls and Reporting across schedule monitoring, progress tracking, variance analysis, forecasting, and reporting.
  • Apply AI-assisted techniques to analyse project data, milestone performance, costs, risks, issues, and corrective actions.
  • Use structured prompting for project-control reviews, schedule analysis, variance commentary, KPI reporting, and management summaries.
  • Explore AI-supported approaches for identifying schedule slippage, performance trends, reporting exceptions, and potential delivery risks.
  • Build responsible AI-assisted project-control workflows while maintaining data accuracy, traceability, governance, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisProject Controls AnalysisSchedule & Variance AnalysisReporting AIDashboard & Workflow Automation

Who should attend

  • Project Controls Analysts
  • Project Reporting Analysts
  • Project Controls Engineers
  • Planning & Controls Professionals
  • Project Analysts
  • PMO Analysts
  • Project Planning Professionals
  • Project Schedulers
  • Cost Control Analysts
  • Program Controls Professionals
  • Project Management Officers
  • Project Performance Analysts
  • Project Controls Managers
  • Project Controls & Reporting Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of Project Management, project controls, or reporting activities
  • Familiarity with schedules, milestones, progress data, cost information, risks, or status reports is helpful
  • Basic computer, spreadsheet, and document-handling skills
  • No AI or programming knowledge required
  • No previous AI training required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to project controls and reporting
  • Identifying AI applications across schedule monitoring, cost tracking, variance analysis, forecasting, and reporting
  • Understanding AI assistance versus Project Controls and Project Manager judgement
  • Recognising limitations such as incomplete data, inaccurate assumptions, and unsupported forecasts
Practical activities
  • Mapping a typical Project Controls & Reporting workflow
  • Identifying repetitive and information-intensive activities suitable for AI assistance
  • Comparing a traditional reporting task with an AI-assisted approach

Scenarios

Project Performance Data to Controls Review

Baseline Schedule + Actual Progress + Cost Data + RAID → AI Analysis → Variances → Delivery Risks → Corrective Actions → Controls Summary

Participants use AI to analyse sample project-control information, identify performance deviations and delivery concerns, and prepare a structured review for the Project Manager.

Monthly Project Data to Executive Report

Schedule + Cost + Milestones + Risks + Actions → AI-Assisted Analysis → Trends → Forecast Outlook → Exceptions → Executive Commentary → Management Report

Participants use AI to transform sample monthly project data into a concise management-ready project-controls report highlighting performance, risks, forecast concerns, and decisions required.

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