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PCI AIProject Controls
Institute Global, Inc.
Global Standards & Certification Body for Project Professionals
Curriculum

One syllabus, the whole discipline.

Thirteen domains, assessed together — 40 % project accounting & finance, 40 % project management principles, 20 % AI knowledge & practical approach. Sixty-one Knowledge Areas across the full framework, with AI embedded in every domain and treated systematically in Domain 13.

Project accounting & finance — 40 %

Domains 1–4 · the financial grammar of project controls.

01

Foundations of Accounting for Project Controls

  • 1.1 The accounting model
  • 1.2 Components of the financial statements
  • 1.3 Accrual accounting and the matching concept
  • 1.4 Cost provisions and cost accruals (IAS 37)
  • 1.5 Chart of accounts and cost coding for projects
  • AI in this domain — embedded coverage
02

Financial Reporting & the Standards

  • 2.1 The reporting framework
  • 2.2 IFRS 15 Revenue from Contracts with Customers — flagship
  • 2.3 Revenue recognition beyond the basics
  • 2.4 Other relevant standards for project controls
  • 2.5 Management reporting versus statutory reporting
  • AI in this domain — embedded coverage
03

Budgeting & Forecasting

  • 3.1 Budgeting fundamentals
  • 3.2 Cost estimation
  • 3.3 The time-phased budget / cost baseline (Planned Value)
  • 3.4 Forecasting
  • 3.5 Cash-flow forecasting
  • AI in this domain — embedded coverage
04

Performance Management, Variance Analysis & Management Reporting

  • 4.1 Performance management principles
  • 4.2 Variance analysis
  • 4.3 Management reporting
  • 4.4 Data visualisation and storytelling for controls
  • AI in this domain — embedded coverage

Project management principles — 40 %

Domains 5–12 · the delivery disciplines controls serves.

05

Cost Management & Cost Control

  • 5.1 The cost management framework
  • 5.2 The cost control cycle
  • 5.3 Cost breakdown and control accounts
  • 5.4 Change control and cost impact
  • AI in this domain — embedded coverage
06

Earned Value Management & Forecasting (EVM/EAC)

  • 6.1 EVM fundamentals
  • 6.2 Variances and performance indices
  • 6.3 Forecasting with EVM: the EAC family — the heart of the domain
  • 6.4 Integrating cost & schedule; limitations; earned schedule
  • AI in this domain — embedded coverage
07

Contracts, Commercial Management, BoQ, Invoicing & Revenue

  • 7.1 Types of contract
  • 7.2 Contract management
  • 7.3 Bills of Quantities (BoQ)
  • 7.4 Invoicing and applications for payment
  • 7.5 Revenue recognition in the commercial cycle
  • AI in this domain — embedded coverage
08

Project Management Lifecycle

  • 8.1 Initiating
  • 8.2 Planning
  • 8.3 Executing
  • 8.4 Monitoring & Controlling
  • 8.5 Closing
  • 8.6 Development approaches: predictive, iterative, incremental & adaptive
  • AI in this domain — embedded coverage
09

Agile, Scrum & Adaptive Delivery for Project Controls

  • 9.1 Agile foundations
  • 9.2 The Scrum framework in depth
  • 9.3 Backlogs, estimation and agile metrics
  • 9.4 Kanban, Lean and scaling
  • 9.5 Agile cost control, forecasting & earned value (AgileEVM)
  • 9.6 Hybrid delivery and agile governance
  • AI in this domain — embedded coverage
10

Project Scheduling

  • 10.1 Schedule development
  • 10.2 Network analysis and the Critical Path Method
  • 10.3 Schedule compression and resourcing
  • 10.4 Progress measurement and schedule control
  • AI in this domain — embedded coverage
11

Business Process Cycles (O2C, P2P & the control environment)

  • 11.1 Order-to-Cash (O2C)
  • 11.2 Procure-to-Pay (P2P)
  • 11.3 Internal control and segregation of duties
  • AI in this domain — embedded coverage
12

Risk Management for Project Controls

  • 12.1 The risk framework
  • 12.2 The risk process
  • 12.3 Contingency and management reserve
  • AI in this domain — embedded coverage

AI knowledge & practical approach — 20 %

Domain 13 · governed AI across the controls lifecycle.

13

AI for Project Controls & PM: Concepts, Tools & Practice

  • 13.1 AI foundations for professionals
  • 13.2 Data: the fuel
  • 13.3 Prompting and working with generative AI
  • 13.4 AI tool categories for project controls & PM
  • 13.5 AI applied across the project-controls lifecycle — the heart of the domain
  • 13.6 Governance, ethics, risk & assurance of AI
  • 13.7 Building an AI-augmented project-controls capability

AI is embedded across the framework. Every domain carries embedded “AI in this domain” coverage, shown in red, and Domain 13 carries the systematic treatment — concepts, data, prompting, tools, applied workflows and governance. Always governed by the principle that a competent human owns the result: AI proposes; the professional disposes.

Assessment

Tested on judgement, not recall.

Format

Scenario + applied task

Scenario-based items plus an applied analytical task — evaluate an AI forecast, or work a controls problem on real data — sampling the domains at the published 40/40/20 blueprint.

Standard

Criterion-referenced

A defensible cut score will be set by a modified-Angoff panel — not a fixed percentage — informed by a formal job-task analysis.

Currency

Three-year CPD

Recertification through continuing professional development, including a mandatory AI-currency component.

How the curriculum is organised

The curriculum is the thirteen-domain PCL-AI Body of Knowledge, organised in three groups — project accounting & finance (Domains 1–4), project management principles (Domains 5–12) and AI knowledge & practical approach (Domain 13) — treated as one integrated discipline, with governed AI woven through every domain rather than bolted on.

Accounting & finance

Domains 1–4 · 40 % — accounting, reporting, budgeting and performance.

Project management

Domains 5–12 · 40 % — cost, earned value, contracts, lifecycle, agile, scheduling, process cycles and risk.

AI knowledge & practice

Domain 13 · 20 % — concepts, data, tools, applied workflows and governance.

Governed throughout

AI proposes; the professional disposes — the principle runs across all thirteen domains.

The thirteen domains at a glance

Each domain is assessed as part of one integrated discipline. Together they describe what a capable project-controls professional can do today.

01
Accounting Foundations

The double-entry model, statements, accruals and cost coding.

02
Financial Reporting & the Standards

Revenue from contracts — IFRS 15 at its heart.

03
Budgeting & Forecasting

Estimates, baselines, forecasts and project cash flow.

04
Performance & Variance

Turning numbers into decisions — variances, KPIs, reporting.

05
Cost Management & Control

Commitments, accruals, actuals and control accounts.

06
Earned Value & Forecasting

The flagship: EV, indices and defensible EACs.

07
Contracts & Commercial

Contract types, BoQ, invoicing and revenue.

08
PM Lifecycle

Initiating to closing, and development approaches.

09
Agile & Adaptive Delivery

Scrum, Kanban, flow metrics and AgileEVM.

10
Project Scheduling

CPM in full — networks, float, compression and delay.

11
Business Process Cycles

O2C, P2P and the control environment.

12
Risk Management

Registers, quantification, contingency and reserve.

13
AI for Project Controls & PM

Concepts, tools and governed practice across the lifecycle.

Common questions

What does the curriculum cover?

Thirteen domains across sixty-one Knowledge Areas — project accounting & finance (Domains 1–4), project management principles (Domains 5–12) and AI knowledge & practical approach (Domain 13) — treated as one integrated whole.

Is AI part of it?

Yes — Domain 13 carries the systematic treatment of AI and 20 % of the examination blueprint, and every other domain carries embedded “AI in this domain” coverage, reflecting how controls work is now done.

Does completing a curriculum certify me?

No. The certification decision is independent and based on your assessed competence, not attendance on any course — and no preparation guarantees a pass. That separation between training and assessment is what makes the credential credible.

How current is it?

It is maintained rather than fixed, and is intended to keep pace as practice and AI evolve.

Study approach

How to work through the syllabus

The framework is examined as one integrated whole, but nobody studies thirteen domains at once. The domains have natural dependencies, and a study plan that respects them is far more efficient than working front to back.

Audit yourself first

Score yourself honestly against each of the 61 Knowledge Areas — strong, working, or weak. Most experienced practitioners find their gaps cluster in two or three domains, often the accounting and finance domains (1–4) or the AI domain (13), rather than the areas they use daily.

Follow the dependencies

Start with the finance domains — Domains 1–4 supply the accounting grammar the delivery domains assume. Take Domain 6 (earned value) before Domain 9, because AgileEVM builds directly on EVM. And weave Domain 13 through the whole plan rather than leaving AI to the end — its applied coverage draws on every other domain.

Practise integration early

The assessment rewards reasoning across domains, so do not leave mixed practice to the end. From the middle of your preparation onwards, work scenarios that force schedule, cost and risk thinking together.

The exam structure page explains how the assessment is organised, and the sample questions show the scenario style to expect.

Integrated thinking

One slip, seven domains

A worked example shows why the domains are assessed together rather than as separate modules. Suppose a critical procurement package slips by six weeks. A planner sees the network impact and re-runs the critical path (Domain 10). The earned-value analyst reads the same event as a schedule variance and a falling SPI (Domain 6). The cost engineer asks what standing time and re-mobilisation do to the estimate at completion (Domains 3 and 5). The risk lead checks whether the slip was already on the register and what it does to the quantitative model (Domain 12). Commercially, someone must establish whether the delay is compensable under the contract (Domain 7), and the reporting lead has to present all of this coherently to a decision-maker (Domain 4).

A candidate who can follow that whole chain — and knows where an AI-generated forecast helps and where it must be challenged (Domain 13) — is what the credential is designed to certify. Each Knowledge Area matters mostly for how it connects to the others, which is why the Body of Knowledge treats the discipline as one.

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