AI Training for Construction & Infrastructure

How can project, commercial and asset teams use AI while keeping control of capital project decisions?

Excentra AI Academy’s AI training courses for construction and infrastructure professionals focus on using project information to make better-informed decisions. A design revision can affect quantities, procurement and the construction schedule. AI can help teams trace those implications across drawings, contracts and progress records so the people responsible can check the evidence before acting.

The training is designed for contractors, consultants, developers, asset owners and infrastructure operators. It connects AI to the decisions teams make across a capital project, from reviewing tender information and monitoring delivery to handing over asset records and planning maintenance.

In short

AI training for the construction and infrastructure sector helps professionals use drawings, contracts, schedules and site records to assess cost, progress and risk. A quantity surveyor might use AI to compare a revised specification with a cost plan. A planner might use it to flag work packages at risk of delay. At handover, an asset team can use AI to identify missing records before relying on them for maintenance planning.

Where AI is used in Construction & Infrastructure

01

Document and contract intelligence

Extract notice dates and obligations from contract documents, compare drawing or specification revisions and trace each finding to its source.

02

Schedule and cost forecasting

Use actual progress, productivity records and cost data to update forecasts and identify activities or work packages that need closer review.

03

Project controls and claims

Organise change records, site diaries and correspondence into a timeline so project and commercial teams can assess the evidence behind a variation or delay.

04

Survey, geospatial and site monitoring

Analyse drone imagery, point clouds and geospatial data to identify changes in site conditions or compare observed progress with planned work.

05

Design review and planning

Screen designs against selected requirements, flag discrepancies between revisions and compare planning options for engineering review.

06

Facilities and asset management

Use inspection records, maintenance history and sensor data to identify assets that may need attention and inform renewal planning.

AI Product Development for Business Leaders

From AI Opportunities and Product Strategy to Development, Governance & Scalable Business Value

5 days · Live online · In-house available

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Artificial Intelligence (AI) for Enhanced Maintenance & Reliability Engineering

Transforming Asset Performance, Predictive Maintenance, and Reliability Strategies Through Intelligent Automation

5 days · Classroom or live online · In-house available

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Artificial Intelligence (AI) for Instrumentation Optimization

Applying AI to Maximize Instrumentation Efficiency, Reliability, and Performance

5 days · Classroom or live online · In-house available

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Artificial Intelligence (AI) in Asset Lifecycle Management

Optimizing Asset Strategy, Reliability, and Value Through Intelligent Technologies

5 days · Classroom or live online · In-house available

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Artificial Intelligence (AI) in Project Management

Insight in Action: AI as a Catalyst for Real-Time Project Decision-Making

5 days · Classroom or live online · In-house available

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Artificial Intelligence (AI) in Real Estate Development and Facilities

Transforming Real Estate Design, Operations, and Management with Intelligent Technologies

5 days · Classroom or live online · In-house available

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Who attends

Project directors and developers: Project directors and developers who decide where AI can support capital project delivery and who approves its use.
Contracts, commercial and claims teams: Contracts, commercial and claims teams, including quantity surveyors and contract administrators who manage valuations, variations and project records.
Planners, project controls and estimators: Planners, project controls and estimators who assess schedule changes, cost forecasts and work package performance.
Surveyors, engineers and facilities managers: Surveyors, engineers and facilities managers who work with site data, design information, handover records and asset condition data.

Standards the courses draw on

These learning references connect AI use with established practices for managing project information, assets and risk.

  • ISO 19650 series. Information management using building information modelling (BIM) across the lifecycle of buildings and infrastructure. 
  • ISO 55000. Asset management concepts and principles that provide context for decisions about asset value, performance and lifecycle planning. committee.
  • ISO 21500. The organisational context and concepts for managing projects and portfolios. Standard forms of contract can provide separate context for examples involving notices, obligations and changes. 
  • ISO/IEC 42001 and the NIST AI Risk Management Framework. References for establishing an AI management system and assessing and managing the risks of AI use. 

In-house training for construction & infrastructure teams

In-house training for construction teams: Excentra AI Academy can tailor training for contractors, consultants and client teams working on the same capital project or across a portfolio. Your team can focus on a shared workflow, such as reviewing design changes, updating a cost forecast or checking asset information before handover. Exercises can reflect your approved document types and review procedures.

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How can construction teams use AI to manage capital projects?

Construction teams can use AI to flag schedule risks, compare forecasts with actual progress and summarise changes across drawings and site records. For example, a planner can review work packages showing lower-than-expected productivity, check the underlying progress data and assess whether the completion forecast needs to change.

What should AI training for quantity surveyors and contract managers cover?

AI training for quantity surveyors and contract managers should cover how to extract information from project documents, compare quantities and cost assumptions, and organise evidence for valuations and variations. It should also show how to verify an AI-generated finding against the approved drawing, the relevant contract clause or the original site record.

Frequently asked questions

AI can extract notice dates, organise records by event and flag gaps in the evidence supporting a variation or delay claim. The contracts team checks those findings against the agreed terms, approved changes and contemporaneous records before deciding what action to take.

Land surveyors can use AI to classify features in drone imagery or point clouds and flag changes between successive site surveys. Survey teams verify those results against survey control, source imagery and field observations before using them for measurements or reporting progress.

AI can use information from a BIM model to flag inconsistent asset records or compare model quantities with project data. When a digital twin receives operating data, AI can also highlight unusual readings for investigation. The value of either use depends on the quality and currency of the underlying information.

Yes. A shared handover scenario helps developers and facilities teams agree which asset records must be complete, who verifies them and how gaps are resolved. For example, both teams can use AI to flag missing maintenance instructions and check the results against the agreed handover requirements.

Many practical tasks, including comparing drawing revisions, summarising site reports and checking cost inputs, can be carried out without writing code. Building custom forecasting models or integrating AI with project systems may require programming or specialist technical support.

Find the AI training your construction & infrastructure team needs