Case Study: Project management in construction using AI (pre-development stage)

Marina Melnick
02 April 2026

Client: LLC “ZARS”
Format: corporate consulting
Subject: Project management in construction
Duration: 28 hours
Coach: Marina Melnik

Context

Construction projects are complex systems with a large number of participants, dependencies, and risks.

Key decisions regarding:

  • deadlines and budget
  • volume and quality of work
  • architectural and technical approaches
  • development planning and organization
  • are accepted at the predevelopment stage.

At the same time:

  • Mistakes in the early stages are the most expensive
  • lack of a systematic approach leads to delays and cost overruns
  • classic planning approaches do not provide sufficient flexibility

Task

  • to form a systematic approach to construction project management even before the start of implementation
  • structure the future project (stages, dependencies, roles)
  • practice key PM tools on a real case
  • integrate AI into planning, analysis and decision-making processes

Decision

A practical project management program was implemented, where all tools were immediately applied to a real project at the pre-development stage.

The focus of the work:

Project structuring

  • formation of requirements and design documentation
  • building a WBS (work breakdown structure)
  • definition of stages and execution logic

Planning

  • calendar and network planning
  • critical path definition
  • coordination of contractors' work

Budget and control

  • budget structure
  • control of changes and deviations
  • cost management approach

Communication and management

  • working with stakeholders
  • building a communication model
  • coordination of project participants

Risks and changes

  • risk identification
  • construction of a risk matrix
  • project change management

Using AI in the project

AI has been used as a tool to enhance management decisions:

  • structuring complex tasks and documentation
  • analysis of dependencies between stages
  • preparation of solution options
  • rapid development of scenarios (“what-if”)
  • support in working with documents and communications

The focus was not on generation, but onenhancing thinking and decision-making speed

Result

The program included:

  • the project is structured before the start of implementation
  • the logic of work execution and key dependencies have been formed
  • potential risks identified at an early stage
  • an approach to budget and change management is laid out
  • a systemic vision of project implementation has been formed

The use of AI has enabled the project manager to see how to analyze options faster; identify risks in advance; make more informed decisions; improve quality by establishing clear criteria before construction begins; and reduce the potential for changes, cost overruns, and delays.