Mentioned in 36 AI use cases across 6 industries
Comments and markups made in Bluebeam on drawings can be shown inside the submittal record so reviewers can see what was marked up, by whom, and on which page.
When a construction document needs an updated version, the system copies the old one, bumps the revision number, lets the team edit key fields, and can notify the right reviewers automatically.
The system changes what each person sees based on their job and access rights, so they only get the tools and information they need.
Instead of scrolling through every submittal, a user can narrow the list on an iPhone using filters like open/closed, current revision, responsible party, location, and specification section.
Once the utility network is built correctly, teams can ask the system to follow connections and show what equipment belongs to which part of the grid.
Use one network model to turn utility asset data into engineering designs, schematics, maps, and views that different teams can use without rebuilding the data each time.
A utility takes its old network data, matches each asset to the right standard bucket in Esri’s Utility Network Foundation, and loads it into ArcGIS in several passes so the new system works correctly.
This workflow connects AI tools with building information and live environmental data so designs can be tested and updated using more realistic climate inputs.
An AI assistant tests many early building design options and shows architects which ones best balance energy use and carbon impact before major decisions are locked in.
AI helps designers compare materials and design choices to pick options that are greener and better suited for future climate conditions.
The platform keeps work plans and material information updated so teams can stay aligned in near real time.
Workers on an Android device can drop a pin on a project drawing and connect it to an issue or observation so everyone can see exactly where the problem is.
Project teams can pull room or area locations from Revit into Procore and send grids over too, so everyone uses the same project map.
AI helps architects and builders test many building designs and construction plans quickly, then picks options that fit the site, budget, and environmental conditions better.
At the end of a project, it automatically gathers the paperwork history into an organized digital archive so teams can find what happened later.
An AI tool could help affordable housing teams compare projects, flag likely health/efficiency issues, and prioritize which designs are most likely to meet program goals.
Broccolini wants AI to turn all its project data into clearer answers for leaders, helping them see risks sooner and decide what to do without digging through scattered reports.
Teams attach site photos to the right spot on project drawings so anyone can quickly see what happened at a specific location.
It checks a building model and predicts how bright different rooms and surfaces will be before anything is built.
It watches for workflow status changes in Aconex and updates another project tool so everyone sees the latest progress.
Use AI to balance many sustainability goals at once—water, energy, certification, affordability, public benefits, and historic preservation—so the project team can choose the best overall design package.
AI can help organize project documents, workflows and updates so teams spend less time chasing information and more time building.
AI can understand a request like 'give me all approved drawing files for this project handover' and automatically find, bundle, and deliver the right files while respecting access rules.
Instead of carrying paper plans and calling the office about changes, teams use digital drawings and documents in the field so everyone works from the latest version.
Project teams can update photo details like album, location, trade, and descriptions directly while viewing a jobsite photo instead of opening extra screens.
Workers take photos of defects or cleanup problems, and the system automatically places them on the floor plan and alerts the right trade to fix them.
AI helps contractors choose billing schedules and payment terms that better match owner draw schedules and subcontractor payment obligations so cash does not get squeezed.
An AI planner could help teams draft a site-specific steel erection plan by asking the right questions and filling in required sections like crane placement, fall protection, material staging, and emergency response.
AI can turn all the status changes, linked records, messages, and proposal versions in a potential change order into a simple timeline and impact summary for project teams.
SEH planned drone flights in the cloud, sent the exact plan to other pilots, and repeated the same flight over time so teams could compare progress consistently.
When a project question (RFI) leads to extra work or cost, the system can turn that question into a draft potential change order so the team does not have to retype the same details.
It gives field teams a chat-style assistant trained on the company’s own rules and documents so they can quickly find the right procedure, safety guidance, or project information on site.
An AI assistant helps the new building owner receive the right logins, manuals, training, and system information so they can run the building from day one.
AI can compare owner requests against the original contract and closeout status to flag whether a request is a simple fix, a punch list item, or brand-new work that should be priced separately.
Helps design and construction teams work together on the same project information so they can spot issues earlier and keep the process visible.
The system keeps a detailed card for each warranted piece of equipment, including where it is, what it is, who covers it, and how to contact them.
It helps builders use one online system to ask contractors questions, collect documents, review answers, and decide who is safe and qualified to hire.