AI Platforms Gain Traction in Construction

- Agentic AI systems are designed to perform multi-step tasks with a degree of autonomy, breaking down goals into smaller steps and adjusting as conditions change. This differs from earlier AI that might optimize a single task, as agentic AI can balance competing objectives like cost, safety, and scheduling simultaneously. - While investor confidence in construction AI is growing, with 56% planning to increase funding, overall adoption remains low. A 2025 global survey found that 45% of construction firms report no AI use at all, and less than 1% have embedded it across multiple processes. - The primary barriers to AI adoption in construction include a lack of skilled personnel (46%), difficulties with integrating new and existing systems (37%), and issues with data quality and availability (30%). - O3 Solutions' "Otto" assistant is embedded directly into the company's project execution platform to provide insights from live project data. It is designed to help teams assess schedule risks, analyze Requests for Information (RFIs), and identify the root causes of project issues using natural language queries. - The Haseko and Tektome training program centers on Haseko's internal architectural database, MetiS, which organizes knowledge from hundreds of thousands of past condominium developments. The training enables architects to use natural language to query the database, automate drawing checks, and generate 3D models without needing to code. - Didero's AI platform for manufacturing is designed to automate procurement and supply chain management, aiming to eliminate 90% of manual tasks. The recent $30 million funding round included investment from Microsoft's venture fund, M12. - AI is being used to improve job site safety, a critical concern as construction had the most fatal injuries of any U.S. industry in 2023. AI systems can monitor sites for hazards, track worker locations, and ensure the use of proper safety equipment. - The use of AI in building design can help reduce waste and improve sustainability. AI tools can analyze building data to identify energy inefficiencies and model more sustainable design options, with the potential to cut building costs by up to 20%.