The construction industry suffers high rates of injuries, fatalities, and close calls. In 2018 alone, a boom year for the U.S. construction industry, over 1,000 construction workers never made it home. Each statistic represents a life — someone’s family member, co-worker, or friend.

Safety compliance regulations and periodic training alone haven’t solved this crisis. Safety knowledge rarely makes it from corporate binders to the field, and when it does, it is usually sitting in a site office gathering dust. Workers tune out repetitive messaging. Supervisors struggle to improve safety while responding to project pressures. Managers juggle competing priorities while struggling to create engaging safety programs.

But artificial intelligence finally provides a path to weave collaborative, personalized, engaging user experiences into the fabric of safety management processes at scale. AI safety assistants are poised to transform the culture and experience of safety in construction and beyond.

The Limits of Analog Safety Practices

Traditional safety tactics rely on:

• Administrative compliance — documentation focused on liability rather than prevention.

• Infrequent training — periodic meetings and classes that fail to build lasting skills and awareness.

• Generic guidance — one-size-fits-all materials that overlook specialized contexts.

• Reactive response — investigating after incidents rather than avoiding them.

• Scarce data — limited human observations prone to oversight.

While essential, these analog safety processes have proven insufficient on their own.

Existing Solutions Are Not Fit For Purpose

Several SaaS solutions, aiming to address the safety challenges in the construction industry, such as Intelex, Safe Site, and Hammertech, have made commendable strides in digitizing safety management. However, their approach often mirrors traditional methods, merely transferring paper-based processes to digital formats. While this digitization offers some convenience, it doesn’t necessarily translate to enhanced safety or engagement on the ground.

Intelex, for instance, offers a comprehensive suite of tools, but its core functionality revolves around form-filling, preset data, and checklists. Similarly, Safe Site and Hammertech, while providing digital solutions, still operate on models that prioritize compliance over genuine engagement.

Dashboards are provided by all but focus on meeting reporting requirements, failing to leverage the opportunity for predictive and proactive analytics. These platforms, in essence, digitize the analog process without significantly innovating or adding transformative value. The result? A digital replication of the same old methods, where safety becomes a box-ticking exercise rather than a collaborative and engaging experience.

How AI Assistants Are Fundamentally Different

AI is reshaping user experiences across sectors, and relying solely on these dated models is a missed opportunity. Workers, supervisors, and managers need tools that don’t just replicate old methods but revolutionize them. They need solutions that shift the focus from mere compliance to active engagement and collaboration. The construction industry deserves a platform that harnesses the power of AI to create personalized, dynamic, and engaging safety experiences, ensuring that safety knowledge isn’t just stored but actively shared, accessed, and implemented throughout the construction safety management lifecycle. The time is ripe for a digital transformation.

AI safety assistants leverage capabilities like:

• Conversational interfaces — comprehending natural language queries and enabling intuitive knowledge exploration

• Computer vision — assessing imagery and video for risk and hazard identification, augmenting human observations in the field

• Predictive analytics — identifying hazardous scenarios before they unfold, gaps in compliance documentation, high-risk project areas

• Continuous data ingestion — monitoring thousands of environmental variables, documents, user observations, and incident reports

By absorbing safety knowledge and site data, assistants gain an intricate understanding of each project’s unique risks and requirements. Key sources analyzed include:

• Project plans and schedules, equipment logs, permits, safe operating procedures

• Company incident reports, safety guidelines, best practices, and historical data

• Real-time weather, traffic, and environmental alerts

• Geospatial risk models and industry safety benchmarks

Safety Applications Across the Project Lifecycle

Equipped with perception far beyond any individual or team, AI assistants enhance safety across multiple roles:

For Workers

• Answering on-demand safety questions via voice onsite

• Reviewing work permits and procedures against regulations

• Proactively sending personalized reminders and protocol prompts

• Rapidly assessing hazards reported via voice, text, or images

• Tracking worker safety training comprehension and participation

For Safety Managers

• Automating tedious reporting and inspection procedures

• Flagging hidden hazards in project plans and work packages

• Analyzing observations and incidents to reveal crisis indicators

• Maintaining dynamic regulatory compliance cheat sheets

• Delivering data-driven insights to target the highest-risk areas

For Leadership

• Monitoring macro risk metrics and safety trends by project type

• Quantifying ROI on safety investments with lead indicator analytics

• Demonstrating state-of-the-art safety programs to avoid liabilities

• Generating automated reports for stakeholders on recurring schedules

• Anticipating potential crises based on predictive risk models

Unlike periodic human interventions, AI enables continuous vigilance — perpetually connecting insights that might be missed in siloed efforts.

And the more data captured over time, the more attuned the systems become to each company’s unique risks, vocabulary, and pain points. They learn on the job.

Meet Oscar: Our AI Specialized For Workplace Safety

Oscar is our AI system, meticulously trained on safety knowledge from some of the world’s most reputable sources, including OSHA, HSE, and Safe Work Australia. This technology showcases the potential of domain-specialized AI, bringing unparalleled expertise to construction safety management.

Oscar’s capabilities are integrated into advanced systems to streamline safety operations and automate key tasks such as hazard classification, determining appropriate remedial actions, and assessing risk factors. This ensures that safety protocols are not only followed but enhanced with cutting-edge technology.

Two applications that leverage Oscar’s expertise are SWMS AI and Upsafe.

SWMS AI is a powerful tool designed to generate comprehensive safety risk assessments. Known in different regions as a Safe Work Method Statement (SWMS), Risk Assessment Method Statement (RAMS), Job Hazard Analysis (JHA), or Pre-task Plan, this tool takes a description of the work to be performed and produces an expert-level safety plan, tailored to the specific needs of the task at hand.

Upsafe is a safety observations management platform that maximizes safety reporting and harnesses AI-driven analytics to empower OHS teams with proactive, data-driven decision-making capabilities. Through Upsafe, Oscar serves as a conversational user interface, enabling users to report safety issues with ease. Whether through natural language, video, image, or recorded audio, Oscar processes unstructured reports and compiles detailed safety issue documents. It classifies hazards and behaviors, and automatically routes these issues to the appropriate team members based on their roles.

Beyond individual reports, Upsafe aggregates data across multiple projects and job sites, allowing companies to leverage AI to uncover insights, trends, and areas that require attention. This approach not only enhances safety compliance but also drives continuous improvement across operations.

Oscar represents the future of safety in the construction industry—turning complex safety management into a seamless, intelligent, and highly efficient process.