In recent years, artificial intelligence (AI) has dominated headlines and captured the attention of both industry insiders and the general public alike. This transformative technology has been a big deal in the media, with discussions focusing on its potential to revolutionize almost every aspect of our lives. From healthcare to finance, from retail to transportation, AI-powered technologies are reshaping the way businesses operate, optimizing operations, driving innovation, and unlocking new opportunities for efficiency.
The same is true for safety management in high-risk industries like construction, mining, oil and gas, and manufacturing. AI is a game-changer that promises to revolutionize safety practices by making engagement easier, streamlining processes, providing access to real-time safety data and analytics that improve decision making, and reducing overall incidents.
In this and several articles to follow, we’re going to delve into all things AI as they relate to safety management. We’ll examine the amazing potential of AI safety management tools and how they’ll dramatically change the way safety programs are run. We’ll also provide guidance on what AI-powered tools are available and how to start using them in your own safety program.
A word of warning: If you’re a big fan of time-consuming processes, stacks of paper forms, confusion across your organization, lack of critical data, and general inefficiency throughout your safety program, maybe it’s best to stop here. Because once you see what AI-driven safety systems can do to streamline processes, improve safety behaviors, and enhance data analysis capabilities, you’ll never go back to the old way of managing your safety program.
A Quick Overview of AI
Let’s start with the basics. What exactly is AI, and how does it work?
At its core, AI refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require a human brain, such as problem-solving, learning, creating, and decision-making. Think of AI as a virtual assistant who understands your behavior or needs and provides personalized recommendations or assistance. What’s more, this assistant learns from your interactions and gets better over time.
It’s also helpful to understand some of the other kinds of AI being used today. Machine learning (ML) is a subset of AI that enables computers to learn from data without explicit programming. Unlike traditional AI that imitates human intelligence relying on fixed rules, machine learning iteratively learns from data, identifying patterns and making predictions autonomously, enabling computers to adapt and improve performance over time without human intervention. In other words, with machine learning computers learn by being fed lots of examples.
Natural language processing (NLP) is a branch of artificial intelligence that focuses on enabling computers to understand, interpret, and generate human language in a way that is both meaningful and contextually relevant. The most recognizable examples of NLP are virtual assistants like Siri, Alexa, and Google Assistant which use NLP to understand and respond to spoken commands or queries, but NLP is also used for text summarization, sentiment analysis, machine translation of languages, and more.
Generative AI is a branch of artificial intelligence that creates, or “generates”, new data based on patterns and examples from existing data sets. A common type of generative AI uses what’s known as a large language model (LLM) to produce content. A LLM is an artificial intelligence system trained on vast amounts of text data to understand and generate human-like language, and it uses deep-learning techniques to analyze patterns in text and generate coherent and contextually relevant responses.
For example, OpenAI’s GPT (Generative Pre-trained Transformer) models are LLMs that can generate realistic text based on prompts provided by users, such as writing stories, answering questions, or composing poetry. As I write this article, I’m using Chat GPT to source information, check facts, and verify accuracy. Some generative AI systems can also create images and even video clips based on text inputs.
Each of these forms of AI is being used in virtually every industry today in transformative ways.
- In healthcare, AI analyzes medical images to assist doctors in detecting diseases earlier, and virtual health assistants provide personalized recommendations.
- In retail, AI recommendation engines analyze customer data to provide personalized product recommendations and optimize inventory management.
- In finance, AI algorithms analyze financial data to automate trading decisions and detect fraud.
- In manufacturing, AI-powered systems monitor equipment performance in real time and inspect products for defects during manufacturing.
- In transportation, AI optimizes route planning and scheduling for logistics companies and helps autonomous vehicles navigate roads safely.
These examples illustrate the diverse applications of AI across different industries, showcasing its potential to drive innovation, improve efficiency, and enhance experiences.
Now, unless you’ve been on a wilderness trek for the last few years, you’re well aware of the buzz around AI. Experts predict that it will change the global economy on a scale not seen since the transition from farming to manufacturing in the early 1900s. Already, hundreds of billions of dollars have been invested in AI-related technologies and research, including billions spent building the data centers needed to handle the massive computational power and storage that AI demands.
Just how AI will impact jobs, however, is still being studied. A report by McKinsey Global Institute estimated that AI and automation technologies could affect up to 800 million jobs worldwide by 2030 depending on industry, occupation, and geographic region. While AI is already automating certain tasks and roles, it’s also creating entirely new jobs such as prompt engineers, AI trainers and educators, AI data scientists, AI safety and security specialists, and more. In fact, a World Economic Forum study projects that AI will actually produce a net gain in jobs.
How AI Is Changing Safety Management
So where do things stand when it comes to AI being used in safety management? Already, the same kinds of far-reaching innovations that are changing other industries are now being applied to safety management in high-risk industries. Though we’re still in the early stages of adoption, solutions that use AI, ML, NLP, and generative AI are being used to significantly improve critical areas of safety.
Risk Prediction and Prevention
AI algorithms are now able to create predictive analytics for safety by analyzing diverse data sources, like historical incident reports and worker behavior, to predict and prevent accidents. By detecting patterns and trends, companies can implement preventive measures and mitigate risks.
Real-time Monitoring and Alerts
AI-powered sensors can continuously track environmental conditions and worker activities, issuing immediate alerts for swift intervention. This real-time monitoring enables proactive accident prevention on project sites.
Optimized Resource Allocation
AI can analyze project schedules and site conditions to optimize resource allocation, reducing congestion and hazards. By ensuring efficient resource deployment, AI enhances overall safety on work sites.
Enhanced Training and Education
AI-driven VR (virtual reality) and AR (augmented reality) simulations can offer immersive safety training experiences for frontline workers. These simulations, which can be performed virtually anywhere, can help reinforce safety awareness, improve decision-making, and minimize accident risks.
Data-driven Decision-making
Advanced, AI-powered safety analytics platforms can analyze safety data to identify trends and root causes, enabling informed decision-making. By providing actionable insights, AI can support continuous improvement in safety management practices.
Predictive Maintenance
AI is being used to analyze equipment sensor data to predict potential failures, enabling preventive maintenance scheduling. This proactive approach reduces the risk of accidents due to equipment malfunctions, ensuring worker safety and productivity.
We anticipate that as more safety leaders integrate AI technologies into their safety programs, outcomes in high-risk industries will significantly improve as companies experience greater engagement, reduced accidents, minimized injuries, and a safer work environment.
Taking Your First Steps Toward AI
Adopting new technologies, especially transformative ones like AI, can be somewhat daunting, and as we interact with our customers, we often hear the same basic questions: What is the best way to implement AI in our organization? Are there certain areas where it makes sense to start applying AI capabilities? How do we take that first AI step with confidence?
The answers depend on various factors, including the specific needs and circumstances of the organization, the complexity of existing systems, and the readiness of employees to adapt to new technologies. Many of our customers are testing the waters by applying AI in specific areas of their safety program, especially areas where immediate benefits can be achieved. Ultimately, the right adoption approach will depend on your unique circumstances and the priorities of your organization.
Based on the use cases and successes we are seeing, we think it makes sense for companies to begin their AI adoption in three specific areas that are central to every safety management program: form completion, real-time access to safety data, and on-demand access to safety documentation and requirements. Let’s take a look at how AI is changing existing processes in these areas.
AI-Assisted Form Completion: Conversational Forms
Whether paper or digital, safety programs run on forms. AI-powered conversational forms are poised to revolutionize how traditional forms are filled out by offering a more intuitive, efficient, and user-friendly experience. Here’s a quick rundown of how things are changing.
Natural language interaction
Unlike current forms that require manual input, AI-powered conversational forms use NLP to allow users to interact with the form by simply talking. Users can speak as if they were having a conversation with a virtual assistant, which makes the form-filling process more intuitive and accessible.
Enhanced accuracy and efficiency
AI algorithms behind conversational forms can interpret and process spoken responses with high accuracy. It’s not just talk-to-text, conversational AI can read between the lines to understand and extract relevant information from complex or ambiguous user inputs. This reduces the risk of errors and ensures and increases accuracy, while saving time and effort for both users and administrators.
Contextual assistance and guidance
Conversational forms can provide contextual assistance and guidance throughout the form-filling process. If a user provides incomplete or unclear information, the AI-powered system can prompt them for clarification or provide suggestions based on the context of the conversation or a company’s safety requirements. This proactive guidance helps users navigate the form more effectively and ensures that all necessary information is captured accurately.
Multilingual support
AI-powered conversational forms use machine translation to support multiple languages, allowing workers to interact with the form in their preferred language and engage more fully in safety management processes.
Adaptability to field conditions
In outdoor work environments typically seen in construction, mining, oil and gas, and manufacturing, traditional form-filling methods like pen and paper or digital keyboards can be cumbersome. AI-powered conversational forms offer a voice-activated alternative, allowing workers to fill out forms effortlessly without having to remove gloves or navigate through complex user interfaces.
Instant Access to Critical Data: Conversational Dashboards
AI-powered conversational dashboards are poised to revolutionize how real-time data is accessed for safety management by providing a more intuitive, accessible, and actionable experience. Here are some of the changes you can expect to see.
Natural language interaction
Unlike traditional dashboards that require users to navigate through complex menus and filters, conversational dashboards allow users to access data by making simple requests using spoken language. This natural language interaction makes it easier for anyone, no matter their level of technical proficiency, to access safety data that used to require specialized skills.
Instant access to relevant information
Conversational dashboards provide instant access to the specific real-time data needed to make informed decisions. Whether it’s historical incident reports, safety inspection findings, or compliance status updates, users can quickly retrieve relevant information by simply asking for specific data, eliminating the need to sift through multiple reports or dashboards and saving time and effort for safety leaders and company executives.
Personalized insights and recommendations
Conversational dashboards can provide personalized insights and recommendations based on user queries and historical data. By leveraging machine learning algorithms and data from safety software, these dashboards can analyze trends, patterns, and anomalies in the data to offer proactive suggestions and actionable recommendations. For example, if a user asks about recent safety incidents on a particular work site, the dashboard can provide insights into common root causes and suggest preventive measures to avoid future risks.
Bottom line, AI-powered conversational dashboards represent a significant advancement in how real-time data is accessed and utilized for safety management. By leveraging the power of AI and NLP, these dashboards empower leaders to make faster, more informed decisions, ultimately improving safety outcomes on work sites.
On-Demand Access to Safety Documentation: Conversational Search
AI-powered conversational tools now make it possible for safety professionals to access safety requirements in real time from various safety documents including safety manuals, standard operating procedures (SOPs), job hazard analyses (JHAs), and more. Here’s how these tools are transforming the process:
Natural language engagement
As with conversational forms and dashboards, AI-powered conversational tools allow safety professionals to access safety requirements using natural language queries. Instead of manually searching through lengthy documents or navigating complex file structures, users can simply ask questions or make requests in plain language, mimicking a conversation with a virtual assistant. For example, a safety professional could ask, “What are the tie-off requirements at South Weber site 4?”
Instant access to safety documents
AI-powered conversational tools can access and retrieve safety requirements and information from a wide range of safety documents, including manuals, SOPs, JHAs, OSHA documents, and more. Whether someone is looking for general safety procedures, specific hazards, or regulatory compliance requirements, the conversational tool can analyze the context of the user’s request and extract relevant content from the appropriate documents. It can also tell you exactly where it found the data, so that you know it can be trusted. This eliminates the need for manual searching and enables safety professionals, frontline workers, and subcontractors to access the information they need quickly and efficiently.
Multilingual support
Conversational tools can understand and process queries in multiple languages, catering to the diverse workforce in the high-risk industries and broadening engagement in safety behavior.
There’s no doubt that conversational search tools represent a significant improvement in how frontline workers access safety requirements from documents. Using the power of AI and NLP, these tools can help workers access the information they need quickly, accurately, and effortlessly, ultimately enhancing safety practices and compliance. It’s especially powerful in organizations where a large number of subcontractors need to be onboarded. Now the first stop for questions doesn’t need to be the nearest safety pro—it can be an app that’s accessible from anywhere.
The Two Goals of AI Solutions: Streamlining Processes and Improving Behavior
At the end of the day, AI-powered safety tools are designed to deliver on one overarching objective—that of building a strong culture of safety. To help companies early in AI adoption to move down that path, we encourage them to focus on two fundamental areas of safety management: streamlining processes and improving behavior.
Streamlining Processes
Research shows that safety professionals currently spend a significant portion of their time engaged in time-consuming manual processes. This is one area where AI should make a measurable difference in efficiency gains, enabling safety leaders to spend time on more productive activities.
Safety meetings, PTPs, JHAs, etc
AI-powered systems should automate the generation of safety meeting agendas, pre-task planning documents, and alert frontline leaders about high-risk permit work requests. This reduces the time spent on manual paperwork and ensures that documentation is accurate and consistent.
Observations and incident reports. NLP technologies should help streamline communication by converting spoken or written language into actionable data. This can facilitate data gathering, incident reporting, and compliance tracking through voice commands or text inputs. Just imagine how much critical data can be lost between the time an incident occurs and when the required forms are filled out. With conversational AI tools you can start capturing information almost immediately.
Notifications and alerts
AI sensors and monitoring systems should continuously track environmental conditions and worker activities, issuing real-time alerts for potential hazards or non-compliance with safety protocols.
Compliance
AI-enabled safety tools should automate compliance with safety regulations and company policies. This includes ensuring that workers have completed required training, that safety equipment is properly maintained, and that all necessary permits and documentation are up to date.
Improving Safety Behavior
Obviously, the safety behaviors of your frontline workers are essential for building a culture of safety that leads to a safer and more productive work environment. AI-powered tools should drive substantial improvement in safety behaviors across your organization, so as you implement AI, you’ll want to be sure you’re seeing measurable improvements in these areas.
Engagement
AI-powered platforms should engage frontline workers by making safety reporting and observation processes more intuitive and accessible. Mobile apps with AI-driven interfaces allow workers to easily report observations on hazards, unsafe acts, near-misses, and incidents using natural language or voice commands. This encourages active participation and promotes a culture of safety within the workforce.
Analytics
AI-driven analytics should do more than just display data in pretty charts and graphs. They should provide safety management professionals with actionable insights into safety performance and trends. These analytics can identify patterns in safety data, such as root causes of incidents, common hazards, or high-risk activities, enabling managers to prioritize resources and interventions effectively. Additionally, AI-powered incident prevention solutions can predict potential safety risks based on historical data, allowing proactive measures to be implemented to prevent incidents before they occur.
Personalized safety training
AI-based training solutions can personalize safety training programs to meet the individual needs and learning styles of employees. These solutions use adaptive learning algorithms to deliver targeted content and assessments that address specific safety knowledge gaps and reinforce good safety practices. By providing engaging and relevant training experiences, AI helps instill a culture of safety and compliance among employees.
In summary, focusing on these two foundational objectives of streamlining processes and improving behavior will help ensure that your AI initiative does what you want it to do—create a workplace culture where everyone is serious about safety
Embracing the Future of Safety Management
Embracing AI-powered tools will literally transform the way you manage safety. You’ll be able to streamline processes, spend less time on unproductive work and more time on actual safety improvements, enhance decision-making capabilities, improve safety behaviors, and ultimately create safer work environments for all.
In addition, making the transition to innovative safety technology with AI could be easier and quicker than you might think, largely because the new AI-enabled tools are incredibly easy to use and are no different than popular voice-activated AI tools like Amazon Alexa or Apple Siri.
The good news is that Mojo’s safety management platform offers AI safety solutions with groundbreaking features that are field-tested and ready to go right out of the box. In upcoming articles, we’ll take a closer look at Safety Mojo’s conversational forms, conversational dashboards, and conversational search capabilities, and explore how Mojo can help you start gaining the advantages and benefits of AI right now. If you’re interested in learning more right away, you can connect with one of our sales reps and schedule a demo.
