AI Trends, Insights, and the Future of Operational Safety – A Conversation with Comply365’s General Manager of AI, Alan Sternberg
As the aviation industry and other highly regulated sectors face increasing operational complexity, AI is rapidly becoming the force multiplier that connects data, workflows, and decision-making. At Comply365, we are building AI that does not just automate tasks – it is transforming how organizations understand safety events, link insights across training and documentation, and make informed decisions faster.
To explore where AI is heading and how Comply365 is helping our customers to unlock its value, we sat down with Alan Sternberg, Comply365’s General Manager of AI to discuss the evolution of AI within Comply365’s unified platform, the shift from reactive to predictive safety with the Comply365 CoAnalyst in SafetyManager365, trends for AI in 2026 and the responsible use of AI in high-stakes environments.
AI Evolution in Comply365
Q: How has AI evolved within Comply365?
Alan: We have seen tremendous evolution. AI is now transforming how organizations analyze data, connect siloed workflows, and generate insights across safety, training, and documentation. Within Comply365 and our next generation solutions including SafetyManager365, AI is doing far more than accelerating tasks – it’s enabling deep understanding of events, identifying patterns in seconds, connecting and automating workflows and offering recommendations that were previously impossible without extensive manual effort.
“The aviation industry sits on decades of siloed data. AI’s job is to finally make sense of it – AI is the glue that finally connects training, safety, and documentation into one intelligent ecosystem.”
– Alan Sternberg
Industry Data Challenges
Q: What challenges do aviation and other regulated industries face when it comes to data?
Alan: These industries sit on enormous amounts of siloed and historical data – training records, safety reports, operational documents. Making sense of all that information used to take analysts days or weeks. AI changes that. Its role is to help organizations actually use their data: improving accuracy, simplifying analysis, and revealing trends that were previously buried.
Q: Can you give an example of how AI improves data analysis?
Alan: Absolutely. Take safety reports: AI can automatically categorize, classify, and process them with high accuracy. It can compare new events to historical data in milliseconds, providing context instantly. The result is both increased efficiency and higher-quality insights for analysts.
Q: How does AI connect workflows that were previously separate?
Alan: This is one of the most transformative shifts. We can now link root cause analysis in a safety event directly to training recommendations or documentation updates. So instead of processes happening in isolation, our vision is that AI will enable a unified, intelligent workflow across the entire Comply365 platform. AI helps organisations get so much more value from their data. Instead of checking boxes, they can now identify risks earlier, understand contributing factors, and proactively drive operational improvement. AI turns compliance data into actionable insight.
Q: How does the unified Comply365 platform support this interconnected approach?
Alan: The Comply365 platform is designed to bring training, safety, and documentation together. AI is the engine powering those connections. It can automate recommendations- such as suggesting updates to manuals or training content – and guide organizations toward smarter, faster decisions across all operational areas.For example, every safety event has implications for training and documentation. Every training gap has potential safety impact. AI is the tool that finally empowers organizations to treat these areas as parts of a unified ecosystem rather than separate departments. That’s the core value of the Comply365 platform.
Q: How do automated recommendations work in practice?
Alan: If a safety report identifies a root cause related to for example existing procedures, AI can immediately propose a documentation change. If training gaps surface, AI can recommend curriculum updates. This reduces manual effort and gives organisations immediate, actionable value.
SafetyManager365 & the CoAnalyst: Transforming Safety
Q: Specifically in Safety Management where you focused your AI innovation before joining Comply365, what challenges in the aviation safety sector did you identify that led to the development of the CoAnalyst?
Alan: Aviation safety teams struggle with fragmented, inconsistent data, making it hard to analyze events, spot patterns, and shift from reactive to proactive risk management. Current tools often miss cross-system hazards, leaving teams focused on individual issues instead of prevention. We’ve developed effective AI solutions to address these challenges.
Q: Can you explain how the CoAnalyst works to enhance safety management for aviation companies?
Alan: SafetyManager365 integrates AI to give safety teams instant access to advanced analytics for reports. CoAnalyst automates event classification, hazard detection, and report triage, while custom dashboards and AI-driven root cause analysis help teams quickly uncover trends and insights. This streamlines workflows, improves data quality, and enables a shift from reactive to proactive safety management.
Q: What makes your approach to safety analytics different from traditional methods used in the industry?
Alan: The CoAnalyst leverages state of the art advanced technologies for machine learning and large language models, moving far beyond traditional industry methods where humans would manually process safety data. We have invested millions of dollars in research and development to ensure our AI capabilties provide real value in aviation safety. There is no “out-of-the-box” in safety AI! The big advantage with the CoAnalyst is that we have trained AI models with millions of safety data to compensate the lack of data to achieve accuracy. Also our AI is self-learning, which continuously improves over time and leverages historical data across divisions to deliver high quality AI-driven insights. Replicating this in-house would require a massive and ongoing investment from IT teams.
Q: What makes SafetyManager365 and the Co Analyst so powerful?
Alan: SafetyManager365 brings real-time, AI-powered insights to safety teams. CoAnalyst takes it further – leadership can run their own analyses, ask questions, and get reliable answers without waiting for reports. Leaders can now explore safety data independently with trustworthy, structured results. They no longer have to wait days for a report – they can get insights instantly, allowing faster and better-informed decisions.
AI Trends, Custom Models & Customer Priorities for 2026
Q: What major AI trends and customer priorities do you expect for 2026?
Alan: There’s a clear move toward custom AI models tailored to an organization’s own data. Customers want automation of manual workflows, domain-specific AI capabilities, and AI infrastructure built for accuracy and reliability – not generic tools. Investments in specialised AI are becoming a top priority
Q: Why are custom AI models and specialised providers becoming so important?
Alan: Because accuracy matters. When you’re analysing safety data, you need models built specifically for your domain and your data. That’s why Comply365 invests heavily in custom AI infrastructure. Organisations will still use general AI internally, but for safety, training, and documentation, they’ll rely on specialised providers who can ensure trustworthy results for accuracy and oversight. Using the wrong tool for the job can create significant risks.
Q: How does the CoAnalyst ensure that safety analysts can effectively use and trust the AI-driven insights?
Alan: We ensure transparency by showing AI-suggested classifications only when they meet strict accuracy standards, and users must actively accept, reject, or correct results. This keeps experts in control and enables ongoing improvement of our AI models through real-world feedback.
Q: What are the risks of relying on generic AI models for safety data?
Alan: The biggest risk is untransparent and unvalidated AI output from one of the big models and AI companies. If the AI generated data gets copied back into your systems or reports and data pipelines, it undermines data quality and trust. Safety decisions depend on accuracy, so organizations must be very careful with the tools they use.
Q: What advice would you give safety leaders preparing for the future of AI?
Alan: Invest in the right AI infrastructure and partnerships now. The organizations that fail to do this risk what I call “data chaos” – a situation where low-quality or inconsistent AI outputs erode trust in the entire data ecosystem. Responsible, specialised, trustworthy AI is the foundation of the future.
AI is evolving rapidly, but its true value lies in how it elevates human decision-making. At Comply365, we are committed to delivering AI that strengthens safety cultures, connects operational ecosystems, and empowers organizations to move from reactive management to proactive excellence. As we look toward 2026 and beyond, one thing is clear: the future belongs to organizations that invest in responsible, specialized, trustworthy AI.
