“Okay, AI, explain OT Asset Management to me.”
Already a hot technology topic, artificial intelligence captured a lot of general media attention recently in coverage about ChatGPT. We decided to check its responses to a subject we know well: operational technology (OT) for networked production environments.
- AI-based chatbots now provide conversational replies of generally impressive quality on a huge range of topics, including highly specialized fields like operational technology (OT).
- ChatGPT correctly identified the central aspects of OT asset management: creating and continuously updating inventories of all production systems and machines and securing them in accordance with compliance and security requirements.
- It’s important to note that while IT and OT administration are often similar, OT asset management must be conducted without disturbing production or device uptime.
The exciting thing about ChatGPT and other AI-based chatbots – and what distinguishes them from classic search engines – is that they generate detailed, conversational, natural language responses to highly specific queries. We decided to see how ChatGPT would explain a subject that we know in depth: Asset Management in Operational Technology (OT). So we asked it, “Please write me a blog article about OT Asset Management.”
ChatGPT says: “OT (Operational Technology) Asset Management is an important part of enterprise IT security. It involves monitoring and managing the IT systems and devices that
are responsible for the operation of plant and machinery. These include, for example, industrial control systems, SCADA systems (Supervisory Control and Data Acquisition) and process
An important aspect of OT asset management is the identification and monitoring of assets. This includes capturing information such as manufacturer, model, serial number, location and operational status. This information is important to ensure that IT systems and equipment are functioning properly and to respond quickly to problems.”
We agree. The challenge lies primarily in the diversity of asset types and vendors that range from ABB to Siemens to Zebra. If all devices are not fully inventoried there is no basis for assessing security gaps. You can only protect what you can see.
Next, ChatGPT says: “Another important element of OT asset management is monitoring the security of these systems and devices. This includes monitoring security vulnerabilities
and performing security updates. It’s also important for organizations to regularly review their IT systems and devices for compliance requirements to ensure they meet applicable laws and
Again, ChatGPT described many aspects correctly. Compliance and security requirements take up a lot of space in the day-to-day operations and pose significant management challenges. ChatGPT correctly points out that IT and OT admins already do – or should – collaborate in this area.
However, it’s important to note that the implementation of security updates in OT can be much more difficult than in IT. Not every update for OT assets can be applied quickly or with flexible timing. Disruptions to production processes during or after update deployments can lead to costly downtime, increased safety risks and other negative outcomes.
ChatGPT sums up: “In conclusion, it is important to emphasize that OT Asset Management is a continuous process that needs to be monitored and updated regularly to ensure that IT
systems and devices are functioning properly, and security is maintained.”
ChatGPT’s bottom line is worth noting: one-time or occasional inventory snapshots only help for short periods of time. Continuous updating, maintenance and storage of asset data for historical analysis are enormously important to be able to detect changes. That’s one reason why the baramundi Management Suite supports such data collection and historization in the Argus Cockpit module.
The chatbot-generated article is pretty good overall. It accurately summarizes how asset management is the basis for all OT security measures. AI can explain it credibly enough using industry knowledge published by manufacturers, analysts, and trade journals.