Jetbuilt’s founder and CEO, Paul Dexter, explains how automation, generative AI, and applied intelligence can enhance AV offerings.
Attribution: Paul Dexter, Founder and Chief Executive Officer for Jetbuilt
Artificial intelligence encompasses multiple technologies operating at different levels of capability. In the AV industry, these technologies are often grouped under a single label, which can confuse their distinct meanings. Automation, generative AI and applied intelligence are each separate tiers, and understanding these tiers can help integrators and manufacturers evaluate practical value.
Automation forms the foundation of most AI-driven workflows. It follows predefined rules to complete repetitive tasks such as routing approvals, updating pricing or issuing notifications. An automed system can increase speed and reduce manual effort. However, automation does not interpret context beyond its programmed conditions.
Generative AI is the second layer. It can produce new language or content based on learned data patterns. Within AV platforms, generative AI can draft scopes of work, summarize documentation or provide conversational interfaces. These tools enhance accessibility and reduce drafting time, yet they operate primarily on unstructured data rather than relational system architecture.
Applied intelligence functions very differently from automation and generative AI. It operates within structured project data and recognizes relationships among devices, documentation and lifecycle services. Rather than generating descriptive language, it produces outputs based on engineering logic. For example, when a platform can analyze a bill of materials and scope of work to produce a connected system schematic in seconds, it demonstrates awareness of signal paths and device roles.
This distinction becomes clearer in documentation workflows. For example, a generative tool can help write narrative text describing a room’s system, while applied intelligence can evaluate equipment relationships, confirm connection logic and produce structured documentation aligned with design intent.
We can use service operations to demonstrate the progression, too. Automation can route a support request to the appropriate team. Generative AI can suggest troubleshooting steps based on historical patterns. Applied intelligence can interpret installed equipment records, evaluate system context and determine when escalation to a technician is required, which represents structured system understanding rather than keyword matching.
For AV professionals, these different tiers of AI can influence daily operations. Simply put, automation streamlines administrative tasks, while generative AI improves interaction and communication. The real value lies in applied intelligence, which is designed to reduce engineering time, improve documentation accuracy and support informed decision-making across the project lifecycle.
As the AV industry continues exploring AI-driven tools, distinguishing among automation, generative AI and applied intelligence will help professionals evaluate solutions based on real capabilities. Technologies that understand structured project data and system relationships can support engineers, designers and service teams throughout the entire lifecycle of an AV system. To learn more about how applied intelligence is being implemented in practice, visit Jetbuilt.com and explore Jetbuilt’s Jetbot, designed to help AV professionals work more efficiently across design, documentation and service workflows.
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