Content
Agentic AI is often misunderstood, and many users get discouraged by their initial experiences due to unrealistic expectations. According to Morron, the common complaint that AI "doesn't work" typically stems not from the technology itself but from the approach taken. Many users provide minimal or overly simplistic prompts, expecting comprehensive results, and give up when the AI produces unsatisfactory or inaccurate outputs. Consumer-grade AI tools like ChatGPT are impressive general assistants but are not tailored to specific businesses or industries. To build truly effective AI agents, significant customization and training based on distinct use cases are necessary. This goes far beyond just crafting better prompts—it requires designing systems that understand and reflect the unique aspects of a business.
One of the major challenges with AI agent development is the problem of hallucinations, where AI generates plausible but false information. Morron acknowledges this as a genuine issue but insists the solution lies in proper design. He advocates for focusing on "utility agents," which have narrowly defined, specific tasks to minimize the risk of misinformation and increase reliability. This practical approach contrasts sharply with the overhyped vision of AI agents that autonomously achieve broad goals by accessing all relevant data and tools. Many Silicon Valley vendors promise such “thoroughbred” agents, but their actual performance often falls short, creating a gap between expectations and reality. Thus, implementing AI agents effectively requires concentrating on realistic, narrow applications rather than chasing sci-fi fantasies.
Morron founded HighlandTech to provide AI automation solutions tailored for small and medium-sized security businesses, which often lack the in-house development resources or large IT budgets needed for complex AI projects. With over a decade of experience in the security industry, he understands that many integrators are technicians turned entrepreneurs who run excellent operations but may not have evolved their business processes accordingly. HighlandTech helps these companies by codifying best practices into AI agents, enabling process improvements and automation simultaneously. Morron is particularly focused on removing repetitive, mundane tasks so human workers can emphasize relationship-building, empathy, and higher-level conversations.
Currently, HighlandTech is applying agentic AI in practical ways that transform security integration businesses. One example is automating service requests: the AI monitors email inboxes, creates service tickets in systems like SedonaOffice, acknowledges customers, and manages internal escalations. This automation ensures that customers receive immediate acknowledgment—often their primary concern—while the internal team benefits from organized tracking and timely reminders, preventing tasks from falling through the cracks. Importantly, the AI embodies the specific integrator’s unique approach to customer service, scaling what is often the key differentiator between similar companies.
Another application involves tier-one technical support. Here, AI agents interact with customers to troubleshoot basic problems through email or other channels. The agent can ask targeted questions, such as verifying whether firmware is updated or whether devices are properly connected. It can further triage issues by requesting details about product models or symptoms and then offering self-help guidance to resolve common problems without immediate human intervention. This setup addresses multiple goals: customers feel acknowledged and heard promptly, minor issues can be resolved quickly, and human technicians are freed to focus on more complex challenges. Such agentic AI deployments illustrate how narrow, well-designed systems can deliver tangible benefits in real-world business contexts.
