Two years ago, artificial intelligence (AI) chatbots were at the cutting edge of customer service automation. Today, they’re the norm. For rural broadband service providers (BSPs) competing in an increasingly sophisticated marketplace, understanding the distinction between chatbots and agentic AI will help you keep pace with customer expectations.
Traditional chatbots excel at conversation, answering questions about your service plans, explaining billing charges, and directing customers to support resources. They’re essentially sophisticated FAQ systems.
But AI agents are built to do things. They can access multiple systems, make decisions, and execute multi-step processes that previously required human intervention. While a chatbot can tell a customer how to troubleshoot their connection, an AI agent can run diagnostics, identify the problem, reboot equipment when needed, and create a service ticket for escalation in a single interaction.
Agentic AI allows BSPs to create specialized expertise. Rather than a single, generalized chatbot, BSPs can deploy multiple AI agents trained for specific roles. For example:
- A prospective customer visiting your website might interact with an AI sales agent trained on your service areas, competitive advantages, and current promotions. This agent can help customers if service is available at their home, recommend the appropriate service based on the customer’s needs, and schedule an installation.
- A current customer might encounter an AI technical support agent that can check for outages, review account history, run remote diagnostics, and send the issue to human technicians as needed. This AI agent knows what it can fix and what requires a person.
- BSP employees might have access to internal AI agents with access to institutional knowledge, policies, customer data, and report generation.
Specialization matters because generic solutions rarely serve anyone well. A sales-focused agent needs persuasive capabilities and deep product knowledge. A technical agent needs diagnostic abilities and integration with network management systems. An internal agent needs access to operational data that should never be customer-facing.
The Importance of Training
AI agents are only as good as the training they receive and the accuracy of the information they’ve been trained on. AI agents must be highly customized with your company’s specific information, procedures, and policies.
This customization process requires an investment of time:
- Resource gathering: You’ll need to compile service documentation, policy manuals, troubleshooting guides, procedural workflows, and anything else you can think of that might be relevant.
- Testing: You’ll need to test extensively, feeding the agent variations of the same question to ensure it understands how different customers phrase their needs.
- Setting limits: You’ll need to establish guardrails, so agents know when to escalate to humans rather than attempting to resolve issues they can’t or shouldn’t.
Implementing agentic AI is akin to hiring and training a new employee. You’re creating a digital team member who needs onboarding, ongoing supervision, and periodic retraining.
CDG launched our customizable AI agent platform early this year, designed specifically for the broadband industry’s unique requirements. If you are interested in learning more about how agentic AI can help transform your customer experience and internal processes, please don’t hesitate to reach out.
Tony Stout, CTO
CDG
Tony Stout joined PRTC in 2010 and serves as the company’s Chief Technology Officer. In his role as CTO, Tony is responsible for overseeing strategic direction for building and expanding PRTC’s next generation network infrastructure. In 2020, PRTC acquired CDG, a telecom OSS/BSS solutions provider. Tony was appointed CTO for CDG and oversees the company’s technology, software engineering, IT and technical support teams. Tony has more than 28 years of technology, business and management experience in various Telecom and Information Technology roles.
