One vendor promises to automate your follow-up. Another offers an AI assistant. A third says its AI agent can manage an entire workflow. The descriptions can sound similar, even when the tools do very different things.
For an independent agency, understanding those differences helps you decide where a tool fits, what your team needs to review and which questions to ask before putting it to work.
Traditional Automation
Traditional automation carries out steps based on rules you set. When someone submits a website form, for example, your system might send a confirmation, assign the inquiry to a producer and create a follow-up task. A renewal date could trigger a reminder.
These are useful functions, and they don’t necessarily involve AI. The system follows a predetermined path. Its effectiveness depends on whether you’ve established the right steps, timing and exceptions.
Generative AI and LLMs
Generative AI can draft, summarize or revise material. Large language models, often called LLMs, are a type of AI used for language tasks. An agency employee might use one to draft an email, summarize meeting notes or turn a rough outline into a first draft of a procedure.
The output needs review. A polished response can still contain incorrect information, miss an important detail or introduce something that wasn’t in the source material. Your team remains responsible for checking accuracy and deciding whether the result is appropriate to use.
AI Inside Your Existing Software
“Embedded AI” describes where the capability is available, rather than a separate kind of intelligence. Your agency management system or other software might include AI that summarizes an account’s activity, extracts information from a document or helps identify accounts needing attention.
That convenience can reduce the need to move between tools, but it doesn’t tell you everything about how the feature works. Ask what information it uses, how current that information is and whether you can check the records behind its output. An AI feature inside familiar software still needs evaluation.
AI Agents and Agentic AI
An AI agent may do more than generate a response. Depending on its design and permissions, it can select and carry out steps using connected tools. “Agentic AI” generally refers to AI systems that can work toward a goal through multiple steps. For example, an agent might review an inquiry for missing information, prepare a follow-up and create a task for the appropriate employee.
The distinction is how much discretion it has. Traditional automation follows a path you established; an AI agent may choose its next action based on what it finds. Some products combine both approaches, and vendors use the term “agent” differently.
That makes permissions especially important. Can the tool send a message, change an account record or act without approval? What happens when it encounters something it cannot resolve?
Questions to Ask Vendors
Ask a vendor to walk through a task your agency performs. What starts the process? What information does the tool use? Does it draft something for review or take action itself? Where does an employee step in, and can you see what the tool did?
Also establish how agency and client information will be handled and what access the tool requires. Start with a defined task, assign someone to oversee it and check the results before expanding its use.
The most useful technology is technology your team understands well enough to use confidently. Knowing what happens between the input and the outcome is a better starting point than the name on the sales presentation.