Chatbots, Copilots and Agentic AI: What Brands Need to Understand
From answering questions to getting things done
There is a significant increase in talk about agentic AI. Microsoft is introducing autonomous agents, start-ups are building new assistants, and computer-use tools are beginning to act through the interfaces we use ourselves.
For businesses, the opportunity is enormous. So is the confusion. We are moving from systems that respond to questions towards systems that can carry out work, but the terminology often hides the practical differences.
I find it useful to think about three overlapping capabilities: conversation, assistance and action.
Chatbots, copilots and agents
The traditional chatbots I used to build relied heavily on defined conversational flows. We created intents, sentence fragments and responses, then worked through the possible routes a conversation could take. Their strength was control; their weakness was the effort needed to anticipate what people might ask.
Generative copilots add another capability. They can draw on supplied information, summarise it and generate answers, helping a person explore a subject or complete a task. They work alongside the user rather than simply following a fixed script.
Agentic systems go further by using tools and taking actions towards a goal. An agent might investigate a service case, retrieve the relevant information and prepare the next step. The degree of autonomy depends on its design, permissions and approval requirements.
These categories overlap. A single product can contain scripted responses, generative assistance and task-specific agents. The useful question is what it can actually do, with which information and under whose authority.
Where avatars fit
An avatar is the interface through which someone experiences the system. It can give a conversational tool a face, a voice and a sense of character.
My digital.dudley experiments use my own material about the future of marketing to demonstrate this. The aim is to let people test the possibilities and limitations themselves, rather than rely on a polished sales presentation.
A human face and voice can help create a connection, but they do not guarantee accurate answers. The quality of the knowledge sources and the way the conversation is managed remain fundamental.
Why conversational design still matters
One of the strengths I see in Microsoft Copilot Studio is the ability to combine generative answers with more controlled dialogue. A brand can let a conversation develop naturally while defining how certain questions should be handled.
For example, a broad question about consumer research might deserve an informative explanation. A request for a product recommendation might require an approved description of the company's own research service. A definition with a particular strategic meaning may need to come from a designated document.
That takes work. You need to understand the subject, the user's intentions and the circumstances in which a particular response is appropriate. Connecting a website to a model is only the start.
My experience of building these demonstrations is that conversational orchestration remains a specialist skill. Tools make more possible, but they do not remove the need to decide what good behaviour looks like.
The agentic opportunity
Microsoft's October 2024 announcement points towards copilots working with specialised agents. A user could ask an assistant to delegate a defined job, rather than navigate every step themselves.
This matters for marketing, sales and operations as much as technology teams. The opportunity extends from finding information to coordinating useful work.
My advice is to start with the task. Decide whether you need a reliable answer, a useful conversation or an action completed. Then define the knowledge, controls and skills required. The next phase of human–machine interaction will reward businesses that understand all three.