From Chatbots to AI Agents: What Does It Mean for Your Team?

Where once AI waited to be asked, increasingly it is now able to move forward with the task at hand without additional instructions.

A chatbot may be capable of answering a question, summarising information or providing options for an employee struggling to decide what their next action should be, but an AI agent can make decisions within defined parameters and take unilateral action across business systems.

For any business looking to add capacity, that dramatically expands their options around recruitment. The HR focus is no longer exclusively on who should fill the role, but how much of that role needs to be filled by a human.

Chatbots in Disguise?

With the rapid evolution of AI and the terminology surrounding it, it’s reasonable to question whether an AI agent is simply a chatbot masquerading as something more.

Salesforce’s Agentforce 360 provides a useful example of how far AI technology has moved beyond the chatbot model. It delivers the opportunity to design and deploy agents that can reason and act within business workflows, to embed granular controls over agent behaviour, and to ground agents in complex company data, all ensuring that conditions, transitions and actions can be defined using natural language instruction.

This isn’t a chatbot pretending to be something it isn’t. It’s a work colleague.

A Different Kind of Team

Now that AI can act, rather than simply assist, it is able to occupy a different place within businesses.

That doesn’t necessarily mean allocating an entire role to an agent. A workflow can move between agents and people according to what the work requires. An agent might gather information, update records and complete routine actions before escalating an unusual case to a human. In sales, an agent might research and qualify opportunities, while the salesperson concentrates on conversations, negotiation and closing the deal.

This isn’t a choice between a human and non-human workforce, but around the balance, and the value that both have. The potential for an integrated relationship changes the value calculation around agents. An agent doesn’t necessarily need to own an entire role to make a meaningful contribution. It can pick up work at one point in a workflow, carry it forward and hand it back when human involvement becomes useful or necessary. The opportunity lies as much in changing how work moves through a team as in deciding who — or what — does it.

Giving an Agent Work to Do

With greater autonomy comes the need for greater clarity around exactly what an agent is there to accomplish.

A useful agent role begins with a sharply-defined intention detailed in task-led instruction:  “handle order enquiries across our main channels, escalate those above £500.”

Authority should be equally deliberate. If an agent can take action within business systems, the business needs to determine which systems it can access, what changes it can make and those decisions for which it must always seek human authorisation. Those limits should be enforced through permissions and controls rather than relying solely on instructions.

Someone must also assume responsibility for its output. Performance needs to be reviewed, exceptions examined and permissions changed when necessary. Measures such as resolution rates, accuracy, escalation rates, cost per outcome and employee time released provide a much clearer picture than the number of tasks completed.

When the Normal Process Stops Being Normal

Agents are not suited for every workload. But, where work follows a recognisable pattern and unusual cases can be identified and escalated, an agent could prove transformative.

Some jobs are certainly not that. They involve incomplete information, difficult conversations, competing priorities and decisions that depend heavily on experience or organisational context. A senior account manager may spend relatively little time following a repeatable process because responding to what the customer does next is the role. Leadership or negotiation positions present similar challenges.

In those cases, the human isn’t there simply to handle the exceptions exactly because those exceptions are the basis of the role.

Choosing Where Agents Belong

The development of AI agents means that businesses now have more choice over how work is distributed across their teams. It also brings more nuance to the hiring process.

Some work will always require another employee. Some might be handled by an agent. Most could benefit from the combination; with agents completing mundane, repetitive tasks and people leading where experience and judgement matter.

The strongest teams won’t simply add agents to the workforce. They’ll redesign workflows around what people and agents can achieve together.

Satish Thiagarajan is the founder of Brysa, a Salesforce and data consultancy based in the UK. His company advises media, industrial, and services clients on using Data Cloud and Agentforce to turn signals into action. His work focuses on closing the loop between insight and execution in sales, marketing, and service.