What Are AI Agents and How Are They Starting to Help Marketing Professionals

By Aby Varma, Spark Novus

Sam Altman describes AI agents as assistants that can take actions on a user’s behalf, complete multi-step tasks, and operate within defined boundaries while still requiring human oversight. This reflects how early marketing agents are beginning to assist with structured work today. AI agents are not fully autonomous, but they are showing early signs of being able to manage parts of workflows that once depended entirely on manual effort.

What an AI agent is in practical marketing terms

An AI agent is a software system that can perform a sequence of actions toward a defined goal. In marketing, this usually means:

• Receiving an instruction

• Gathering or interpreting information

• Completing a task within clear boundaries

• Handing the result back to a human or another system

This is different from a chatbot or a prompt based tool. Agents operate inside workflows and follow logic that moves work forward rather than producing one off responses.

Where AI agents are beginning to show value in marketing

AI agents are starting to help in areas where the rules are known, the structure is predictable, and the outcomes can be checked quickly. Early use cases include the following.

Drafting campaign briefs

AI agents can turn defined goals, basic context, and audience inputs into draft campaign outlines that marketers can refine. E.g., Salesforce Agentforce can generate an initial campaign brief by interpreting a stated objective, a target audience, and a content theme before handing it back for human review[1].

Building early audience segments

Agents can scan contact databases and highlight simple audience groupings based on shared characteristics or recent activity. E.g., HubSpot Breeze agents can recommend new segments by analyzing CRM fields, web behavior, and recent engagement to surface audiences that warrant attention[2].

Suggesting workflows

Agents can propose step by step sequences for journeys that follow known patterns such as welcome series, onboarding flows, or re engagement paths. E.g., Adobe Experience Platform Agent Orchestrator can outline a rough sequence for a basic nurture workflow when provided with a goal and the assets available in the system[3].

Automating repetitive tasks

Agents can take on routine operational tasks that follow rules, saving teams from manual updates and quality checks. E.g., Conversica agents can manage structured outreach and escalate conversations needing attention, while Demandbase Agentbase can recommend next steps and automate parts of B2B workflows driven by intent signals[4][5].

Martech vendors offering early AI agent capabilities

These martech platforms represent select examples of vendors with publicly documented early AI agent capabilities, not an exhaustive list.

• Salesforce Agentforce: Enables teams to create agents that help draft campaign elements, update CRM records, and perform structured tasks inside workflows.

• HubSpot Breeze: AI Agents Supports task based actions such as generating content, routing inquiries, and updating contacts within marketing and sales processes.

• Adobe Experience Platform Agent Orchestrator: Coordinates actions across Adobe applications including pulling data, preparing drafts, tagging assets, and assisting with multistep workflows.

• Conversica: Provides digital assistants that conduct structured outreach, qualify leads, and escalate conversations requiring a human.

• Demandbase Agentbase: Helps teams prioritize accounts, recommend next steps, and automate parts of B2B workflows based on intent signals.

• Albert AI: Optimizes paid media by adjusting budgets, rotating creatives, and tuning performance within preset guardrails.

What AI agents cannot do in marketing yet

It is important to stay clear about current limits. As of now, agents are not ready for:

• Planning multi channel campaigns

• Judging creative quality

• Deciding strategy

• Interpreting nuance in customer behavior

• Autonomously optimizing outcomes

• Running initiatives end-to-end

They support work. They do not direct it.

Why this matters for marketing professionals

AI agents signal a shift toward more intelligent workflows. Even in early form, they reduce operational drag by handling tasks that rely on structure and consistency. Teams that explore agents now will:

• Understand where automation is realistic

• Identify workflows that benefit from structured assistance

• Build internal guidelines for responsible use

• Prepare for more advanced capabilities as they emerge

Early familiarity becomes a strategic advantage as the technology matures.

What marketing teams can do next

A simple starting point for evaluating agent use is:

• Identify repetitive tasks that follow clear rules

• Test agent features already available in existing platforms

• Document what agents do well and where oversight is required

• Create lightweight evaluation criteria for accuracy

• Keep humans in the loop for judgment and signoff

• This keeps experimentation grounded and safe while building future capability.

Conclusion

AI agents are in the early stages of supporting marketing work. They are already helping with structured tasks that benefit from consistency and speed, and they require continuous oversight to stay reliable. They are not ready to make independent decisions, but their progress points toward more intelligent and assisted workflows. The goal now is exploration and understanding. Teams that build this familiarity will be better positioned as agent capabilities expand in the coming years.

Frequently asked questions

• Are AI agents replacing marketers?

  No. Agents handle structured tasks. Marketers provide strategy, context, and narrative direction.

• Do agents require coding?

  Most marketing related agents today are no code or low code. They rely on configuration and clear instructions.

• Will agents eventually run campaigns on their own?

  Possibly in the long term, but current capabilities remain early. Directionally the field is progressing, not arriving at full autonomy.

• Should marketing teams begin experimenting

  Yes. Teams often see value sooner because agents remove repetitive work that consumes limited resources.

Footnotes

[1] Salesforce documentation: “Create a campaign from a brief to quickly generate campaign elements such as a subject line, preheader, and body copy.”

[2] HubSpot documentation: “Our AI powered segmentation agent constantly provides recommendations for new segments to target based on your goals and helps you build precise segments by analyzing your CRM, web visitor, and external data.”

[3] Adobe documentation: “Agent Orchestrator can complete complex end to end workflows through an intuitive conversational interface and can build on previous questions without repeating context.”

[4] Conversica documentation: “Conversica AI Assistants can engage leads, qualify interest, and route conversations to humans when needed.”

[5] Demandbase documentation: “Agentbase provides AI agents that recommend next best actions, prioritize accounts, and automate parts of B2B workflows based on intent data.”