AI agents are software systems that plan and carry out multi-step tasks on their own, rather than only answering questions. India Mobile Congress (IMC) 2026 put them on the main stage, with next-generation AI networks as an anchor sector and an ITU Build-A-Thon dedicated to AI agents for 5G. For enterprise marketing, the shift means agents that research, execute and measure campaigns continuously, with humans setting goals and approving decisions.
Key facts: IMC 2026 ran October 7–10, 2026 in New Delhi under the theme "Scale Without Boundaries." Next-generation AI networks and enterprise transformation were two of its nine anchor sectors. Sessions included AI for Good, an AI safety panel with the UK and an ITU Build-A-Thon on AI agents. Agentic AI moves marketing work from dashboards that report to agents that act.
What are AI agents?
An AI assistant answers a question when you ask it. An AI agent takes a goal, breaks it into steps, uses tools and data to complete those steps, and reports back. It can keep working on its own, checking results and adjusting as it goes.
In marketing terms, the difference looks like this:
- AI assistant: "Write me five subject lines for this email."
- AI agent: "Find the segments where email engagement is dropping, draft and test new subject lines for each, and report which ones lifted open rates."
The first saves a few minutes. The second replaces a workflow.
What did IMC 2026 signal about AI agents?
IMC is India's biggest telecom event, so its agenda shows where the technology stack is heading. Three signals stood out in the official programme:
- AI is moving into the infrastructure. "Next-generation AI networks" was named one of nine anchor sectors, alongside 5G, 6G and semiconductors. When networks themselves run on AI, agents become a standard layer, not a novelty.
- Agents got their own competition. The ITU Build-A-Thon focused on AI agents for 5G networks, a sign that global standards bodies now treat agents as a core building block.
- Trust is part of the agenda. An AI for Good track and an AI safety panel with the UK show that governance is being discussed alongside capability, which matters for any enterprise putting agents near customers or budgets.
"Enterprise transformation" was also an anchor sector. The tools telecom operators are adopting to run networks are the same class of tools enterprises are adopting to run functions like marketing.
Why does marketing need AI agents now?
Marketing has more channels, more data and less time than ever. Three pressures make agents practical, not theoretical:
Too many channels for humans to watch
A typical enterprise brand now manages search, social, video, creators, marketplaces, email, retail media and, increasingly, AI assistants. Each has its own data and reporting. Agents can monitor all of them continuously and surface only what needs a decision.
Discovery is moving into AI answers
Buyers increasingly start research by asking ChatGPT, Gemini or Perplexity. That creates a new channel to measure and optimise. Tracking it manually across five platforms and hundreds of prompts is not realistic; agents can do it daily. Our coverage of Gemini 4 Argon and ChatGPT ads shows how quickly this channel is changing.
Reporting cycles are too slow
Monthly agency reports mean teams react to problems weeks late. Agents shorten the loop from "something changed" to "here is what to do" to hours.
What can AI agents do in marketing today?
The most useful jobs for marketing agents fall into four groups:
- Monitor: track brand mentions in AI answers, competitor launches, community conversations and campaign performance around the clock.
- Analyse: explain why a metric moved, such as which page, review or forum thread changed how AI models describe a brand.
- Create and check: draft content briefs, score creative before launch, and vet creator content for brand safety.
- Execute and optimise: shift budget between channels, publish and refresh content, and produce board-ready reports.
What are the risks of AI agents in marketing?
Agents are powerful, which is exactly why they need guardrails. The safety focus at IMC applies directly to marketing:
- Accuracy. Agents can be wrong. Google's guidance now calls manual fact-checking of AI-generated content critical before publishing, including titles, meta descriptions and alt text.
- Spend control. Any agent that can move budget needs caps, approval steps and an audit trail.
- Brand safety. Agents that publish or approve content must follow brand rules and escalate edge cases.
- Data governance. Prompts and outputs are records. Use platforms with clear access controls and data handling.
The rule of thumb: let agents do the watching and the legwork, and keep humans on decisions that are expensive or irreversible.
How should a CMO start with AI agents?
- Pick one painful workflow. Reporting, competitor monitoring or AI visibility tracking are good first candidates because they are repetitive and easy to measure.
- Define success upfront. Hours saved, faster decisions or a measurable lift such as share of AI answers.
- Keep a human in the loop. Require approval for spend changes and published content at first.
- Connect the data. Agents are only as good as the context they see. A shared data layer beats ten separate tools.
- Expand from proof. Add workflows once the first one shows results.
How does MarkGrid use AI agents?
MarkGrid was built around this model. Its platform runs 650+ autonomous agents across 15 modules, grouped into three jobs: See (where your brand shows up and why), Make (proof before spend) and Run (execution and budget). At IMC 2026, the team showcased this as an interactive grid; read what MarkGrid showed at IMC 2026.
For marketing leaders evaluating agentic platforms, our CMO solution page explains how the operating model works, and our GEO guide covers the AI-visibility side in depth.
FAQ
What is an AI agent in marketing?
An AI agent in marketing is software that takes a goal, such as improving AI search visibility or reallocating budget, and carries out the research, execution and reporting steps on its own, with humans approving key decisions.
How are AI agents different from AI assistants?
AI assistants respond to individual prompts. AI agents plan multi-step tasks, use tools and data, monitor results and keep working toward a goal without being prompted at each step.
What did India Mobile Congress 2026 say about AI agents?
IMC 2026 made next-generation AI networks an anchor sector and hosted an ITU Build-A-Thon on AI agents for 5G networks, alongside AI for Good and AI safety sessions.
Are AI agents safe to use in marketing?
They can be, with guardrails: human approval for spend and publishing, fact-checking of AI-generated content, brand-safety rules and clear data governance.
Which marketing tasks should AI agents handle first?
Start with repetitive, measurable work such as reporting, competitor monitoring and AI visibility tracking, then expand to creative checks and budget optimisation.
Last updated October 15, 2026.
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Kashish singh
Ai lead
Kashish Singh is AI Lead at MarkGrid, overseeing AI systems for marketing intelligence, automation, and brand visibility. Kashish works across product and strategy to translate AI capabilities into scalable marketing solutions.
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