Agentic AI in marketing

Agentic AI is an AI system that takes a goal, plans its own steps, uses tools and data to carry out several of them, and only stops to ask a human at checkpoints someone has set in advance. In marketing, that means agents that analyze campaigns, propose changes and apply those changes once they are approved.

What is agentic AI?

Generative AI writes a headline when you ask for one. Agentic AI takes a job like “lower the cost per lead on this campaign”, then looks at the numbers, finds the cause, proposes a fix and, if allowed, makes the fix itself.

Ads Advisor in Google Ads is a concrete example. Google describes a user asking how to optimize a Performance Max campaign for a seasonal moment; the agent suggests adding sitelinks and, once approved, applies the change to the account. Ads Advisor and Analytics Advisor rolled out to English-language accounts starting in December 2025 (Google, Ads Advisor and Analytics Advisor, November 2025).

Why is agentic AI everywhere in 2025 and 2026?

Gartner predicts that by 2028, 60% of brands will use agentic AI for one-to-one interactions with customers. These agents will run across marketing, sales and customer service instead of being split by channel (Gartner, January 2026).

Gartner also warns that more than 40% of agentic AI projects will be canceled by the end of 2027 because of rising costs, unclear business value or weak risk controls. Many vendors put the “agentic” label on chatbots or old automation tools, a practice Gartner calls “agent washing”. Out of thousands of vendors, Gartner estimates only about 130 are the real thing (Gartner, June 2025).

What can agentic AI do in marketing?

• Diagnose metrics: ask why users spiked or orders dropped, and the agent compares segments on its own and points to the main driver.
• Optimize campaigns: propose and apply changes to keywords, ad assets and budgets within set limits.
• Produce variations: write headlines, descriptions and scripts for each customer group.
• Handle customer care: answer questions, give advice and send repurchase reminders based on each person’s history.

Buyers are getting their own agents too, which search for products and place orders for them. That side is called agentic commerce.

An example from Vietnam (hypothetical)

A cosmetics brand runs ads on Meta, TikTok and Shopee, one of Vietnam’s largest e-commerce marketplaces. It gives an agent a morning routine: check spend and cost per order, flag any ad group whose cost is more than 30% above its 7-day average, and draft recommendations. The agent may pause disapproved ads on its own. Any budget change above VND 2 million per day needs a person to approve it.

Agentic AI vs automation and generative AI

Frequently asked questions

Can agentic AI replace marketers?

Not for now. Gartner’s view is that the models are not mature enough to reach complex business goals by themselves. Agents do well at repetitive work with clear numbers. Strategy and messaging are still a human job.

Where should a business start?

With one task that repeats, can be measured and carries little risk, such as a daily report. Spell out which thresholds the agent can act on alone and which need approval. Gartner also advises tightening data governance before plugging agents into the martech stack, and a Gartner survey of 335 US consumers found that 78% consider clearly labeling AI-generated content very important or the most important factor in keeping their trust.

If you are thinking about bringing AI agents into your advertising, SEO or measurement workflow and want to know where to start, the Adtek team can go through it with you on our contact page.