The state of agentic AI in marketing (2026)

Agentic AI in marketing workflows is the next major evolution of how marketing teams use AI. These systems don’t just generate content. They turn complex data into actionable insights in real time. 

Key takeaways

1. Agentic AI adoption will become the norm in 2026. Over half of senior execs say their companies are already using AI agents.

2. Data reporting and insights is a prime use case for marketers. Agentic AI is streamlining analytics, brand monitoring, insights, and reporting. 

3. Trust is critical. Marketers need clear citations and verified data sources to get onboard with agentic AI. 

What is agentic AI — and why it matters for marketing

Agentic AI refers to artificial intelligence systems that have the ability to:

• make decisions,

• use tools,

• and even complete tasks.

They have agency: The ability to do things on their own without constant direction from a human. 

Rather than commands, agentic AI relies on goals. You tell the system what you want to achieve, and it figures out how to get there.  Here’s how agentic AI compares to other forms of AI used in marketing

The rise of agentic AI: Adoption and growth stats

Is agentic AI really surging ahead as fast as it seems? Let’s look at the stats. 

Market adoption

AI agent adoption rates. Source: PwC AI Agent Survey

• 52% of senior executives say AI agents are broadly or fully adopted across their company. 27% said they have limited agentic AI adoption. And 15% have not yet started using agentic AI but are exploring the idea. Only 4% have no plans to start using agentic AI. 

• Globally, 28% of organizations are “very familiar” with agentic AI. More than half are “somewhat familiar.”

• In marketing and sales, only 7% of organizations are fully scaled or scaling agentic AI. 16% are either experimenting or piloting agentic AI. 5% plan to start using agentic AI within the year. 

• Among companies who already use agentic AI, sales and marketing is the second-most-common business function for AI agents (54%). Customer service and support is #1 at 57%.

• The industry most invested in agentic AI for marketing and sales is insurance (20%). It may be surprising to note that the technology industry comes in second (16%). Media and telecom is third (10%). 

Investment and innovation

• Global agentic AI startup funding hit $3.8 billion in 2024, up from just $24 million in 2020. There were 162 deals completed in 2024 compared to just 8 four years earlier. 

• In the second half of 2025, 51% of buyers of services were making conservative investments in agentic AI. 6% were making a high investment. 

• 71% of executives say their companies plan to increase their investment in AI by at least 10% over the next 12 months due to agentic AI. 8% plan that increase to be more than 50%.

Sentiment and conversation volume

Note: We’ve excluded crypto and bitcoin conversations in all our stats. They make up nearly half the online conversation volume, but focus on a very niche use of the technology. Including these conversations would not give an accurate picture of the overall trends in agentic AI.

Agentic AI mentions over time (excluding crypto), November 2023 to November 2025, 10% sample. Source: Talkwalker Social Listening

• There were 17 million mentions of agentic AI from November 2023 to November 2025. The conversation was almost nonexistent until several AI agents launched in early 2025.

• Net sentiment about AI agents is 91% (62.9%, 3% negative). Positive and neutral sentiment spiked around the time of the agent launches. They've seen a more consistent level since spring of 2025. 

AI Agent conversations sentiment over time (excluding crypto), November 2023 to November 2025, 10% sample. Source: Talkwalker Social Listening

Expected benefits

The top three expected benefits of agentic AI for market research and audience analysis are:

• faster time to insight (54%),

• productivity improvements (53%),

• and higher-quality work (52%).

The four top expected workflow changes when using agentic AI for these tasks are:

• working faster/more efficiently (49%),

• less time-consuming work on decks or reports (46%),

• applying insights to more use cases (46%),

• and better alignment/collaboration between teams (46%)

For companies already using agentic AI, the top benefits seen so far are:

• increased productivity (66%),

• cost savings (57%),

• and faster decision-making (55%).

How are marketers using agentic AI in 2026?

Marketers are using agentic AI – like Talkwalker’s Yeti Agent – to surface insights, protect brand reputation, and guide strategic decision making. 

Acceptable uses of agentic AI among marketing/advertising business professionals. Source: GWI Report

Insight discovery and analytics

Autonomous data collection and insights generation is an excellent use case for agentic AI for marketing. AI-driven agents comb through multiple data sources, recognize patterns, and generate contextual insights. 

GWI stats show how marketers are already using agentic AI:

• 72% of marketers are comfortable using agentic AI to summarize data

• 65% are comfortable having AI agents generate insights headlines

• 80% say they would use an AI agent for audience targeting or understanding an audience

• 80% also say they would use an AI agent for competitor or market analysis

Brand monitoring and risk management

AI agents constantly scan multiple channels for brand mentions (social media, news, blogs, forums, and so on). This gives them a full picture of the conversation about your brand right now, with no data lag. Seventy-nine percent of marketers say they are likely to use an AI agent for brand positioning. 

Agentic AI can take this a step further by recommending specific actions to manage risk. 

Decision support and reporting

Agentic AI makes reporting as easy as a conversation. Anyone on your team, from the intern to marketing leaders, can ask your marketing agents targeted questions. No data analysis expertise is required, as the AI agent takes care of all that on the back end. You ask a question and get a thoroughly researched answer with citations for backup. 

Here’s what marketers say about using agentic AI for this purpose:

• 66% of marketers are comfortable asking agentic AI to suggest a marketing strategy

• 65% are comfortable using AI agents to automate performance reporting

• 75% say they are likely to use an AI agent for internal reporting or stakeholder enablement                                                                                                 

What does public sentiment tell us about the future of agentic AI?

You saw above that the public conversation about agentic AI exploded in 2025, as new agents hit the market for the first time. What does the current conversation tell us to look for next?

Common themes in online discussion

AI Agent key themes segmented by sentiment (excluding crypto), English language, November 2023 to November 2025, 10% sample. Source: Talkwalker Social Listening

The most common themes in online discussion about agentic AI relate to efficiency, innovation, and trust. But the real insight here is how people feel about those topics. 

Talkwalker data shows that innovation is the most common theme in conversations with positive sentiment, but efficiency, trust, and speed are all catching up. 

On the negative side, trust is a growing concern – look at the spikes in pink in the chart below. Other negative themes include manipulation, misinformation/deepfakes, monopolization, and electricity demand. 

AI Agent key themes over time with negative sentiment (excluding crypto), English language, November 2023 to November 2025, 10% sample. Source: Talkwalker Social Listening

This indicates that agentic AI will need to lean into verified citations for user confidence.

Sentiment by audience type

We’ve seen that overall sentiment about AI agents is very positive. But is that universal, or does it vary based on how people plan to use the technology? Here we use Talkwalker data to look at the sentiment of two very different groups of agentic AI users:

• Marketers: Based on posts that include mentions of marketing, or created by someone who has marketing in their profile

• Technologists: Based on posts that include mentions of technology, or created by someone with technology or AI in their profile

Not surprisingly, technologists talk about AI more than marketers do – at least for now. They had 2.1 million conversations about agentic AI in the last two years, compared to 598,000 for marketers. 

Both groups have very high net sentiment. But marketers are slightly more positive at 91.64% compared to 89.86% for technologists. 

Overall, marketers and technologists are aligned in what they see as the most positive and negative aspects of agentic AI. But these two groups differ a little from everyone else. 

It’s important to note that innovation has both positive and negative sentiment for marketers and technologists. This indicates some mixed feelings about how innovation is going in this field. 

Trust has negative sentiment for all three groups. Interestingly, though, trust also is a topic of positive sentiment for the general public. 

Looking at audiences another way, we also broke down sentiment by media type. 

AI Agent mentions sentiment segmented by media type (excluding crypto), November 2023 to November 2025, 10% sample. Source: Talkwalker Social Listening

Media coverage is in general positive, as is the conversation on X. But on platforms with more nuanced conversations, like Reddit and Bluesky, the net sentiment is lower. 

Conversation hotspots

AI Agent conversations segmented by country (excluding crypto), November 2023 to November 2025, 10% sample. Source: Talkwalker Social Listening

Geographically, the United States is the hotpot of conversation. More than half (57.5%) of all conversations about agentic AI originate in the U.S. No other countries even come close. 

This makes sense, since Silicon Valley is an obvious place for the conversation about AI agents to take place. But it’s interesting how far behind other countries are in their share of the agentic AI conversation. Following the U.S., the next largest volumes of conversation on the topic come from:

• India (7.3%)

• Nigeria (4%)

• UK (3.3%)

• Canada (2.5%)

In terms of platforms, X is the dominant conversation hotspot, representing 89.6% of the conversation about AI agents. Online news (4.8%) and Reddit (1.7%) are the next-most common platforms for conversation about agentic AI. 

Challenges and trust barriers slowing adoption

You saw above that question of trust are a real issue in the adoption of agentic AI

Marketers are generally cautious about AI hallucinations and opaque decision-making. Transparent and cited sources were one of the most common trust requirements in GWI’s recent survey. And the IBM Institute for Business Value found that 45% of executives say a lack of visibility into agentic AI’s decision-making is a barrier to adoption.

In a PwC survey, the most common challenges cited for realizing value from agentic AI were: 

• cybersecurity concerns (18%), 

• cost of implementation (12%), 

• and lack of trust in AI agents (11%). 

To resolve these concerns, AI agents must be equipped to cite and source their data. Transparent decision-making is also critical in helping teams feel comfortable working with these new tools. Context-aware workflows and the use of custom-purpose tools, like Yeti Agent, can also reduce errors.

The road ahead: What’s next for agentic AI in marketing?

Agentic AI may still be new, but look for heavy adoption throughout marketing teams in 2026. Here are some of the developments that will facilitate a new era of AI use.

Integration across martech stacks

Marketers need AI agents to make their lives easier, not more complicated. That means these tools need to integrate into existing martech stacks and workflows. Look for integration with Slack, Microsoft Teams, Salesforce, CRMs, and other tools your team already uses. 

Agent-to-agent collaboration (LLM networks)

Through MCP integration, marketing AI agents will connect to other business LLMs, integrating multiple data sources. This will improve pattern recognition and trend identification. 

Teams will be able to create multiple agents, each with its own specific purpose and tasks. The agents can then communicate and collaborate to produce robust, verified insights. This orchestration exponentially increases the value of each AI agent.

Autonomous campaign optimization

The autonomous nature of agentic AI means that the tools will soon be able to optimize marketing campaigns and messaging without ongoing human intervention. 

For example, Meta aims to have agentic AI tools in place to create and optimize entire campaigns based on just a product description and a budget, by the end of 2026. 

FAQs about agentic AI in marketing

How is agentic AI different from regular AI tools?

Agentic AI doesn’t just assist humans with tasks or create content like Gen AI. It can actually take over those tasks for them. Agentic AI uses complex reasoning to complete tasks working towards a human-defined objective. 

How does agentic AI benefit marketing teams?

Agentic AI tools like Yeti Agent help marketing teams turn real-time datasets into speedy decisions. Marketers no longer need to manually set up, query or interpret metrics. The tools turn the data into actionable insights, delivered in real time.