This is a complete guide to the AI agents every marketing team needs in 2026. Not content generators or copywriting hacks, but real, operational agents that run campaigns, route and enrich leads, clean data, QA pages, surface insights, and handle the glue work that actually consumes marketers’ time. While most AI marketing conversations stop at “write faster,” this guide goes deeper into the agent layer that connects tools, makes decisions, and carries work from trigger to outcome so teams can move from manual execution to strategic control.

Top 15 Marketing Agents at a Glance

1. Campaign Orchestrator: Converts a single brief into channel-ready assets, UTMs, and tasks.
2. Campaign Intelligence Agent: Auto-pulls metrics from GA4/CRM to write weekly "what changed and why" narratives.
3. Intent Intelligence Agent: Analyzes why someone engaged to recommend the right next action.
4. Routing Orchestration Agent: Enriches, dedupes, and routes leads based on intent signals.
5. Conversation Intelligence Agent: Transforms sales call data into actionable marketing signals.
6. SEO Content Brief Agent: Generates comprehensive briefs with internal linking targets and pre-publish checks.
7. Ad Creative Variant Generator: Produces structured ad variations (hooks, claims, CTAs) aligned to brand guidelines.
8. Lead Enrichment & Cleanup Agent: Standardizes messy lead data and fills in missing details before sales sees them.
9. Lifecycle Nurture Agent: Continuously tests subject lines and refreshes nurture sequences based on engagement.
10. Landing Page QA Agent: Automates QA, checking for broken links, slow load times, and UTM errors.
11. Webinar Ops Assistant: Handles promotion, reminders, scripts, and post-event follow-up.
12. Social Listening & Response Agent: Monitors brand mentions to draft responses and extract insights.
13. Personalized Email Engager: Classifies intent of users dropping off from app/website and sends personalized email to re-engage them
14. Content Repurposing Agent: Atomizes high-performing content into social posts, newsletters, and decks.
15. Competitor Monitor: Tracks competitor website changes, pricing updates, and new ad launches.

Every marketer knows that AI will help them with all the work their doing, but the path to building a system of marketing agents embedded in all your marketing operations is still very challenging.

The reality is that most marketing teams are stuck. They're using AI to write mediocre blog posts or generic emails, but they're still drowning in the manual operations and data work that actually eats up their week.

I wanted to find out what's actually working by talking to marketing ops leaders and demand gen experts who are in the trenches working with larger marketing systems.

My conversation with Devreet Dulay from the founding team at Respell really stuck out to me. She said:

The agents I find most valuable are ones that connect existing marketing ops tools and surface insights, not just create content. Think agents that summarize performance, clean up messy data, and help teams understand what's actually happening across campaigns and funnels.

That clicked for me. We don't need more content generators. We need intelligent and context enabled agents that help with making sense of the mess, so us marketers can make better decisions that move the needle.

Digging deeper, I spoke with a Marketing and Revenue Ops Leader at Regal AI who expressed frustration between marketing and sales, specifically the "black box" of lead routing. They told me:

The agents I wish I had today are less about doing tasks and more about handling the messy glue work between systems. An inbound intent agent that actually understands why someone engaged... and recommends or triggers the right next action instead of treating everything like the same MQL.

Sales conversations are a goldmine of marketing intelligence that rarely makes it back to marketing teams. Imagine an Intent Intelligence Agent that doesn't just see a form fill, but has all the tools and data connectivity to analyze why the person filled it out and routes it accordingly.

These kinds of agents reduce all the manual work of actually close the feedback loop.

I wrote this guide to actual help those critical to running marketing operations have access to learning and using AI marketing agents that actually increase efficiency of go to market for Vellum and other businesses’ marketing teams. All 15 agents are ones that experts are asking for, building, and/or using right now.

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What Are AI Agents?

AI agents are AI automations that can carry out work on your behalf, end to end. They have the ability to decide what steps to take, use your existing tools, and follow through until a task is finished. An agent might pull data, evaluate it against rules or goals, and then take action in tools like Slack, Salesforce, or Google Ads, without needing constant human input.

Why Marketing Teams Need AI Agents

Marketing teams in 2026 aren't suffering from a lack of ideas; they are suffering from operational drag. Here is why you need agents now:

• Expedite reporting functions: Eliminate the hours spent manually stitching data from GA4, ad platforms, and spreadsheets just to prove ROI.
• End cross-channel inconsistency: Prevent messaging drift where your ads say one thing and your landing page says another.
• Fix lead routing friction: Stop the fighting between ops and sales over "bad leads" by ensuring data is enriched and validated before it ever hits a rep's queue.
• Scale content without chaos: Move beyond "more content" to "better operations," handling briefs, SEO checks, and distribution automatically.
• Reduce campaign overhead: Automate the dozens of repetitive steps (UTMs, tracking, naming conventions) that slow down every go-to-market effort.
• Capture lost signals: Actually use the data from social listening and sales calls to inform strategy.
• Enforce brand governance: Catch compliance issues and off-brand claims before legal has to get involved.
• Personalize at scale: Move from generic "blast" emails to dynamic nurture streams that adapt to user behavior in real-time.

Common Tasks AI Agents Easily Automate

• Converting campaign briefs into assets: Taking a single strategy doc and auto-generating the ad copy, emails, and social posts to match.
• Normalizing performance data: Pulling messy CSVs from different ad networks and formatting them into a single, clean source of truth.
• Enriching and routing leads: Checking a lead against Clearbit/ZoomInfo, verifying intent, and assigning it to the right territory owner.
• QA-ing landing pages: Automatically checking every link, form, and UTM parameter on a page before it goes live.
• Summarizing weekly performance: Reading analytics data and writing a plain-English summary of what went up, what went down, and why.
• Monitoring brand mentions: Scanning social media for sentiment and drafting on-brand responses for community managers to approve.

What Makes a Great AI Marketing Agent

• Autonomy: It doesn't just wait for you to click a button; it triggers based on events (like a new lead or a completed week).
• Connectivity: It integrates deeply with your current stack (HubSpot, Slack, Google Ads), acting as the glue between them.
• Observability: It leaves a clear audit trail. You can always see why the agent made a specific decision or recommendation.
• Guardrails: It has strict rules about what it cannot do (e.g., "never promise a specific ROI figure" or "never email a prospect twice in 24 hours").
• Action-Oriented: It produces a tangible output, meaning a routed lead, a built campaign, a fixed report not just text.

The 15 Best AI Agents for Marketing Teams

Marketing teams in 2026 aren't replaced by AI, they are orchestrated by it. The agents listed below handle practical, operational out of the box you can build in Vellum today to reclaim hours for strategy and creative work.

1. Campaign Orchestrator Agent

What it does: Converts a single campaign brief into channel-ready assets, tasks, and tracking codes.

The problem it solves: Launching a campaign requires translating one strategy into dozens of formats (ads, emails, landing pages). Marketers spend 6–12 hours/week manually copy-pasting context and reformatting text for different channels, often leading to version control errors.

How it works:

1. Trigger: New "Campaign Brief" document added to Google Drive or Notion.
2. Process: Analyzes the brief for core messaging and offer; generates specific copy for email, social, and ads; creates UTM links based on taxonomy; drafts tasks in project management tools.
3. Output: A folder containing all draft assets and a populated project board.

Tools it connects: Google Docs → OpenAI/Claude → Asana/Jira → Google Sheets (UTM builder)

Time saved: 8+ hours/week

💡 Use this agent in Vellum!

2. Campaign Intelligence Agent

This agent idea comes from a Marketing Operations Professional who shared how their team uses it.

What it does: Automatically connects data across marketing tools to surface performance insights and identify what's actually driving results.

The problem it solves: Marketing teams are drowning in dashboards but starving for insights. Teams spend hours manually pulling reports and cleaning data instead of acting on insights.

How it works:

1. Trigger: Scheduled daily/weekly or on-demand when campaign milestones are hit.
2. Process: Connects to marketing stack, normalizes messy data, identifies performance patterns/anomalies, and drafts a narrative summary.
3. Output: Plain-language summary of what's working, what's not, and recommended next actions.

Tools it connects: Google Ads → HubSpot/Salesforce → Google Analytics → Slack

Time saved: 10-15+ hours/week

💡 Use this agent in Vellum!

3. Intent Intelligence Agent

This agent idea comes from a Marketing Operations Leader who shared how their team uses it.

What it does: Analyzes the context and intent behind every inbound engagement to recommend the right next action instead of treating all leads the same.

The problem it solves: "Traditional lead scoring treats a calculator user the same as someone who requested a demo," notes our expert. This leads to wasted sales time and frustrated prospects. Ops teams need to understand why someone engaged, not just that they engaged.

How it works:

1. Trigger: Any inbound engagement (form fill, calculator use, content download).
2. Process: Analyzes engagement type, content consumed, and behavioral signals to classify intent level and journey stage.
3. Output: Intent classification and a recommended next action (e.g., "Send Nurture B" vs. "Call Immediately").

Tools it connects: Website Analytics → Marketing Automation → CRM → Slack

Time saved: 8-12+ hours/week

💡 Use this agent in Vellum!

4. Routing Orchestration Agent

This agent idea comes from a Marketing Operations Leader who shared how their team uses it.

What it does: Manages data dependencies automatically and only routes leads when data is truly ready, with full visibility into decision logic.

The problem it solves: Leads get routed to sales with incomplete data because systems don't wait for enrichment. "The agents I wish I had today are less about doing tasks and more about handling the messy glue work between systems," says our expert.

How it works:

1. Trigger: New lead enters system.
2. Process: Checks data completeness; waits for enrichment tools to finish; validates data quality; applies routing logic only when conditions are met.
3. Output: Fully enriched, validated lead routed to the correct owner with a log of the decision.

Tools it connects: Form Source → Clearbit/ZoomInfo → CRM → Slack

Time saved: 5-8+ hours/week

💡 Use this agent in Vellum!

5. Conversation Intelligence Agent

This agent idea comes from a Marketing Operations Leader who shared how their team uses it.

What it does: Transforms sales call data into actionable marketing signals including objections, themes, and messaging gaps.

The problem it solves: Marketing teams operate in a black box, creating campaigns without real feedback from sales conversations. This agent turns unstructured call data into a feedback loop for campaign optimization.

How it works:

1. Trigger: Sales calls completed (daily batch).
2. Process: Transcribes calls; analyzes for recurring objections, competitor mentions, and questions; identifies gaps between marketing promises and sales reality.
3. Output: Weekly insight report with messaging recommendations and content gaps.

Tools it connects: Gong/Chorus → CRM → Slack → Notion

Time saved: 6-10+ hours/week

💡Use this agent in Vellum!

6. SEO Content Brief Agent

What it does: Generates comprehensive content briefs based on keyword intent, SERP analysis, and brand guidelines.

The problem it solves: Creating a high-quality SEO brief takes 45–60 minutes of research per article. Writers often receive vague instructions, leading to drafts that miss the search intent or lack internal linking opportunities.

How it works:

1. Trigger: Keyword added to "Planned" status in content calendar.
2. Process: Scrapes top 10 SERP results for the keyword; analyzes structure, headings, and gaps; identifies internal linking opportunities from your sitemap.
3. Output: A detailed brief with outline, target word count, required entities, and internal link suggestions.

Tools it connects: Semrush/Ahrefs → Google Search Console → Google Docs/Notion

Time saved: 10+ hours/week

💡 Use this agent in Vellum!

7. Ad Creative Variant Generator

What it does: Generates structured ad copy variations (hooks, bodies, CTAs) mapped to specific buyer personas and hypotheses.

The problem it solves: Paid media teams need to test constantly, but writing 50+ distinct ad variations is mentally draining and often results in repetitive, low-quality copy.

How it works:

1. Trigger: Request form with "Product," "Offer," and "Persona."
2. Process: Generates 10 distinct hooks (fear-based, gain-based, curiosity-based); pairs them with body copy and CTAs; checks against character limits.
3. Output: A CSV or Airtable view ready for upload to Meta/LinkedIn Ads.

Tools it connects: Airtable → OpenAI → Google Sheets

Time saved: 5+ hours/week

💡 Use this agent in Vellum!

8. Lead Enrichment & Cleanup Agent

What it does: Standardizes messy lead data (job titles, locations) and fills in missing firmographic details before sales sees them.

The problem it solves: "VP of Mktg," "Vice President Marketing," and "VP Marketing" are treated as three different roles in reporting. Ops teams spend hours normalizing fields to make segmentation work.

How it works:

1. Trigger: New record created in CRM.
2. Process: Standardizes job titles to a master taxonomy; fixes capitalization; infers missing geography based on phone/IP; flags obvious fake emails.
3. Output: Cleaned record updated in CRM.

Tools it connects: CRM (HubSpot/Salesforce) → Enrichment API → CRM

Time saved: 4+ hours/week

💡 Use this agent in Vellum!

9. Lifecycle Nurture Agent

What it does: Monitors email engagement and suggests content refreshes for underperforming nurture steps.

The problem it solves: Nurture sequences are often "set and forgotten." Marketers rarely have time to audit 12-month-old emails, resulting in stale content and declining open rates.

How it works:

1. Trigger: Weekly performance check of email automation steps.
2. Process: Identifies emails with open/click rates below baseline; analyzes subject lines and body copy against current best practices; drafts 2 alternative versions.
3. Output: A Slack alert with the underperforming email and suggested A/B test variants.

Tools it connects: Marketing Automation (Marketo/HubSpot) → LLM → Slack

Time saved: 3+ hours/week

💡 Use this agent in Vellum!

10. Landing Page QA Agent

What it does: Automated quality assurance for landing pages, checking links, UTMs, page speed, and mobile responsiveness.

The problem it solves: Manual QA is tedious and error-prone. Broken links or missing UTM parameters on a live ad campaign can waste thousands of dollars in spend before being caught.

How it works:

1. Trigger: URL submitted to "Ready for Launch" channel.
2. Process: Crawls the page; clicks every link to verify 200 status; checks for presence of GTM container; verifies form submission works; takes mobile screenshot.
3. Output: A "Pass/Fail" report with screenshots and list of errors.

Tools it connects: Slack → Headless Browser/Scraper → Slack

Time saved: 4+ hours/week

💡 Use this agent in Vellum!

11. Webinar Ops Assistant

What it does: Automates the repetitive logistics of event management, from speaker coordination to post-event follow-up.

The problem it solves: Hosting a webinar involves dozens of small tasks—collecting speaker bios, scheduling prep calls, uploading recordings, and cleaning attendee lists—that distract from the actual content strategy.

How it works:

1. Trigger: New webinar topic approved.
2. Process: Generates speaker invite emails; creates calendar holds; drafts the landing page copy; after the event, transcribes the recording and drafts the follow-up email with key takeaways.
3. Output: Draft assets delivered to the event manager at each stage.

Tools it connects: Zoom → Google Docs → Marketing Automation → Slack

Time saved: 6+ hours/event

💡 Use this agent in Vellum!

12. Social Listening & Response Agent

What it does: Monitors social channels for brand mentions and drafts on-brand responses for approval.

The problem it solves: Speed matters in social, but marketers can't stare at feeds 24/7. Opportunities to engage with positive mentions or mitigate negative ones are often missed or seen too late.

How it works:

1. Trigger: New mention of [Brand Name] or [Competitor] on LinkedIn/X.
2. Process: Analyzes sentiment; categorizes as "Support," "Praise," or "Troll"; drafts a response based on the brand voice guide.
3. Output: A notification in Slack with the post and a "One-click to publish" draft response.

Tools it connects: Social Listening Tool (or API) → LLM → Slack

Time saved: 5+ hours/week

💡 Use this agent in Vellum!

13. User Recapture Emailer

What it does: Classifies the intent of a new user who enters and engages with your application, and takes that intent to make a personalized email to re-engage the user and bring them back into your application.

The problem it solves: enables users with calls to action to re-engage and find value within a product/application

How it works:

1. Trigger: User leaves platform without performing a defined action
2. Process: Analyzes their conversations with platform to classify intent
3. Output: Sends a personalized email to enable user to return and perform desired action

Tools it connects: User conversations data → Hubspot

Time saved: 20+ hours/week

💡 Use this agent in Vellum!

14. Content Repurposing Agent

What it does: Takes a high-performing blog post or whitepaper and atomizes it into social posts, newsletter snippets, and slide decks.

The problem it solves: Great content often dies after one publish because teams lack the bandwidth to reformat it for other channels. This agent ensures maximum distribution for every asset.

How it works:

1. Trigger: New blog post published (RSS feed or URL).
2. Process: Extracts key stats and quotes; formats them into a LinkedIn carousel text structure; writes a Twitter thread; drafts a newsletter blurb.
3. Output: A "Distribution Kit" document.

Tools it connects: CMS (WordPress/Webflow) → OpenAI → Google Docs/Canva

Time saved: 4+ hours/week

💡 Use this agent in Vellum!

15. Competitor Monitor

What it does: Tracks competitor website changes, pricing updates, and new ad launches to alert the team to strategic shifts.

The problem it solves: Competitive intel is usually ad-hoc. Teams miss subtle changes like a competitor changing their H1 to target a new persona or quietly raising pricing until it's too late to react.

How it works:

1. Trigger: Daily scan of competitor URLs.
2. Process: Compares current page text/HTML to yesterday's version; detects significant changes (ignoring dynamic elements like dates); summarizes the shift.
3. Output: A "Market Intel" digest in Slack.

Tools it connects: Scraper → Diff Checker → Slack

Time saved: 2+ hours/week

💡 Use this agent in Vellum!

Marketing Operations Agent Reference Table

Key Trends Shaping AI Agents for Marketing

Based on the latest research from 2024-2025, here are the key trends and statistics regarding AI agents and automation in marketing.

1. Rapid Integration of Task-Specific Agents into Enterprise Apps

The era of standalone chatbots is ending as "agentic AI" becomes embedded directly into software workflows. By the end of 2026, 40% of enterprise applications will be integrated with task-specific AI agents, up from less than 5% in 2025 [1].

2. Explosive Growth in Automated Customer Interactions

Customer-facing AI agents are moving beyond simple support queries to handling complex marketing and sales interactions autonomously. The number of customer interactions automated by AI agents is projected to grow from 3.3 billion in 2025 to more than 34 billion by 2027 [2]. This trend validates the necessity for "Customer Experience" and "Sales Development" agents in the 2026 marketing stack.

3. Significant Conversion Lifts from Agentic Workflows

Unlike early generative AI which focused on content volume, the new wave of AI agents drives measurable bottom-line results. Marketing teams deploying agents for lead nurturing and personalization are seeing direct improvements in conversion rates. Organizations integrating AI agents into their existing marketing operations saw, on average, a 23% increase in lead conversion rates over a twelve-month period [3].

4. The Shift from Production to Strategy

As AI agents take over execution tasks—such as data analysis, content resizing, and ad bidding—human marketers are being freed to focus on high-level strategy. This necessitates the adoption of "Operations" and "Analytics" agents to handle the grunt work with 75% of companies that use AI for marketing reporting will shift their workforce to more strategic activities as agents handle execution [4].

5. High Experimentation and Scaling of Agentic Systems

We have crossed the chasm from "playing with ChatGPT" to deploying autonomous agents. 62% of organizations report they are at least experimenting with AI agents, with 23% already scaling agentic AI systems within at least one business function [5]. A significant portion of the market is now actively scaling these systems, meaning marketing teams without a defined "AI Agent" strategy in 2026 will be competitively disadvantaged.

How to Evaluate AI Agent Ideas

Before you build, score your ideas against these practical criteria.

How We Chose These Agent Ideas

We didn't just pick random cool tech. We filtered for impact.

Why Marketers Use Vellum

Vellum AI is an AI agent builder designed to help teams automate boring operational work. Anyone can create AI agents by simply describing the task they want done. No code, no workflow wiring, no AI expertise required. Vellum handles the underlying complexity so teams can go from idea to working agent that meaningfully automates work in minutes.

Marketing teams are drowning in "glue work"—moving data between HubSpot and spreadsheets, reformatting briefs for different channels, and manually checking UTMs. Vellum is ideal for these teams because:

• It connects to your stack: Direct integration with HubSpot, Google Ads, Slack, and Google Sheets means you don't need to change your tools.
• It fits your workflow: You don't need to learn a new flowchart software. You just describe the process you already do.
• It's shareable instantly: Marketing Ops can build a "Campaign QA Agent" and share it with the whole content team in one click.

Why Vellum Stands Out

• Describe the work, not the workflow: You tell Vellum what the agent should do in plain English. No flowcharts, no node wiring, no scripts to maintain.
• Go from idea to live agent in minutes: Most teams build their first working agent the same day, without long setup or onboarding.
• Built for real operational work: Vellum is optimized for tasks like campaign setup, lead routing, QA, reporting, and data cleanup, not just content generation.
• No AI expertise required: You do not need to be a prompt engineer or developer. If you understand the process, you can automate it.
• Handles the complexity for you: Model selection, tool connections, logic, and context are managed by Vellum so agents stay reliable as they scale.
• Connects to your existing stack: Works directly with tools like HubSpot, Google Ads, Slack, Google Sheets, and more without forcing new systems.
• Easy to share across teams: Build an agent once and share it as a reusable internal tool anyone on the team can use.
• Designed for trust and reuse: Agents are built to be consistent and observable, so teams actually adopt them instead of working around them.

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Getting Started With Your First Agent in 5 Minutes

Step 1: Describe your task

Prompt Vellum with what you want the agent to do in plain English. Be specific about the trigger and the output.

Example prompt for a Marketing Lead Agent:

"When a new lead comes in from LinkedIn Ads, research their company size and recent news, and add the enriched data to our HubSpot CRM. Then draft a personalized outreach email based on their industry and save it as a draft for review."

Step 2: Connect your tools

Link the apps your marketing team already uses daily.

• Communication: Slack, Gmail
• Data: Google Sheets, HubSpot/Salesforce
• Ads: LinkedIn Ads, Google Ads

Step 3: Test it

Run the agent with a dummy lead or a past campaign brief. Watch it execute the steps. Adjust the instructions if the tone isn't right.

Step 4: Share it

Deploy for your team with one click. The SDRs or Content Writers can use it immediately without needing to know how it was built.

Time to first working agent: Under 10 minutes.

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FAQs

1. How do marketing teams actually use Vellum day to day?

Marketing teams use Vellum to run the operational work around campaigns. This includes turning briefs into assets, routing and enriching leads, QAing landing pages, summarizing performance, refreshing nurture sequences, and monitoring competitors, all inside the tools they already use.

2. How long does it take to build a marketing agent in Vellum?

Most marketing teams build their first working agent in under 10 minutes. You describe the workflow in plain English, connect your tools, and test it with real campaign or lead data.

3. Do I need marketing ops or engineering support to use Vellum?

No. Vellum is built so marketing and revenue ops teams can own their automations. You do not need engineers to build or maintain agents for common campaign, reporting, or lifecycle workflows.

4. How is Vellum different from using AI for content generation?

Content generation stops at text. Vellum agents connect tools, move data, apply logic, and complete multi step work. Instead of just writing copy, agents can create UTMs, update CRMs, route leads, trigger follow ups, and deliver outputs teams actually act on.

5. Can Vellum work with our existing marketing stack?

Yes. Vellum connects directly to tools like HubSpot, Salesforce, Google Ads, GA4, Slack, Google Sheets, and common CMS platforms. You do not need to change your stack or rebuild workflows.

6. How do marketing teams ensure agents are reliable and trustworthy?

Agents in Vellum are easy to test before rollout. Marketing ops teams can run them on historical campaigns or sample leads, see exactly what happens, and add guardrails before sharing them with the wider team.

7. How do we roll agents out to the rest of the marketing team?

Once built, agents can be shared with one click. They become simple internal tools the rest of the team can run without understanding how they were built, which significantly improves adoption.

8. What kind of time savings do marketing teams see with Vellum?

Most marketing teams save 5 to 10 hours per week per agent. Agents focused on campaigns, reporting, QA, and lead operations often save even more.

9. Is Vellum only useful for large or enterprise marketing teams?

No. Smaller teams often see outsized benefits because agents reduce context switching and manual coordination. Vellum works for lean growth teams as well as large marketing organizations.

10. What types of marketing workflows are best to automate first in Vellum?

The best starting points are repetitive, high volume tasks like campaign setup, reporting, lead routing, enrichment, QA checks, and nurture maintenance. These deliver fast wins and immediate ROI.

11. What happens as our marketing workflows become more complex over time?

Teams typically start simple and layer in more logic as needed. While some advanced SDK features still require engineering support, most marketing operations use cases can be handled without code in Vellum.

Extra Resources

• Complete 2026 Guide to AI Agent Builders →
• Beginner’s Guide to Building AI Agents →
• Best Enterprise AI Agent Builder Platforms →
• Best Low code AI Workflow Automation Tools →
• Best AI Workflow Platforms →

Citations

[1] Gartner. (2025). Gartner Predicts 40% of Enterprise Apps Will Feature Task-Specific AI Agents by 2026.

[2] Demand Gen Report. (2025). AI Agents Revolutionized B2B Marketing in 2025.

[3] Market Vantage. (2025). AI Agents in Marketing for 2025.

[4] Digital Marketing Institute. (2025). 10 Eye Opening AI Marketing Stats to Take Into 2026.

[5] McKinsey & Company. (2025). The state of AI in 2025: Agents, innovation, and transformation.