Marketing teams today have no shortage of AI tools to choose from. A quick search throws up hundreds of options, each promising to save time, cut costs or “revolutionize” your workflow. The real challenge isn’t finding AI. It’s knowing which AI tool solves which marketing problem, and where it fits into a campaign that already spans paid media, organic search, email, social and now, AI search.
This article doesn’t attempt to rank tools or pick winners. Instead, it groups the most useful AI marketing automation tools by the stage of the marketing workflow they support, from strategy and planning to creation, distribution, SEO and the newest frontier: AI visibility. Along the way, we’ve pulled in our own experience running these tools inside a media planning business, along with the reservations our brand team still has about handing certain jobs over to AI.
“We’ve tested most of these tools inside our own campaigns before writing a word about them here. Some earned a permanent place in our workflow. Others we still use with a fair bit of caution.” — Arpita Nayak, Head of Marketing, The Media Ant
Why AI marketing tools need a framework, not a list
Most marketing teams don’t lack tools. They lack a system for using them. A tool for writing ad copy is not a substitute for one that plans media spends. A tool that tracks keyword rankings won’t tell you whether ChatGPT is recommending your brand to a prospective customer. Each of the twelve tools below sits at a different point in the campaign lifecycle. Together, they map out what a modern AI marketing stack can look like.
At The Media Ant, our own content workflow reflects this layered approach. “We use ChatGPT to brainstorm angles, Perplexity to fact-check and research those angles, and then bring everything together with more structured tools for the actual write-up,” says Arpita Nayak, Head of Marketing at The Media Ant. “None of these tools does the whole job on its own. That’s really the point of this article.”
Why AI marketing tools need a framework, not a list
Most marketing teams don’t lack tools. They lack a system for using them. A tool for writing ad copy is not a substitute for one that plans media spends. A tool that tracks keyword rankings won’t tell you whether ChatGPT is recommending your brand to a prospective customer. Each of the twelve tools below sits at a different point in the campaign lifecycle. Together, they map out what a modern AI marketing stack can look like.
At The Media Ant, our own content workflow reflects this layered approach. “We use ChatGPT to brainstorm angles, Perplexity to fact-check and research those angles, and then bring everything together with more structured tools for the actual write-up,” says Arpita Nayak, Head of Marketing at The Media Ant. “None of these tools does the whole job on its own. That’s really the point of this article.”
AI Strategy & Research
Before a single ad is booked or a line of copy is written, most campaigns start with research. This is where general-purpose AI tools have quietly become part of the marketer’s toolkit.
ChatGPT
ChatGPT has become the default starting point for campaign ideation. Marketers use it for messaging drafts, positioning statements, brainstorming sessions and quick customer research summaries. It’s fast, conversational and good at generating a wide spread of ideas in minutes. Part of why it’s the default: ChatGPT crossed 900 million weekly active users in early 2026, and roughly a third of consumers now say they begin their searches with an AI tool rather than a traditional search engine, according to industry tracking cited by Search Engine Land.
ChatGPT works best with a clear prompt and context behind it — the more specific the input on your market and goals, the more useful the output.
“I use ChatGPT the way I’d use a sharp junior teammate in a brainstorm,” says Arpita Nayak. “It throws out ten ideas fast, and two or three of them are worth developing. The other seven need to be thrown out, and you need to know your market well enough to tell which is which.”
Perplexity
Where ChatGPT is good at generating ideas, Perplexity is better at finding facts. It’s built around real-time web search against an index of more than 200 billion URLs, with most answers carrying somewhere between three and ten inline citations linking each claim back to a source. That structure makes it useful for competitor research, trend discovery and sourcing information before a campaign brief is written.
One advantage marketers will appreciate is that Perplexity shows its sources. This matters when you’re building a business case internally and need to point to where a claim came from, rather than relying on an AI-generated statement with no trail behind it.
“Perplexity has become our first stop for fact-checking. If a number or a claim can’t be traced back to a source, it doesn’t go into the article. That’s non-negotiable for us.” — Arpita Nayak, Head of Marketing, The Media Ant
AI Campaign Planning
Once the research is done, planning begins. This is where media buying decisions, budget allocation and channel selection come into play, and where AI-powered planning tools are starting to replace spreadsheets and guesswork.
Ant10
Ant10 is The Media Ant’s AI-powered media planning platform, built to simplify how marketers discover media options, estimate budgets and plan campaigns across channels. Rather than functioning as a generic content generator, Ant10 is designed specifically around the mechanics of media planning: matching campaign goals to media inventory, recommending channels based on audience and budget, and estimating costs before a plan is finalised.
“Most AI tools in marketing are built for content. Ant10 was built for the problem that comes before content: where do you spend, and how much,” says Arpita Nayak. “We built it because we were solving this manually for years, across cinema, radio, digital, print and outdoor. Ant10 is really us handing that process over to AI, but keeping a planner in the loop to sanity-check the output.”
For marketers managing multi-channel campaigns, this kind of AI-assisted planning cuts down the manual back-and-forth that media planning has traditionally involved.
AI Content & Creative Creation
With strategy and planning in place, the next stage is producing the actual assets: banners, ad copy, social creatives and campaign visuals.
Sivi AI
Sivi AI takes a different approach to AI design than most tools in this category. Rather than generating a flat image, it produces layered, fully editable files, with text, vectors and images each sitting on their own layer, so marketers can adjust copy, colours or elements after generation instead of starting over. It covers a wide range of formats: display ads, social posts, banners, YouTube thumbnails and ecommerce graphics, all built to fit any custom dimension.
The standout feature for marketers working across Indian markets is language support. Sivi generates designs in 72+ languages, which matters for a country where campaigns often need to run in English alongside Hindi and regional languages, without the composition breaking. The platform also lets teams upload a brand kit, so generated designs stay within defined fonts, colours and components rather than drifting off-brand with every new creative.
It’s also worth noting that Sivi has been recognised by the Government of India (MeitY, IndiaAI) and the Government of Karnataka, alongside recognition from Google Cloud and NVIDIA Inception. “On paper, it looks like one of the stronger options for Indian marketers specifically, mainly because of how seriously it treats regional-language design, not just English,” says Arpita Nayak, Head of Marketing at The Media Ant.
AI-generated design output tends to benefit from a quick human review pass before it ships, particularly for brand consistency across a large creative set — a good habit with any design tool, Sivi included.
The Media Ant AI Ad Copy Generator
Writing ad copy at scale, across Meta, Google and other platforms, is repetitive work that eats into a copywriter’s time. The Media Ant’s AI Ad Copy Generator is built to help with exactly this: generating headlines, CTAs and campaign messaging variations quickly.
This is a productivity tool built for volume. “If a campaign needs a dozen headline variations for testing, this saves real hours,” notes Arpita Nayak.
Canva Magic Studio
Canva’s Magic Studio brings AI features into a tool most marketing teams already use daily: resizing creatives across formats, editing images and generating presentation decks and social assets. Its strength is convenience — it removes a lot of the manual resizing and formatting work that eats into a design team’s time.
For teams whose campaigns are English-only, Canva is often the simpler starting point. “If you’re not designing across multiple Indian languages, Canva is genuinely the easier tool to pick up,” says Vaishali Tripathi, Brand Manager at The Media Ant. “Our team already knows it well, the template library is huge, and there’s almost no learning curve. We reach for a more specialised design AI only when a campaign needs something Canva’s templates can’t quite stretch to.”
AI Distribution & Marketing Automation
Once content exists, it needs to reach the right audience through the right channel, at the right time. This is where marketing automation platforms come in.
HubSpot AI
HubSpot’s AI layer, rebranded as Breeze AI, spans its Marketing, Sales and Service Hubs. It centres on Breeze Copilot, an assistant that drafts content, researches contacts and summarises CRM records, alongside a set of Breeze Agents built for specific jobs: a Customer Agent for support conversations, a Prospecting Agent for lead research, and a Data Agent that keeps CRM records clean. For teams already using HubSpot, the AI features add incremental value, such as suggesting subject lines, summarising lead activity or automating follow-up sequences. Because these features sit on top of existing CRM data, the automation tends to be grounded in real customer behaviour rather than generic rules. Teams looking for lighter alternatives can consider Mailchimp AI or ActiveCampaign AI, both of which offer similar automation capabilities at a smaller scale.
Organic Search & Discoverability
Even as AI search grows, traditional SEO hasn’t gone away. If anything, it remains the foundation that AI search visibility is built on.
Ahrefs
Ahrefs remains one of the most reliable tools for SEO audits, backlink analysis and identifying keyword opportunities. Its index has grown to roughly 35 trillion tracked backlinks and close to 29 billion keywords across 200-plus locations, which makes it useful for competitive link analysis and technical SEO health checks. Worth noting: Ahrefs has extended into AI visibility too, with a Brand Radar feature that tracks brand mentions across ChatGPT, Perplexity, Google AI Overviews, Gemini and Copilot, built on a database of over 100 million tracked prompts.
Semrush
Semrush covers similar ground with a stronger focus on keyword research, competitor tracking and content optimisation, working off a database of roughly 27 billion keywords and 43 trillion backlinks. Many teams use Ahrefs and Semrush alongside each other, since each surfaces slightly different data and insights. Semrush has also added an AI Visibility Toolkit that tracks brand mentions, sentiment and share of voice across ChatGPT, Perplexity, Gemini, Copilot and Google AI Overviews, drawing on a dataset of tracked prompts to estimate how often a brand surfaces in AI answers.
SEO still matters in the AI era for a simple reason: most AI search tools and chatbots pull their answers from indexed web content. If your site isn’t well optimised for traditional search, it’s less likely to be cited or referenced by AI systems either. Organic search and AI visibility aren’t competing priorities. They’re increasingly connected, which is exactly why platforms built for one are now building toward the other.
AI Visibility & Brand Measurement
This is where the marketing conversation is heading next, and it deserves closer attention.
Traditional analytics tools tell marketers a lot: clicks, conversions, ROAS, traffic sources. What they don’t tell you is an increasingly important question: is AI recommending your brand?
More buyers are starting their research not with a Google search but with a question to ChatGPT, Google’s AI Overviews, Gemini, Claude or Perplexity. The numbers back this up: roughly 37% of consumers now say they begin searches with an AI tool rather than a traditional search engine, and a G2 study from April 2026 found that 51% of B2B software buyers now start research with an AI chatbot more often than with Google, up from 29% less than a year earlier. Separately, an oft-cited McKinsey estimate puts the share of brands systematically tracking their AI search visibility at as low as 16%, meaning most marketing teams are effectively flying blind on this channel. These tools synthesise answers from across the web and, in doing so, decide which brands get mentioned and which don’t. A brand invisible to AI search risks losing relevance with a growing segment of buyers, even if its traditional SEO rankings look healthy.
This shift has a name: Generative Engine Optimization, or GEO. It’s the practice of optimising content so that AI systems are more likely to reference, cite or recommend a brand when answering user queries. It sits alongside SEO rather than replacing it, but it requires its own measurement approach, since traditional analytics wasn’t built to track how AI models are treating a brand.
SEO optimised pages for search engines. GEO optimises brands for AI conversations. Part of why this matters is that AI models don’t sort content by channel the way marketing teams do. “Your best-performing ad may disappear in a week. A useful article can influence AI recommendations for months,” says Arpita Nayak. A campaign, an SEO push, an email newsletter — an AI system doesn’t distinguish between where content came from, only whether it’s useful enough to reference. “Every campaign leaves a digital footprint,” she adds. “The question is whether AI can find it, trust it and recommend it.”
We’ve actually gone through this evaluation ourselves, testing a handful of AI visibility tools before settling on what works for our workflow. Here’s how Arpita Nayak, Head of Marketing at The Media Ant, describes that journey:
“We’ve used several AI visibility tools. They were an absolute delight when we didn’t know where to start. These tools gave us a starting point, but at some stage, the efficiency depends on knowing what needs to be done, not just knowing that something needs to be done. Seerly bridges that gap by giving recommendations, and not only that, it gives the first draft too. It also covers regular SEO metrics like GSC clicks and GA4 traffic, so we get everything in one dashboard.”
That distinction is worth sitting with, and it’s not just our team’s read. Most tools in the AI visibility category are built around monitoring — showing where a brand appears across ChatGPT, Perplexity and Google AI Overviews, and comparing that against competitors. Where Seerly adds something the rest of the category doesn’t is in what happens after the read: turning a visibility gap into an evidence-backed recommendation and a first draft, in the same workflow.
Seerly
“The next frontier of marketing isn’t ranking on Google. It’s being recommended by AI.” — Arpita Nayak, Head of Marketing, The Media Ant
Seerly is one of the emerging platforms built specifically to close that gap. It tracks brand visibility across ChatGPT, Google AI Overviews, Perplexity, Gemini and Claude, and runs on a three-step workflow: it starts by diagnosing where a brand is underrepresented or losing to competitors in AI-driven answers, then serves evidence-backed recommendations that point to specific competitor citations and content patterns that are working, and finally lets a team generate and publish optimised content directly from those recommendations rather than starting from a blank page.
Beyond visibility tracking, it goes further into:
- Content recommendations, suggesting what kind of content is more likely to get cited by AI systems, and providing a first draft rather than leaving the team to start from a blank page
- Competitor insights, showing how a brand’s AI visibility compares against others in its category
- Prompt tracking, monitoring the specific queries and prompts where a brand does or doesn’t appear
- Citation monitoring, tracking which sources AI tools are pulling from when they mention a brand
- Agent-led automation, which helps surface and act on optimisation opportunities without requiring a team to manually audit every AI response
- Consolidated SEO metrics, connecting Google Search Console clicks and GA4 traffic data alongside AI visibility numbers, so teams aren’t switching between dashboards to see the full discoverability picture
For us, the standout wasn’t the visibility score itself, it was the jump from “here’s a gap” to “here’s a draft to fix it.” That’s where Seerly’s recommendations and agent-led automation have made the biggest difference to how much time we spend acting on AI visibility data versus just reading it.
For context on why this category exists at all: research from Seer Interactive found a roughly 61% drop in organic click-through rate on searches where Google’s AI Overviews appear, while Adobe Analytics tracked a 393% year-over-year jump in AI-driven traffic to US retail sites in the first quarter of 2026. Both point the same direction, AI-generated answers are absorbing a growing share of the clicks that used to go to a ranked link, which is precisely the gap AI visibility tools are trying to help brands close.
It’s worth being clear-eyed here: AI visibility measurement is still a young category, and no single platform has all the answers yet. Seerly is one of a growing set of AI visibility tools addressing this space, and marketers evaluating GEO platforms should expect the category itself to keep evolving over the next few years.
Other AI Marketing Tools Worth Exploring
Beyond the tools covered above, a few others are worth knowing about, even if they don’t warrant their own section.
- Napkin AI converts pasted text, bullet points or outlines into flowcharts, diagrams and infographic layouts in under a minute. It’s built for single visuals rather than full decks; for a complete presentation, most reviewers point teams toward Gamma instead.
- Gamma generates entire multi-card presentations, documents and web pages from a single prompt, with a responsive, scrollable format that reads well on both desktop and mobile. Where Napkin produces individual diagrams, Gamma builds the whole deck.
- Ideogram built its early reputation on generating legible, accurate text inside AI images, useful for banners and social creatives with embedded copy. By 2026, more tools in the category — including Adobe Firefly and Recraft — have added strong typography handling too, giving marketers a wider set of solid options.
- Similarweb offers traffic and competitive intelligence, and has extended into AI search with an AI Traffic module that shows actual clicks a site receives from ChatGPT, Perplexity and Gemini, alongside an AI Brand Visibility module tracking how often a brand appears in AI-generated answers.
- Otterly is another player in the AI search visibility space, tracking brand mentions and sentiment across AI-generated answers, similar in category to Seerly, with a focus on monitoring.
Comparison Table
| Tool | Category | Best For |
| ChatGPT | Strategy & Research | Ideation, messaging, brainstorming |
| Perplexity | Strategy & Research | Market and competitor research with citations |
| Ant10 | Campaign Planning | AI-powered media planning and budget estimation |
| Sivi AI | Content & Creative | Banner and social creative generation |
| AI Ad Copy Generator | Content & Creative | Ad headlines and CTA generation |
| Canva Magic Studio | Content & Creative | Resizing, editing, presentations |
| HubSpot AI | Distribution & Automation | Email automation, lead nurturing, CRM |
| Ahrefs | Organic Search | SEO audits, backlinks |
| Semrush | Organic Search | Keyword research, competitor tracking |
| Seerly | AI Visibility & Measurement | AI search visibility, content and citation insights |
| Otterly | AI Visibility & Measurement | AI brand mention tracking |
| Ubersuggest | AI Visibility & Measurement | Early-stage AI visibility and keyword tracking |
Frequently Asked Questions
What are AI marketing automation tools? AI marketing automation tools use artificial intelligence to handle tasks across the marketing workflow, from research and planning to content creation, distribution and measurement, reducing manual effort and speeding up campaign execution.
What is AI search visibility? AI search visibility refers to how often and how favourably a brand appears in AI-generated answers from tools like ChatGPT, Google AI Overviews, Gemini, Claude and Perplexity, when users ask questions relevant to that brand’s category.
How is AI visibility different from SEO? SEO measures how well a website ranks in traditional search engine results. AI visibility measures whether and how a brand is mentioned or cited within AI-generated answers, which draw from a different mix of signals, including content structure, citations and perceived authority.
Which AI marketing tools are best for agencies? Agencies managing multiple client accounts typically benefit most from planning tools like Ant10, research tools like Perplexity, and measurement tools like Seerly, since these support work across strategy, execution and reporting at scale.
Which AI tool is best for campaign planning? Ant10 is built specifically for AI-powered media planning, covering media discovery, budget estimation and cross-channel recommendations, making it a strong fit for planning-stage work.
How can marketers measure AI visibility? Marketers can track AI visibility using platforms like Seerly, which monitor how often a brand appears in AI-generated responses, track relevant prompts, and identify content and citation opportunities to improve that visibility over time.
What is Generative Engine Optimization (GEO)? Generative Engine Optimization, or GEO, is the practice of optimising content so that AI systems are more likely to reference, cite or recommend a brand when generating answers to user queries. It works alongside traditional SEO rather than replacing it.
Conclusion
Marketing success is no longer measured only by clicks, impressions or conversions. Modern marketers need visibility across every discovery channel, paid, organic, social and increasingly, AI-generated search experiences.
“The tools will keep changing,” says Arpita Nayak, Head of Marketing, The Media Ant. “What won’t change is that someone on the team needs to know which problem each tool is actually solving. That’s the difference between a stack that works and a pile of subscriptions.” As she puts it elsewhere: “The best AI stack isn’t the one with the most tools. It’s the one with the fewest gaps.”
The best AI marketing stack isn’t about finding one platform that does everything. It’s about combining specialised tools that work well together, from planning campaigns with Ant10 and creating content with AI, to improving discoverability through SEO and measuring AI search visibility with platforms like Seerly.
The future of marketing isn’t just about reaching audiences. It’s about making sure your brand is discoverable wherever customers, and increasingly, AI, go looking.