Generalist AI vs specialist AI: Where marketers see real impact in both

Horizontal AI, vertical AI, or departmental AI may not be in your vocabulary (yet). But as marketers spend more time with AI—testing prompts, building workflows, connecting tools—we start to unlock more language, more nuance, more specific needs, and yes... more specific problems.

What begins as "let's use AI for this", quickly becomes:

• Which AI?
• Built for what?
• Built for who?

This is the discussion—sometimes debate—around generalist vs specialist AI. The type everyone uses (ahem, ChatGPT) and the platforms that are purpose-built to guide you through your industry, your workflows, your pain points, and those pesky compliance requirements.

But horizontal vs vertical or departmental AI isn't about picking sides. It's about understanding how (and when) to put each to work to drive marketing performance.

Let's talk about:

• What horizontal AI, vertical AI, and departmental AI actually mean
• Where marketing teams see impact from all of the above
• Which solutions provide strategic value (not just novelty)

...and ultimately, which AI subscription is really worth your team's limited budget? 🧐

Generalist AI vs specialist AI: Definitions + differentiations

...because a vote for us, is a vote for straight-forward, simple, no-jargon definitions.

Okay, define: Horizontal AI

Horizontal AI is general-purpose AI.

It's designed to work across any industry, any role, and any use case. It's broad by design. Think: writing assistance (eg. the almighty "Please tighten up and strengthen this copy"), brainstorming, summarization, coding help, research support... to a degree.

The thing is that generalist or horizontal AI doesn't know your industry or role requirements unless you teach it. It doesn't come pre-configured with your workflows, and it's not integrated with all the tools you use on a daily basis. Sure, it's flexible, adaptable, and pretty impressive—but it's fair to say, it's neutral.

For marketers, horizontal AI is often the entry point. Where discovery happens, like:

• Exploring campaign ideas
• Drafting content
• Testing positioning
• Analyzing customer feedback
• Pressure-testing messaging

See it as the sandbox or your thinking partner (...especially when you forgot to prepare for that meeting you have in 2 minutes).

Examples of horizontal AI: ChatGPT, Claude, Gemini

Okay, now define: Vertical AI and departmental AI

On the other hand, we've got specialized AI. This can be split into vertical AI and departmental AI—both of which are purpose-built, rather than generalist.

Vertical AI: Vertical AI is industry-based, so for example "For any company within the legal industry"

Departmental AI: Departmental AI is team-based, so for example "For legal teams, within any industry"

In short, specialist AI is built for a specific industry, team, function, or workflow. It's more granular.

Instead of being trained to 'do a lil bit of everything', vertical and departmental AI solutions are designed to solve defined problems within a domain—like healthcare documentation, legal contract reviews, or marketing campaign orchestration (oi oi).

Examples of vertical AI: hyperexponential for insurance industry, Abridge for the healthcare industry

Examples of departmental AI: Harvey for legal teams, Optimizely Opal for marketing teams

So, seeing as we're biased. Let's take a look at AI for marketing teams specifically. For marketers, departmental AI will:

• Understand structured campaign workflows
• Embed brand guidelines and governance rules
• Align to approval processes
• Connect directly into your CMS, DAM and analytics
• Make your lives a h e l l u v a lot easier (basically)

All so you can scale on-brand content faster, stay compliant, get insights at your fingertips... without the bottlenecks and waiting around for what-seems-like years.

With specialist AI, you can sit back, relax, and watch it operate inside your operating model. Not just generate content for content's sake.

A simple conclusion for a simple definition

Generalist for discovery and specialist for delivery.

Like we said, simple.

The issues marketers can have with only using horizontal AI

General-purpose AI tools like ChatGPT from OpenAI, Claude from Anthropic, and Gemini from Google are powerful. They’re flexible. They’re usually the first place marketing teams experiment with AI—and for good reason too.

But when a general tool becomes the core engine of your marketing operations, a few cracks start to show.

Here's where marketing teams can butt heads with horizontal or generalist AI:

1. The "I guess that's... fine" loop

   
   Yes, horizontal AI creates content (and don't your LinkedIn-happy sales team know it). The content it creates, however, is just... well, adequate (most of your sales team hasn't picked up on that yet).
   
   It's grammatically clear, structured logically, and confident in tone—but it is generic. It doesn't know your category nuances, your positioning battles, or your internal strategy debates. Which means marketers end up doing what marketers have got used to doing: refining.
   
   You layer in category insight, tighten up the POV, strip out those vague claims, inject personality, and then align it to the campaign strategy. What was meant to save time just turned into a heavy editing cycle.
   
   Where vertical AI steps in: Instead of starting from generic internet-trained patterns, vertical AI is configured around your industry, your workflows, your brand guardrails, and your campaign objectives. The output doesn't just 'sound good'; it's structurally aligned to how your team actually goes to market. You're refining strategy, not fixing tone.

2. The governance and compliance blind spot

   
   Generalist AI is oblivious to your brand guidelines, legal disclaimers, and unique tone of voice. Unless you manually embed those rules into every prompt (and keep them updated), the model is simply guessing.
   
   The guesswork creates review cycles. Legal back-and-forth. Delays. Sometimes even risk. And do we want any of that? No 👏 we 👏 don't 👏.
   
   Where vertical AI steps in: On the other hand, vertical AI platforms are designed to operate within guardrails—your brand guidelines can be embedded, approval processes reflected, and compliance logic integrated into the workflow itself. No more relying on memory or manual checks because governance is part of the system. This is especially useful to marketing teams working in regulated or brand-sensitive industries.

3. The integration headache

   
   Don't know if you've noticed but that back-and-forth you've got going with ChatGPT is painfully disconnected from your CMS, DAM, analytics, and project management or workflow tools. And that's the thing: horizontal AI works in a silo.
   
   The relentless cycle of copy-pasting into a chat interface, hoping your spreadsheet translates properly, reformatting long-form content, and assuming that AI hasn't made up any wild percentages or statistics for your decks.
   
   Where vertical AI steps in: You could say that vertical AI lives inside your current tech stack. Marketing-specific AI plugs directly into content systems, approval flows, analytics, and orchestration tools. Instead of generating content in isolation, it's here to help with execution and let work move forward without as many manual hand-offs. Efficiency 101.

4. The context ceiling of generic output

   
   General or horizontal AI tools do generate ideas—and some of them are good, sure. But these tools are blind to your specific customer or pipeline data, past campaign performance, and what truly resonates with your audience.
   
   Its insights are generic, not granular... even when you demand precision after some pretty vague outputs. It lacks your human judgement, but also your bespoke data that makes things more personal to your audience.
   
   Where vertical AI steps in: Vertical AI is fueled by your proprietary marketing data and proven best practices (AKA insights from the campaigns that slapped). It deciphers your unique context, allowing it to generate laser-focused content and strategies, made for your business... and your business only.

5. Scaling the wrong thing entirely

   This is the quiet risk. Teams adopt general AI to scale content production. But if every asset still requires manual brand review, compliance checks, formatting, publishing, and reporting, you haven’t scaled marketing.
   
   You’ve scaled draft generation, and you've scaled the time spent on things you don't want to be spending time on.

   Where vertical AI steps in: Vertical AI focuses on scaling the system, not just the output. It automates parts of governance, it integrates with workflows, and it ties creation closer to performance data. The result isn’t just more content — it’s more coordinated, compliant, revenue-aligned execution. And really, it's letting you get back to why you joined marketing in the first place.

None of this means horizontal AI or generic AI is obsolete—no way. It's great for brainstorming, exploration, pressure-testing messaging, and speeding up first drafts.

But when marketing leaders start asking questions like:

• "How do we operationalize this?"
• "How to we make it repeatable?"
• "How do we reduce risk but increase impact?"

...that's where specialist AI starts to look less like a novelty and more like infrastructure you need. Pronto.

How Optimizely Opal changes the game for marketers

This is where Optimizely Opal enters the arena. As a departmental AI, Opal is purpose-built for marketers, enabling them to create and scale agents, as well as true agentic workflows—no code (or bugging your developers) required. Here's what you need to know about Optimizely Opal:

• Built-in, not bolt-on: Seamlessly integrated into your marketing operations, not just an add-on.
• Always-on brand and compliant: Guarantees content meets your standards automatically.
• Enterprise-grade quality and reliability: Built on industry-leading evaluation frameworks.
• No develop dependencies: Create agents and workflows with a low/no-code interface.
• Orchestrated workflows: Effortlessly manages and automates your entire marketing process.

Ready to stop settling for 'adequate' and start driving real marketing performance? Find out what Optimizely Opal can do for you.