When you hear terms like AI-first service, AI marketing, AI-powered service, AI creative, or AI automation agency, do they all mean the same thing? (And we have blogs about each one, as different topics.)
At first glance, the terminology appears to be a collection of acronyms.
However, for marketers and digital marketing agencies making decisions about partnerships or investments (working with one of them or building one), these terms carry real implications about strategy, capabilities, and outcomes.
The proliferation of AI terminology is not accidental. As the OECD observed:
AI means different things to different people.
And there is still no universally accepted definition of what qualifies as artificial intelligence. This ambiguity has created space for the marketing ecosystem to define themselves in niche ways, aligning terminology with their service models.
In this blog, we will examine the main categories of AI agencies, explore what differentiates them, and explain why terminology has fragmented so quickly. By the end, we’ll understand how to interpret these labels and what to look for when evaluating AI-driven partners.
What’s Inside
Why So Many Types of AI Agencies?
Actually, the terminology is not meaningless jargon.
Instead, it refers to the fragmented state of AI adoption and the “strategic battles” digital marketing agencies are fighting to define their role in an AI-driven economy.
Four main factors can explain the explosion of AI agency terminology:
🧩No universal definition: As we noted above, policymakers, developers, businesses, and technologists each frame AI differently.
NASA’s statement on their official website supports that. After defining AI as “computer systems that can perform complex tasks normally done by human-reasoning, decision making, creating, etc.,” the statement says that there is no single, simple definition of AI since “tools are capable of a wide range of tasks and outputs.”
And gives that graphic to expand the explanation:
Meanwhile, Google defines generative AI as follows:
🧩Market positioning: Agencies adopt labels to signal expertise. For example, “AI creative agency” appeals to CMOs seeking innovation, while “AI automation agency” speaks to COOs focused on efficiency.
🧩Maturity levels of adoption:
- AI-powered suggests augmentation of humans with AI support.
- AI-first signals deep integration where AI is the operational core.
🧩Present-day technology: As AILab Agents states, AI advances into agentic systems (autonomous AI agents that manage workflows), new terms emerge to reflect those capabilities.
AI-First Service Agencies
An AI-first service agency is built on AI as its foundation.
As we stated in the corresponding blog post, an AI-first service agency uses AI tools to accelerate human work while designing workflows so that AI agents perform the majority of tasks autonomously, with humans supervising rather than performing.
According to BCG Reports titled “Unlocking the AI-First Organization,” AI-first is not about implementing AI to the tasks and achieving the same outcome:
Instead, it is about fundamentally redesigning entire processes around outcomes delivered by agentic AI and revolutionizing results beyond what was previously possible. For example, the hire-to-retire process will shift from a linear, digitally enhanced process to an outcome-driven solution, focusing human interaction where it is a differentiator and minimizing costs elsewhere.
How It Differs
- AI-first vs. AI-powered: AI-first replaces traditional workflows; AI-powered augments them.
- These agencies serve as proof points that AI can be more than a tool. It can be the operational model.
Why Agencies Use This Term
Today, digital marketing agencies are adopting the AI-first label because they want to communicate deep commitment.
They’re saying, “We don’t add AI to existing processes. Actually, we’ve built from the ground up with AI at the core.”
Take one of our member agencies, Propellic’s “about us” explanation, as an example:
AI Marketing Agencies
An AI marketing agency focuses specifically on customer engagement, campaign optimization, and analytics using AI.
In other words, their value lies in converting data into marketing performance.
How It Differs
- Focus is narrower than service or automation agencies.
- They promise ROI from campaigns rather than operational efficiency.
McKinsey estimates AI could generate $4.4 trillion annually in productivity gains, with marketing use cases like personalization, segmentation, and customer insights contributing significantly. When considering that, it is not surprising that a great number of marketers focus on building an AI marketing agency today.
Why Agencies Use This Term
This label attracts CMOs and growth marketers who care about measurable marketing outcomes, like click-through rates, conversions, and brand reach.
AI-Powered Agencies
An AI-powered agency emphasizes augmentation rather than replacement.
Here, humans remain central, but AI tools support them in decision-making, customer interactions, or workflow execution.
In some sources, we also see the usage of the term “AI-empowered agencies” instead of “AI-powered.”
Here is a quick definition from a paper titled “The AI-Empowered Agency: 6 Principles for a Transformed Future”
AI-empowered agencies’ processes are much more cost-efficient and effective than past models. And they render traditional ways of setting timelines obsolete. The traditional marketing agency workflow followed a linear path: strategy, ideation, creative development and focus groups, production, and then media. It can be a long process of one specialist team handing the project to the next. Overall, it can cost more and take longer than anticipated with little certainty of the end results for the brand.
How It Differs
- AI-first = automation-driven replacement.
- AI-powered = augmentation with human oversight.
Why Agencies Use This Term
This label reassures people who may be uncomfortable with AI replacing humans & their works. It creates a balanced approach. It’s best for industries like healthcare or hospitality, where human empathy remains essential.
AI Creative Agencies
According to PwC’s Middle East CEO Survey, 73% of CEOs believe generative AI will significantly reshape how their companies create, deliver, and capture value in the next 3 years. So, creative agencies are already using AI for automated video ads, personalized visual design, and AI-driven storyboarding.
That’s okay, but an AI creative agency is another story.
An AI creative agency focuses on applying generative AI for storytelling, design, and content (including static images and reels) creation. Their mission is to scale creativity and push boundaries in marketing campaign production.
How It Differs
- Distinct from automation agencies that focus on efficiency.
- Positions creativity and originality as the differentiator.
Why Agencies Use This Term
To appeal to brands seeking bold campaigns that would be impossible to scale with traditional creative teams alone.
AI Automation Agencies
The McKinsey Global Institute found that 60% of occupations have at least 30% of their activities that could be automated. Automation agencies help companies capture this value by applying AI to repetitive tasks at scale.
So, an AI automation agency specializes in workflow efficiency and process redesign. Unlike creative or marketing agencies, these firms focus on operational streamlining, everything from campaign reporting to CRM management.
How It Differs
- Core focus is back-office productivity.
- Appeals more to operations leaders than marketers.
Why Agencies Use This Term
The term signals operational expertise, appealing to COOs or CTOs tasked with efficiency gains and cost reduction.
The AI Agency Quadrant: A Framework for Understanding Differences
So far, we’ve explored that the terminology around AI agencies can feel overwhelming.
However, when we strip it down, most marketing agencies fall into clear patterns. One way to make sense of this is through what we call the AI Agency Quadrant.
It’s a framework that maps agencies across two dimensions:
Level of AI Integration
Augmentation: AI supports humans but doesn’t replace them.
Transformation: AI is the operational core, driving workflows independently.
Primary Value Focus
Creativity: Differentiation through design, storytelling, and campaign innovation.
Efficiency: Differentiation through automation, speed, and cost reduction.
By plotting agencies against these axes, we see four distinct types emerge.
Top Left: AI Creative Agencies (Creativity + Augmentation)
AI creative agencies use generative AI to scale creative output; from ad copy or social media caption to video production, while keeping human creative direction in the driver’s seat.
Example: Agencies producing TikTok campaigns with AI-generated video templates that adapt to trending sounds and hashtags.
These agencies appeal to marketers who want innovation at scale without losing creative oversight.
Top Right: AI-First Service Agencies (Creativity + Transformation)
AI-first agencies go further; like building entire service models around AI agents. Here, humans supervise, but AI does most of the work autonomously.
Example: Agencies using AI agents to make real-time underwriting decisions.
As a supporting fact, according to the BCG Report, AI models now operate autonomously for up to one hour per task, with capabilities doubling every seven months.
Bottom Left: AI-Powered Service Agencies (Efficiency + Augmentation)
AI-powered service agencies keep humans in control while using AI to augment decision-making and workflow execution.
According to the OECD, using technology like this could free up nearly one-third of time for higher-value tasks.
This model appeals to organizations that need efficiency but value the human touch, especially in industries like healthcare, education, and hospitality.
Bottom Right: AI Automation Agencies (Efficiency + Transformation)
AI automation agencies specialize in end-to-end workflow automation and operational efficiency. Their value lies in re-engineering processes to cut costs and increase speed.
Example: Agencies applying AI to automate CRM updates, reporting dashboards, or supply chain workflows.
Why Marketers Should Care About These Labels
Marketers may be tempted to dismiss the labels as semantics. But ignoring terminology is a mistake for three reasons:
🧠Labels Shape Perception
As we stated above, calling yourself an “AI-first agency” signals boldness and transformation.
“AI-powered” signals pragmatism and caution. Clients choose based on the signal.
🧠Labels Guide Investment
Agencies & marketers that emphasize “automation” often pitch cost savings, appealing to operations budgets. Creative-focused agencies target marketing budgets.
The terminology decides where the money flows.
🧠Labels Predict Strategy
If a competitor partners with an “AI-first agency,” it’s safe to assume they’re pursuing deep transformation. If they choose an “AI creative agency,” they’re betting on storytelling differentiation.