Many advertisers are turning to AI to help mitigate the tedious, time-consuming tasks that eat into time, performance, and profitability. Unfortunately, AI alone cannot alleviate them. 

To get the most value out of AI, it must: 

• Integrate into your workflows, systems, and strategies.
• Fully remove operational pinch points instead of just creating more copy-paste work for teams.
• Be advertising-context-specific, not built with generalized knowledge.
• Work with automation rules to amplify outputs at scale.

This is the vision we had in mind, both when we started building Muse AI in 2023 and now. We wanted to give advertisers a robust AI that could handle the nuanced tasks they face every day, across their execution workflow. 

By supporting you in all the key workflows across your advertising management and execution, Muse is a digital workforce: a collaborator that helps you perform critical multichannel advertising tasks by bridging the gap between data and action, much like human teams currently do. 

AI designed for autonomous action

With a sharp focus on saving time, enabling strategic thinking, and simplifying intricate workflows, Muse exemplifies the synergy between AI, automation, and human specialists. Many traditional AI tools still rely heavily on user prompts for every action, forcing teams into repetitive cycles of asking, tweaking, and re-entering commands. This "sneaky villain of AI" trades tedious button clicks for equally tedious typing, adding to your workload rather than reducing it. 

While conversational interfaces are useful for one-off requests, they’re hardly scaled solutions. If you have to ask AI the same prompts or questions every day (or week or month) for every account or campaign, and only get narrative responses that you must go activate manually, are you really saving time? 

Muse goes beyond simple Q&A interactions. It can script, replay, and act on insights without requiring your team to constantly input data or point it in the right direction. Muse eliminates efficiency roadblocks by embedding intelligence and automation directly into your workflows. 

The result? An AdOps trifecta: human expertise, AI precision, and automation at scale. 

Watch now: understanding AI and digital workforce in advertising

How we got here: developing AI for advertising operations

When we decided to integrate AI into Fluency, our goal was simple: build an AI that makes life easier for digital advertisers. But achieving that goal and all its nuances requires deliberate work. 

We needed to understand our users’ core pain points and determine how AI best fit into their workflows. Where could AI help the most? What do our users want to do less of in their role? What kinds of questions, tasks, or KPIs keep them up at night?

This is one of the reasons Muse has had multiple version evolutions: it’s grown more capable alongside our wider system. Here’s a quick overview of how far Muse has come that highlights our intentionality with Muse’s growth.

Version 1: Generative AI for ad content creation 

Like most advertising AI, it all began with writing ad copy and generating keyword recommendations. We used Fluency’s campaign and ad group infrastructure to ensure Muse wasn't just guessing: the outputs were relevant, compliant, and strategic.

Version 2: Easy-to-understand portfolio data insights

Finding insights in a maze of rows and columns is nearly impossible. Muse V2 was the first time you could interact directly with AI within Fluency’s interface to quickly extract insights and analyze real-time data when viewing it on screen. I called it, “What you see is what Muse can interpret.”

Version 3: Detailed, rapid account and campaign analysis

After launching Muse V2, we quickly learned that account-related questions generally require more than just one level of information. For example, exclusively using campaign-level details makes it hard to suggest negative keywords because there’s no context around what negatives do or do not exist and what searches are happening.

Muse’s V3 launch included the ability to curate a set of prompts that pre-fetch structured account data from top to bottom (account, budget, campaign, ad group, ad, keyword, negative keywords) along with performance data.

This is where Muse became a useful partner for ad strategists because you could get a full lens on performance all in one shot, not just surface-level answers.

Version 4: AI-delivered report narratives and analyses

In Muse V4, we added AI text-to-speech and text-to-video generation to our reporting capabilities, bringing client reports to life while saving teams hours every week (if not every day). 

It’s also the first time we started to showcase Muse as a full-fledged, autonomous AI agent that could deliver content directly to end advertisers. AI agents are the future for so many industries, especially one engulfed by manual and repetitive processes like digital advertising.

This teed us up to further explore how Muse could be a force multiplier for ad teams.  

Version 5: Retrieval Augmented Generation (RAG) for valuable domain-specific responses

Retrieval Augmented Generation (RAG) is a game-changer for Muse AI. You no longer have to load specific datasets to get answers: simply ask your question and Muse handles everything in the background. 

For every question you ask, anywhere within Fluency, Muse will select the appropriate data, find the right time frame, and then understand the account(s) you’re asking about. (Muse will think a little longer because it must interact with multiple data services to fetch the most relevant and timely data for detailed domain-specific responses.)

In short, Muse’s new RAG functionality allows you to ask questions about almost any of the data in the platform. This isn’t just neat; it’s time-saving magic.

Why system-specific AI agents are a must for scalable digital advertising operations

Every version of Muse AI has built on what’s come before. Now that you’ve glimpsed what’s possible, I want to explain why specialized AI agents like Muse—operating within closed ecosystems with integrated data access—are revolutionizing digital advertising operations in ways general AI simply cannot match.

Domain-optimized AI that’s purpose-built for digital advertising's unique challenges

From the very start, Muse was engineered to understand the unique challenges, goals, and workflows of digital advertising teams. Unlike general AI models, Muse has been meticulously curated with comprehensive domain-specific knowledge to execute complex advertising tasks with precision and relevance.

Why does this matter? Muse speaks your language and solves your company’s specific advertising problems. It won’t give you generic answers based on a conglomerate of sources like ChatGPT, Perplexity, or Claude. Instead, it provides insights informed by your actual advertising ecosystem.

Full-context learning: crafted from your advertising data for targeted strategies

Using a system-wide AI solution means you can calibrate Muse to understand your unique advertising playbooks, goals, and needs. This ensures all generated content—from ad copy to strategic recommendations—aligns perfectly with compliance standards and campaign objectives.

As Muse observes your workflows, decision patterns, and success metrics, it continuously refines its understanding of your advertising strategy over time. The result is an AI collaborator that evolves alongside your business and needs, delivering increasingly targeted insights based on your operational data.

Complete data integration: unified intelligence across a closed, multichannel data ecosystem

Because Muse lives within Fluency’s closed ecosystem, you can use it to comprehensively query any account, multichannel campaign, or data sets that live within your Fluency database using natural language—no technical expertise required.

This unified approach enables strategic capabilities that are, quite simply, impossible to achieve with traditional AdOps workflows. For example, Muse can provide intelligent cross-channel budget reallocation recommendations and performance optimizations that would be impossible with fragmented data sources, manual analysis workflows, or disconnected tools (even ChatGPT).

Direct system execution: end-to-end implementation beyond narrative recommendations

Rather than simply providing narrative recommendations about what to do, Muse AI can help you manage tasks end-to-end by configuring everything within Fluency for you. All you have to do is approve it and go. 

Here's one of my favorite examples. Pulling specials off a website typically means scanning a client’s website, copying everything into a spreadsheet, and then manually building special ads within each platform. 

With Muse, you can say, "Suggest specials for [account]." Muse will read site data, pull the data, and interactively build the ability to execute the specials within Fluency’s Broadcast tool—all without your team manually reviewing websites, calling clients, or typing anything other than the prompt into Muse.

System-wide scalability: amplifying AI through integrated automation

AI on its own is powerful. AI paired with automation is unstoppable—particularly for digital advertisers. Automation plays a crucial role in maximizing AI’s potential by delivering AI’s outputs at scale. For example, automation can run quality checks on every AI output, automatically triple-checking that everything AI generates is infinitely repeatable and error-free.

Fluency brings the best of AI and automation directly to your advertising business within one system. Running everything through Fluency enables you to scale your AI-powered advertising efforts without sacrificing quality or accuracy. 

Enterprise-grade compliance: keeping sensitive data in a closed, zero egress environment

Unlike generic AI tools that rely on public data, Muse is deeply integrated into Fluency’s closed environment. This guarantees that your data stays exactly where it belongs—securely within your organization’s ecosystem, private and protected. This is how Muse’s outputs can align perfectly with your workflows and strategy while safeguarding sensitive information.

With zero data egress, Muse adheres to enterprise-grade compliance standards to give you total control over your data. This fortified architecture maintains privacy for both you and your clients. 

Reimagining AdOps with an intelligent, AI-powered digital workforce

I want you to think of Muse as more than a tool. It’s a coworker who never sleeps, takes over all the tasks you don’t want to do, and can help you quickly problem-solve in real-time by always putting the most vital information right there in front of you. 

It’s also our Fluency philosophy of how advertising operations can be better. Every update we’ve made to Muse AI—from ad copy creation to the introduction of Retrieval Augmented Generation—is focused on making your work more efficient, more informed, and more creative.

Muse AI is where AdOps meets innovation. Are you ready to work differently? 

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