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The AI Playbook: A modern marketer's guide to agent orchestration
Using AI for just content creation? Boring. Orchestrating your own workforce of AI agents to do the repetitive tasks—or entire marketing workflows—for you? That's more like it.
It's time to stop treading water in the AI era, and start orchestrating your content and marketing at a whole new level.
Introduction
Here's a secret for ya: Only the best marketing organizations, digital teams, and business leaders will tap into the full potential of AI.
Going far beyond the realms of LLMs and basic content generation, agentic AI is empowering marketers to do (way) more with less. The tireless team member that eliminates repetitive tasks and frees us to focus on creative, high-value work that not only makes the difference to your customer journey, but to every marketer's experience and day-to-day too.
Buckle up, marketing and digital teams everywhere — here's the lowdown on how to make AI work for you in the best way possible.
What you'll learn:
- How to move beyond simple prompts and start orchestrating an entire AI workforce
- Practical ways AI can improve both your team's efficiency and your customer's journey
- The framework for building a scalable AI engine with the right governance and team skills
- Key questions to ask to accurately measure your organization's AI maturity
- A step-by-step guide to launch your strategy with a proven 30-60-90 day action plan
Understanding AI in marketing
While many of us initially feared that AI was about to steal our jobs, the reality is way more exciting.
AI isn't replacing marketers, it's amplifying our capabilities, performance, and results. By integrating AI into our workflows, experimentation programs, and general tech stacks, we're unlocking serious levels of efficiency and effectiveness.
And for this to really work, you've got to consider two sides of the equation:
- Your team: How you can work more efficiently and optimize performance
- Your customers: How they interact with your digital experiences and content
Sure, AI can make our lives a helluva lot easier, allowing us to get back to the work we signed up for in the first place — not the boring, admin-booming, repetitive tasks that fill our diaries all too often.
The better the input = the better the output
And don't you forget it
Practical applications of AI in marketing
AI can — and we in our minds, absolutely should — be seen as members of your team. In fact, team members with a difference. These ones don't care about doing the mindless, repetitive, boring, hit-your-head-against-the-desk kind of tasks; AI is actually a master at that type of thing.
But there's more to this robotic teammate, and it all rides on your organization's AI maturity.
A few small steps to apply AI in a meaningful way = one giant leap for your MX and CX.
3 simple ways AI helps the marketer experience
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Use generative AI
Create basic content (eg. text, images, music) using standard AI prompts and open source LLM (large language model).
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Automate tasks with AI agents
Expand the functions of AI beyond just "create" and into other actions such as recommendations (eg. actions to take) and analysis (eg. insights).
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Create brand-specific content at scale
Increase the quality of output by giving AI more specific content (eg. your brand data, industry benchmarking, etc.)
3 simple ways AI helps the digital team experience
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Test variations
Generate additional headlines for every experiment to improve outcomes and deliver more personalized experiences for your customers—without slowing down your team.
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Strengthen SEO foundations
Use AI to scale keyword research, optimize metadata, and surface content opportunities. Fun fact: You can *actually* save 10+ hours a week with AI here.
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Performance tracking
Quickly analyze tests, content, and campaign performance—filterable by region, stakeholder, or goal—so you can focus on what's working and iterate (way) faster.
3 simple ways AI helps the customer experience
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Optimize for AI-powered search
Ensure your content is structured, relevant, and optimized for AI-generated search results, so customers find you fast (and in the way they interact in this AI era).
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Adapt websites to real behavior
Use AI to help define audiences with existing data, tailoring your content and site layout based on how customers engage today—by device, location, search behavior (eg. "Here is an audience of high-spending customers with low engagement").
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Personalized content at scale
Allow AI to take user-level attributes into account (in real-time) and make decisions to personalize individual experiences, increasing engagement and UX without the manual lift.
Yeah, that's right — we are going *way* beyond "write a blog". Use AI (including specialized agents) to analyze data, complete tasks while you're sleeping, and create hyper-personalized output.
AI agents: Everything you need to know
AI agents and specialized AI tools use context and instructions provided by you, the user, to perform a whole range of tasks — no humans necessary. The whole concept of agentic AI is changing the way we use AI and the way we work... for the better.
By incorporating AI agents into your marketing and digital strategies, you'll see:
- Increased efficiency
- More productivity
- Enhanced creativity
- Data-driven insights
How? Because AI agents take on the (painfully) mundane tasks that you don't want to, offer new ideas and insights that align with your brand guidelines, and deliver quick data analysis whether it's campaign results or other performance metrics you want to dive into. Meanwhile, you won't break a sweat.
Now, we know what you're asking: how do you get your hands on them? Well, for one, AI agents are manifested within Optimizely Opal, the agent orchestration platform for marketers. And even better? They integrate with all the tools in your current martech stack too.
Talk about unleashing your full marketing potential, hey.
Optimizely Opal: Meet your agentic workforce for marketing
Given that generative and agentic AI have totally revolutionized the marketing and digital realm, and that realm is kinda our thing, it felt natural — no, essential — that we not only talked the talk, but walked the walk.
We use it
We test it
We build it
So YOU can build it
That's right, we are constantly building highly-specialized agents so our customers can benefit. So, on that note: say hello to Optimizely Opal — here to improve the marketing and digital team experience, and ultimately your customers'.
Embedded across our entire suite of products (also known as Optimizely One) and easily-integrated with the marketing tools you already use, Opal is at your service. Far more than just an AI assistant, it’s an extension of your team that automates tasks and provides proactive insights.
With a mix of out-of-the-box agents and the ability to—very easily—create your own (even if you're not technical), Opal covers all the use cases we mentioned above... and more.
Here are some of Opal's key use cases:
- Speed up content creation and ideation: Spark new ideas and craft compelling content faster than ever. Opal helps you create complete campaigns: including ideating, crafting comprehensive briefs, generating text, and even creating images in various formats and sizes with smart cropping. Plus, AI tagging keeps your assets super organized.
- Deliver personalized experiences: Make the most of Opal to give you ideas for personalizing live webpages so you can easily maximize impact. Put its recommendations to the test, with on-brand, generated content in seconds.
- Boost experimentation velocity: Receive smart, data-backed recommendations to ideate on your next experiment, ensure your test plan is in tip top shape, develop variations (without a developer!), and summarize your results to apply learnings.
- Uncover data insights and trends: Dive deeper (and quicker) into your performance data by getting Opal to analyze complex information, spot emerging trends, and make smarter, data-driven decisions that propel your marketing forward.
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... and the results speak for themselves
In our 2025 Optimizely Opal AI Benchmark Report, we found that teams using Opal are seeing truly transformative results.
Highlights for marketing teams:
- +82% increase in content output
- +75% reduction in time to complete tasks
- +56% more campaigns delivered
Highlights for experimentation teams:
- +150% more variations created per test
- +50% increase in experiment velocity
- +126% more winning experiments
"We're incredibly excited about Optimizely's vision for Opal and the future of AI in content marketing and campaign automation. The potential to streamline everything from brief creation to content production, optimization and repurposing and even translation is game-changing.” John Habib, Director, Content Strategy @ Diligent
What makes Optimizely Opal truly unique?
- Built especially for marketing teams: Generic AI and output? Couldn't be us
- Pre-built agents for top marketing use cases: Agents that know what real marketing work is
- No need for developers: Low, no-code agent creation and agent workflows
- Ready-to-use, intelligent tools: Hundreds of pre-built, highly-sophisticated tools
- Connects seamlessly across your current tech stack: No rip-and-replace necessary
AI governance: How to build a scalable agentic marketing engine
Adopting AI is one thing, but making it scale—while staying on-brand, compliant, and all the rest—is another.
Moving from scattered AI experiments to a fully integrated, scalable AI engine requires a deliberate operating model. It’s not just about buying tools; it’s about building a foundation of people, processes, and governance to support them. Here’s how to build an agentic operating model that scales.
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Build a foundation of culture and trust
For AI to scale, your teams need to trust its outputs and understand its purpose. This is where a sturdy change management process should step in and take the reins. Here are a few pointers:
Be transparent: Share results from early pilots—both wins and losses—to build confidence.
Include everyone along the way: Bring creatives, strategists, and analysts into the process from the start to ensure AI is seen as a collaborator, not a competitor.
Champion augmentation, not replacement: Make it clear that the goal is to augment your team's creativity and strategic capacity... not replace it. -
Invest in skills and define new roles
Scaling AI requires more than just prompt-writing; it demands new fluencies and roles.
Upskill your teams: Treat AI fluency as a core competency and invest in training so everyone knows how to work with AI effectively.
Create hybrid roles: Establish positions like 'AI Content Strategist' or 'Prompt Lead' to bridge the gap between marketing expertise and technical know-how. - Standardize tools and centralize workflows
Inconsistent tools and workflows = brand drift and a lot of duplicated work. Who wants that?
Consolidate your toolset: Create a structured evaluation process to assess AI tools for reliability, integration, and scalability, consolidating where it makes sense (and where it doesn't).
Create a shared playbook for your team: Develop centralized guidelines, approved tools, and repeatable workflows that provide brand consistency while still allowing your creative muscles to flex. -
Establish clear governance and compliance
Without clear ownership, you risk... well, risk. And risk? Risk slows e v e r y t h i n g down.
Define accountability: Assign clear ownership for AI outputs, from factual accuracy to brand review and compliance checks.
Embed checks into the workflow: Build fact-validation, plagiarism detection, and bias reviews directly into the content creation process to build confidence and speed. -
Treat your AI program as a living system
Prompts, models, and brand guidelines will all evolve over time. So, your AI operating model is going to have to, too.
Continuously review and refine: Regularly review prompts, workflows, and style guides to ensure they align with your current brand strategy and the latest AI capabilities.
Measure what matters: Don't just track speed and volume; brand consistency, content quality, and team confidence in AI outputs count too!
Benchmark your organization's AI maturity
AI maturity looks different for every marketing organization.
Some are just getting started with generative AI, while others are beginning to apply it more systematically across campaigns, content, and operations.
Understanding where your organization sits today helps you identify what’s working, where gaps exist, and what the next step should be. An AI maturity lens gives you a practical way to assess your current capabilities and build toward more advanced, scalable use cases over time.
Measuring your AI maturity: Questions to ask
Your 30-60-90 day action plan for AI implementation
Meaningful AI adoption doesn’t happen overnight. For most organizations, it’s an evolution—from experimentation, to standardization, to orchestration.
A phased approach helps teams build confidence, align stakeholders, and unlock value at each stage without overwhelming the organization.
0-30 days
Assess and align
In the early stage, focus on understanding your current state and creating clarity.
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Audit existing AI usage
Identify where AI is already being used, what tools are involved, and which workflows experience the most friction. -
Assess data readiness
Evaluate whether your data is accessible, reliable, and suitable for more advanced AI use cases. -
Define success criteria
Set clear goals for AI adoption—whether that’s improving speed, consistency, personalization, or operational efficiency. -
Establish ownership and governance
Align on who owns AI strategy, enablement, and guardrails across the organization.
31-60 days
Standardize and assemble
With a clear baseline, shift focus to consistency and capability-building.
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Create shared best practices
Document how and where AI should be used, including guidance on prompts, instructions, and brand standards. -
Enable your teams
The next big part in your change management process is to invest in training and internal knowledge-sharing. Less reliance on trial and error, more confidence in the team—yes, please! -
Identify agent-ready use cases
Look for repeatable, time-consuming tasks—like content operations, experimentation setup, or campaign QA—that could benefit from more automation over time. -
Evaluate tools with a long-term lens
Prioritize solutions that integrate well, scale with your needs, and support more advanced workflows as maturity increases.
90 days and beyond
Orchestrate and optimize
At this stage, AI begins to move from assistance to ownership.
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Pilot agent-led workflows
Start small by allowing AI agents to manage defined parts of a workflow—such as research, drafting, optimization, or reporting—under human oversight. -
Connect workflows end-to-end
Where possible, link AI-driven tasks so outputs flow naturally from one step to the next, reducing manual handoffs. -
Continuously measure and refine
Monitor performance against your KPIs, capture learnings, and iterate on workflows to improve results over time. -
Expand into more complex use cases
As confidence grows, apply AI and agents to more specialized or technical areas, unlocking efficiency and freeing teams to focus on strategy and creativity.
AI is giving marketers their time—and their craft—back
The real breakthrough in AI marketing isn’t smarter machines. It’s smarter teams who know how to put AI to work.
AI isn’t here to replace creativity or strategy—it’s here to remove the friction that keeps marketers buried in busywork. When repetitive, operational tasks are handled by AI, marketers get back to what they do best: creating great experiences and driving real impact.
That’s where agentic AI comes in—and where Optimizely Opal leads.
Opal isn’t just more powerful AI. It’s better orchestration: agents that understand context, work across workflows, and improve over time—guided by humans, not micromanaged by them.
The result? Faster execution, more consistent quality, and more time for the work that actually matters.
☑ Less tasks on your to-do. More time for you to DO.
☑ Less stress on your to-do. More space for you to DO.
☑ Less fuss on your to-do. More fun for you to DO.