Wondering how to make the move from generative to agentic AI? Say goodbye to 'another AI assistant', and hello to an infinite workforce with the AI playbook.

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 (marketer experience and CX (customer experience).

3 simple ways AI helps the marketing and digital experience

  • Quality brand-specific content at scale

    Generate on-brand, data-driven content for multiple channels, audiences, and geos simultaneously from a single brief.

  • Maintain continuous compliance and quality

    Deploy AI agents to continuously scan and enforce brand voice, best practices, and regulatory compliance across all content.

  • Always have insights at your fingertips

    Instantly analyze campaign performance and surface key trends with a specialized agent.

3 simple ways AI helps the customer experience

  • More personalized content

    Easily scale the creation of personalized content to ensure every customer feels seen.

  • Easy-to-find insights that improve UX

    Proactively optimize the customer journey by having AI analyze user behavior in real-time to identify friction points.

  • 24/7 autonomous support

    Provide instant, consistent customer support around the clock by letting AI agents handle common inquiries autonomously.

3 advanced ways AI helps the marketing and digital team experience

  • Automate end-to-end campaign creation

    Execute entire multi-channel campaigns from a single high-level goal, with AI handling everything from brief to optimization.

  • Perfect predictive personalization

    Deliver hyper-personalized content by using AI to predict a user's future needs based on their current behavior.

  • Marketing to AI agents

    Adapt your strategy by optimizing product information and trust signals for the personal AI agents making purchasing decisions.

  • Proactive security and governance

    Deploy AI security agents to monitor for threats and audit other agents for compliance, ensuring a secure digital ecosystem.

3 advanced ways AI helps the customer experience

  • AI-powered concierge services

    Provide customers with a personal AI shopping agent to guide them through your products and complete purchases.

  • Dynamic, individualized customer journeys

    Create a unique, real-time journey for every user by having AI adapt the content and layout based on their behavior.

  • Seamless integration with the physical world

    Bridge the digital and physical gap with AI agents that can help customers with in-store navigation or real-time product diagnostics.

So yes, if you hadn't realized, we are going *way* beyond "write a blog". AI agents are doing things while you procrastinate, while you have your coffee break, and even while you sleep.

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:

  1. 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.
  2. 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.
  3. 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.
  4. 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.

  • 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!

If you're looking to scale AI in marketing and want to know more about the key governance frameworks to match your AI readiness, get the (completely free) AI Marketing Playbook.

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

The reality: The training gap is real — and it's slowing you down

The thing is, your answers to these questions might have highlighted an uncomfortable truth: most organizations charging ahead with AI adoption have quietly skipped the part where they actually train their people to use it.

The tools are live, the subscriptions are paid for, the all-hands slide deck says "we're now an AI-first team". But ask your average marketer how confident they feel using AI agents in their day-to-day work? Whole different story.

While 75% of companies are now adopting AI, only 35% of employees have received any AI training in the last year. Now, that's not a small gap, is it? And 55% of hiring managers say their organization lacks the training or resources to help employees use AI in the most effective way.

The result? Teams that are technically 'using AI' but nowhere near unlocking its full potential. Workflows that rely on one or two power users. Plus a lot of trial-and-error that nobody has the time for.

"AI adoption tends to swing like a pendulum — first it’s all experimentation, then it snaps back to control. The companies that actually make progress are the ones that learn how to operate in the middle.”   
Tara Corey, CMO @ Optimizely

Early on, it’s all experimentation — hackathons, everyone building agents, momentum through curiosity. Then comes the backlash: too many disconnected use cases, uneven quality, and no clear ownership. So organizations swing the other way, locking things down with governance and centralization.

But the goal isn’t either extreme... it’s the middle. That’s where real adoption happens: structured enablement, shared standards, and the freedom to build better, not just more.

The bigger the organization, the worse this tends to get. Enterprise AI rollouts often prioritize tooling and governance, which are (of course) both important, but leave the actual skills-building as an afterthought, a one-off Lunch & Learn, or a library of videos that nobody watches.

It's not a people problem, it's a program problem.

Ready to close the AI enablement gap?

Opal U | AI Marketing University is Optimizely's hands-on AI training series, designed for individuals working in marketing and digital that want to go from AI-curious to AI-completely-capable (fast). This isn't another passive webinar — we're talking real practice, real agents you take home, and real results.

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.

  • 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.

  • 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.

  • 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.

☑ 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.

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.