How Optimizely Opal saves time + drives results for teams like yours

Not long ago, artificial intelligence in marketing was largely a vision of the future—an exciting, but experimental, promise of what might be possible. Marketers dabbled in AI tools (realistically, mostly in silos) kinda unsure of what AI could really do.

Adoption was cautious. Impact was inconsistent. Integration was rare.

⏩ Okay, so now fast forward to mid-2025. What was once a novelty, is now an imperative. AI has moved from the fringes to the core of marketing operations, transforming how teams plan, create, deliver, and optimize across every channel. Capabilities that felt futuristic just 18 months ago are now essential components of the modern marketing stack.

According to McKinsey’s latest State of AI survey, 78% of organizations now use generative AI in at least one business function; a telling sign that the future of marketing has arrived, and it’s reshaping the landscape.

Today’s market has crystallized into three distinct tiers of AI capabilities:

• Basic AI tools: Narrow, single-purpose automations for specific tasks
• Mid-tier platforms: Broader, multi-capability solutions, often lacking seamless integration
• Integrated AI ecosystems: End-to-end platforms that unify the entire marketing lifecycle

Enter: Optimizely Opal

At Optimizely, our position in this evolving ecosystem is pretty unique (no big deal).

While many competitors have treated AI as either a peripheral feature or a standalone platform, Optimizely Opal has been architected as a native capability interwoven throughout our existing product suite. The result is an intelligent system that goes beyond simple content generation or data analysis. Optimizely Opal provides contextual intelligence that comprehensively understands an organization's brand, historical performance, and strategic objectives.

To fully understand the value of where we are now, we're going to take a look at how we got there. But first, how about a TL;DR section of the key stats we'll cover (for any of you that are short on time)?

TL;DR: Your Optimizely Opal highlights 📈

The state of AI

1. Adoption of Optimizely Opal is geographically broad, with the US (42.9%), UK (16%), and AUS (7.6%) leading the charge.

2. Industry adoption is broad as well, spanning Retail (18.1%), Business Services (9.1%), Hospitality & Travel (4.9%), and extending into traditionally cautious sectors like Financial Services (9.2%), Healthcare (2.9%), Education (3.3%), and Transportation & Logistics (2.2%).

3. Significant adoption among all levels of digital maturity—high (46%), medium (39%), low (15%)—challenges the assumption that advanced AI tools only benefit large, mature organizations.

4. Adoption is distributed across several key user profiles: Senior Leadership/Executives, Product Marketing Team, Customer Success, Content Marketing, Digital Marketing, Field Marketing, Data Analysts, Experimentation Managers, Brand & Creative Teams, Events Teams.

5. Power users of Optimizely Opal spread use across a variety of features instead of focusing heavily on limited use cases.

The benefits of AI

1. As a Campaign Manager Optimizely Opal has:
   
   👉 Created 20.8% of tasks and 24.1% of campaigns for its users
   👉 Contributed to a 74% and 82% increase in volume of tasks and campaigns created
   👉 Saved 10%, 75%, and 68% more time in campaigns, tasks, and requests compared to last year
2. As an Experiment Advisor Optimizely Opal has:
   
   👉 Created 16.2% of experiments
   👉 Summarized 3% of experiments
   👉 Generated 11% of the variations used in tests
   👉 Seen a 50% increase in experimentation volume compared to last year
3. If the improvements across all Optimizely Opal use cases are aggregated the resulting increase in output for a marketing team is over 50%.
4. Across all of the usage detailed in this report Optimizely has done over 32,000 hours of work—at an average blended team rate of $100 Optimizely has delivered over $3.2M in estimated time savings alone
5. Between generating test ideas, creating variations, or summarizing results, Optimizely Opal has contributed to 3,000+ tests and influenced over $50M of revenue

Building a culture of AI

1. Successful AI adoption requires strong governance, cultural alignment, and clear workflows—not just technology implementation.
2. Clean, current, and well-structured data is essential for generating accurate and reliable AI outputs.
3. Brand safety depends on defined content parameters, human oversight, and legal/ethical compliance in AI use.
4. Marketers must develop AI literacy, especially in prompt design, to fully unlock productivity and creativity gains.
5. Embedding AI into daily marketing tools and workflows drives adoption by removing friction and context-switching.
6. AI output quality improves through iterative refinement, treating prompts as a dialogue rather than a one-time request.

7. The future of marketing AI is integrated, agent-driven, and optimized for real-time, personalized experiences.

Okay, so with all those stats, you might be wondering: how did we all get to this point? What has the journey been for marketers? Let's dive in.

The evolution of marketing

Marketing has always been about understanding customer needs and demonstrating how products and services meet those needs. At its core, marketing is about building demand and delivering value. While this fundamental purpose remains unchanged, the methods and expectations surrounding marketing have evolved dramatically.

Today’s marketers operate in a landscape shaped by rapid technological innovation, shifting consumer behaviors, and an explosion of digital channels. The result? A role that is more dynamic and more demanding than ever before.

The expanding scope of marketing

Modern marketing is no longer confined to crafting compelling messages or managing campaigns. It’s about creating seamless, personalized experiences across every touchpoint. Marketers must harness data and insights to anticipate customer needs, stay ahead of trends, and deliver content that resonates, at scale, on every channel.

Gartner's 2024 Senior Executive Views of CMO Leadership survey states that CMOs remit has grown from driving 5 different initiatives on average, to 8 initiatives.

To succeed, marketers are expected to be:

• Data analysts who interpret complex insights
• Creative storytellers who craft compelling narratives
• Project managers who coordinate across teams and timelines
• Technologists who navigate Martech and Adtech ecosystems
• Strategists who align marketing with business growth

So, it’s no surprise that 66% of CMOs report struggling to exceed mounting executive expectations.

The challenge: Doing more with less

Despite expanding responsibilities, marketing budgets have been stagnant at 7.7% of total revenue over the past year and are not expected to go back to pre-COVID levels of 10-12% anytime soon (CMO Survey, Gartner, 2024).

To add to that, marketers are asked to work within fragmented systems. A typical day might involve switching between spreadsheets, email threads, campaign tools, content management systems, and file-sharing platforms, just to get a single campaign out the door. With the advent of AI, and increased pressure to adopt it, this has also led to an 'AI fragmentation' problem—more disparate tooling that needs to be managed.

They must:

• Manage multiple stakeholders and approval workflows

• Personalize campaigns for diverse audiences

• Increase campaign velocity without sacrificing quality

• Cut through digital noise to capture attention

• Continuously report on performance and ROI

All of this takes place in an environment where marketing’s value is frequently scrutinized, with just 34% of executives aligned with CMOs on marketing’s role in supporting growth (CMO Survey, Gartner, 2024).

The cost of complexity

This complexity comes at a cost. Marketers are stretched thin, tools are disconnected, creativity is stifled by operational burdens, and innovation is often sidelined by the need to “just get things done.” The pressure to perform faster, better, and more efficiently can lead to burnout and missed opportunities.

A better way forward with Optimizely Opal

At Optimizely, we believe it doesn’t have to be this way.

Times are changing and companies need more than just tools—they need intelligent, integrated systems that evolve with them. That’s where the infinite workforce powered by Optimizely Opal comes in.

Optimizely Opal is designed to simplify the marketer’s world. It brings together the tools, workflows, and insights marketers need into a single, intuitive platform. This enables them to focus on what they do best: creating value.

With Optimizely Opal, marketers can:

• Streamline campaign planning and execution with centralized intelligence

• Collaborate seamlessly across teams and stakeholders

• Deliver personalized experiences at unlimited scale

• Accelerate time-to-market with intelligent automation

• Measure and optimize performance with real-time insights

Optimizely Opal isn’t just another AI tool: it’s an extension of your workforce. By reducing complexity and increasing efficiency, it empowers marketers to reclaim their time, amplify their creativity, and drive measurable business outcomes.

Our early results show that our customers agree.

Since launching in Q2 2025, Optimizely Opal has seen rapid adoption, outpacing both early expectations and beta testing benchmarks. This surge reflects a strong market appetite for effective tools that can power experimentation, content optimization, and strategic decision-making at scale.

This report provides a first look at the results: who’s using Optimizely Opal, how they’re using it, the impact it’s making. It also shares insights on how to position your organization as a leader in AI adoption, and what’s ahead in the evolving AI landscape.

The whos, whats, whens, wheres and hows

Firmographic data: Who’s using the infinite workforce?

Together, companies using Optimizely Opal generate over $100 billion in annual revenue—from household names like DoorDash, Nestlé, and Shell to innovative players across every industry. Its broad adoption across such a diverse customer base tells a clear story: AI is no longer a niche tool reserved for a select few.

Organizations of all sizes and sectors are using it to rethink how they plan, create, and deliver marketing. Optimizely Opal’s capabilities aren’t confined to specific roles, verticals, or enterprise tiers—they’re being embraced across the board, signaling a fundamental shift in how modern companies approach digital marketing.

Geographic distribution: Where is Optimizely Opal being used?

The infinite workforce has now been adopted in over 50 countries worldwide, with especially strong traction in the United States (42.9%), the United Kingdom (16%), and Australia (7.6%). The remaining 33% spans a diverse tapestry of users across Europe, Asia, and emerging markets—underscoring the global resonance and universal value of AI-powered marketing solutions.

Industry uptake: What are the main industries adopting AI?

The cross-sector uptake of Optimizely Opal highlights AI’s impact across a wide range of industries:

• Retail leads with 18.1% adoption
• Software follows at 12.4%
• Financial Services account for 9.2%
• Business Services hold 9.1%
• Hospitality, Travel & Recreation represent 4.9%

Notably, traditionally cautious sectors such as Financial Services (above), Healthcare & Medical (2.9%), Education (3.3%), and Transportation & Logistics (2.2%) are beginning to integrate AI-driven marketing technologies. This shows an interesting shift in how these industries are investing in and leveraging marketing innovation.

Digital maturity: Does it depend on company size? (Hint: Nope)

Adoption spans a broad spectrum of organizational sizes and digital sophistication. Mid-market companies lead at 51.6%, with enterprises close behind at 41.1%, and the remainder spread across M&D and strategic business units. This balanced distribution challenges the assumption that advanced AI tools primarily benefit only large enterprises, demonstrating that Optimizely Opal delivers meaningful value regardless of company scale.

Equally revealing is the digital maturity profile: nearly 49% of adopters are highly digitally mature, but a substantial 38% fall into the medium maturity category, and 13.4% represent low maturity organizations. This illustrates Optimizely Opal’s ability to bridge the AI implementation gap, making sophisticated AI capabilities accessible and practical even for organizations earlier in their digital transformation journeys.

Together, these patterns confirm that Optimizely Opal is democratizing access to cutting-edge AI marketing tools, empowering organizations across industries, geographies, and maturity levels to multiply workforce impact and accelerate growth in an increasingly competitive digital landscape.

What roles and teams are using Optimizely Opal?

Understanding who is using Optimizely Opal–not just which companies, but which roles and teams–provides crucial context for its impact on marketing organizations. Our data reveals an adoption pattern that defies traditional technology rollout models, with usage spreading horizontally across roles rather than remaining confined within specialized teams.

• Senior Leadership/Executives
• Product Marketing Team
• Customer Success
• Content Marketing
• Digital Marketing
• Field Marketing
• Data Analysts
• Experimentation Managers
• Brand & Creative Teams
• Events Teams

This distribution represents a profound shift from early AI adoption patterns, where technical specialists and data scientists served as gatekeepers between AI capabilities and marketing teams. With Optimizely Opal, we're seeing direct engagement from the practitioners who apply AI outputs to everyday marketing challenges. Executive-level adoption also signals the strategic priority organizations are placing on AI capabilities.

How are all these people using Optimizely Opal?

It’s not just about who is using Optimizely Opal—it’s about how they’re using it. The following frequency data provides a clear picture of which features are driving adoption and where organizations are finding the greatest impact.

• 19,700+ messages sent to Optimizely Opal chat by 160+ monthly active users

• 1,800+ CMP tasks created

• 830+ CMP campaigns brought to life

• 670+ articles crafted

• 1,300+ documents uploaded

• 3,700+ test ideas generated

• 5,400+ experiment summaries generated

• 740+ experiment descriptions generated

• 2,800+ test variations summarized

• 540+ variations and 770+ variables brainstormed

This data reveals an important insight: Optimizely Opal is being used consistently rather than sporadically, indicating it has integrated into daily workflows rather than serving occasional niche use cases.

Power users: Who is getting the most out of the infinite workforce (and how)?

Not all users are equal either. Some users are finding significantly more use cases, and generating significantly more value, than others. To be in the top 10% of monthly Optimizely Opal users, users need to:

• Send 50+ messages to Optimizely Opal

• Create 17+ tasks

• Create 9+ campaigns

• Create 9+ articles

• Create 35+ test variable variations

A few other trends emerged within this cohort of power users:

• ~92% of users who created campaigns used Optimizely Opal again within the same week
• The most popular Optimizely Opal features for EXP are summarizing experiment results and getting test ideas
• The most popular Optimizely Opal features for CMP are accessing text generation and generating images

The benefit of AI: How companies are using the infinite workforce

As always, we've got to think "what's really in this for me?", so let's cover the benefits of using AI—particularly an infinite workforce like Optimizely Opal.

The use cases of Optimizely Opal are, like the larger Optimizely suite, as varied as there are marketers or marketing initiatives. As shown above, it adapts to different user personas—streamlining complex workflows and accelerating execution across content, campaigns, and experimentation. Among the many use cases for AI, several stand out for the volume of adoption and magnitude of their impact.

Optimizely Opal as a Campaign Manager

Marketers’ value comes from the revenue-generating, value-added work that they contribute to a company; things like strategic campaign planning and brand storytelling, advanced segmentation and personalization strategy, new market or product growth initiatives, and not the administrative work that was previously necessary to set up more meaningful work. Reducing the time spent on operational tasks allows marketers to re-allocate that saved time to more revenue-generating tasks.

A leading education travel company, for instance, used Optimizely Opal to deploy 100% more revenue generating campaigns than their pre-AI volume.

Campaign management: Optimizely Opal benchmarks*

• 20.8% of CMP tasks created with Optimizely Opal
• 24.1% of CMP campaigns created with Optimizely Opal
• +73.9% volume of tasks
• +81.7% campaigns created
• -10.4% time to complete for CMP campaigns
• -74.7% time to complete for CMP tasks
• -67.7% time to complete for CMP requests

* Calculated based on data from February to June 2025, compared to the same period in 2024, unless otherwise noted.

Optimizely Opal as an Industry Marketer

Content that has been personalized for industry performs better. Optimizely’s own research shows that personalized content sees a 41% better result when used for optimization compared to generic content. But finding all the relevant insights to sensitive content to industry is a bear. No marketer is an expert at every industry. Optimizely Opal, with its ability to draw on vast data sets, internal materials, and brand guidelines, is an expert in every industry.

One early adopter of Optimizely used Optimizely Opal’s industry targeting capabilities to tailor a single piece of content for four distinct industries—it saved them nearly 100 hours of manual effort.

Optimizely Opal as an Experiment Advisor

Anyone with an experimentation program knows that its value is the product of two simple inputs:

1. How many experiments are run
2. How good the experiments are

Optimizely Opal contributes to both. Hypothesis creation, variation generation, test setup, and summarization —all speeding up experimentation velocity. Since it’s trained on Optimizely’s own vast knowledge on experimentation best practices, the quality of hypothesis and variation improves, resulting in your experiments seeing both higher quantity and higher quantity.

One Optimizely customer (a leading retailer using Optimizely Opal for experimentation), for instance, got a 72.5% increase in test velocity after the implementation.

Experimentation advisor: Optimizely Opal benchmarks*

• 16.2% of experiments created using ideas from Optimizely Opal
• 2.7% of concluded experiments summarized using Optimizely Opal
• 10.8% of variations brainstormed become actual variations
• +50.2% more experiments created

* Calculated based on data from February to June 2025, compared to the same period in 2024, unless otherwise noted.

Optimizely Opal as a Marketing Researcher

A content strategist at a leading cloud software company is building a content inventory agent with Optimizely Opal, allowing teams to instantly surface everything written about a specific topic or by a particular author. “This whole process will be much faster, and a big help for our team,” they said.

One of the biggest challenges in creating marketing materials is distilling vast amounts of information into clear, credible content. Optimizely Opal helps streamline this process—not only by aggregating relevant data like any AI, but also by ensuring the information is both brand-compliant and contextually on-point.

Multiple customers, including CAB members, have utilized the marketing researcher agent to significantly simplify their workflows. Instead of spending hours manually reviewing and summarizing vast amounts of information, they relied on Opal to quickly aggregate and refine insights into brand-compliant, contextually accurate content—making the entire process faster and more efficient.

Optimizely Opal as a Translator and Transcriber

No task is more manual or more wasteful of marketers’ talents as creators and strategists than translations and transcribers. At best, companies have to pay for third party services to perform this necessary but rote work. With Optimizely Opal, though, translations and transcriptions are nearly instantaneous, highly accurate, and have multilingual reach.

A large multinational Optimizely customer operates across 144 countries. Instead of manually translating promotional content into dozens of languages, they now leverage Optimizely Opal’s AI translation capabilities—saving an estimated 1,000+ hours on a single piece of content.

Translations and transcribers: Optimizely Opal benchmarks

• 180+ translations completed

Putting it all together: The whole is greater than the sum

These AI use cases don’t operate in silos either—they stack such that the whole effect of Optimizely Opal on marketing operations is greater than the sum of the individual use cases. Customers with significant adoption of Optimizely Opal across content production, experimentation, and content delivery are getting nearly 50% more output from their teams.

• Optimizely Opal has logged over 50K total events ranging from chats, to task, campaign, or variation generation, to results summarized or translations performed

• Optimizely Opal has helped bring 830+ campaigns to life—from large scale events like Opticon, in itself 900+ tasks—to smartly executed, time bound individual campaigns e.g. ABM campaigns and paid media initiatives

• Across all of the usage detailed in this report Optimizely has done over 32,000 hours of work—at an average blended team rate of $100, Optimizely has delivered over $3.2M in estimated time savings alone

• Between generating test ideas, creating variations, or summarizing results, Optimizely Opal has contributed to 3,000+ tests and influenced over $50M of revenue

How to build a culture of AI in your organization

1. Ensure governance and prioritization

   
   Successfully deploying an infinite workforce powered by AI goes beyond mere technological adoption—it requires building new organizational capabilities, rigorous governance frameworks, and cultural practices. At Optimizely, we see AI as a strategic partner that interacts deeply with our customers' data and content, making robust policies critical for maintaining brand consistency, accuracy, and compliance.

2. Begin with data hygiene

   
   The effectiveness of any AI agent, like Optimizely Opal, hinges entirely on the quality of data it accesses. Clean, current, and well-structured content serves as the foundation for all AI capabilities. Before deploying at scale, we recommend auditing your content repositories and product databases to eliminate inaccuracies and outdated information. Providing a single source of truth—such as an approved dataset or integrated live data—ensures your AI outputs remain accurate and valuable.

3. Establish brand safety and quality controls

   
   Think of your AI as a new team member needing clear guidance. Optimizely Opal allows custom fine-tuning with your specific brand voice, terminology, and product guidelines. Explicitly define acceptable content parameters to avoid inappropriate or off-brand outputs. Implementing these guardrails early ensures your marketing communications remain consistent, appropriate, and aligned with your brand ethos.

4. Maintain human oversight

   
   AI is powerful but not infallible. Keep humans in the loop with approval workflows—AI-generated drafts reviewed by experienced marketers before publication. Regular auditing maintains high content quality standards.

5. Legal and ethical considerations

   
   Collaborate closely with your legal team to establish clear guidelines around AI-generated content usage, intellectual property rights, and data privacy. Monitoring evolving AI regulations will protect your brand from unintended compliance risks. Transparency about AI-generated content builds trust and ensures ethical standards are met.

6. Empowering your marketing team with AI

   
   AI literacy is rapidly becoming indispensable, yet 62% of marketers lack formal AI training. Address this competitive gap through practical training on prompt engineering and AI tool utilization. Develop 'AI champions' within your organization, align KPIs with AI-driven productivity, and position leadership to frame AI as creativity enhancement rather than replacement.

Best practices for adopting AI

Adopting AI in marketing isn’t just a tech integration—it’s a skill and process integration for your team. As AI agents like Optimizely Opal become part of daily workflows, strategic implementation becomes essential for maximizing organizational impact. The following are some best practices compiled after reflecting on our own experiences:

1) Prompt engineering: Be descriptive, provide context, and point to data

Getting quality output from AI begins with how you ask. Crafting effective prompts is now a must-have marketing skill. A good prompt to an AI agent is clear, detailed, and contextual. In practice, this means:

• Be specific about the task and format: Instead of a vague prompt like “Write a product description,” you want to give more concrete guidance on length, key angle, and tone—something like “Write a 100-word description of [Product Name] highlighting its eco-friendly features, in a playful tone.”

• Provide business context: Always set the scene for the AI by mentioning the target audience, the channel, and the goal so it can tailor the content appropriately. For example: “Draft a LinkedIn post (3-4 sentences) to announce our new analytics feature to a tech-savvy audience of product managers, emphasizing how it saves time.”

• Incorporate relevant data or references: One powerful technique that reduces the risk of hallucinations or generic output is to ground the AI in facts by including data or pointing it to internal content. Optimizely’s Opal allows using special commands like @research to fetch data from integrated database–you can achieve a similar effect by feeding the AI snippets of information. For instance: “Using the following data–{Q1 sales were 20% above target, highest in the industry}–write a one-paragraph update for the team.”

• Iterate and refine: Treat AI interaction as a dialogue, not a one-shot deal. If the first output isn’t perfect, clarify your instructions or tweak the prompt and try again to steer it in the right direction. For example, if an AI-generated social post is factually correct but a bit bland, you can prompt: “Great, now make it more engaging and add an emoji or two. Also include a call-to-action to read our blog.”

2) Workflow integration: Embed AI throughout your stack

To maximize AI’s impact, it should be seamlessly integrated into your marketing technology stack and daily workflows. An AI assistant won’t be used (or useful) if it’s siloed on the side; it needs to be where the work happens.

3) Integrate AI into your content and campaign platforms

Our approach with Optimizely Opal has been to embed the AI directly within the CMS and CMP interfaces. For example, when a marketer is building a webpage in the CMS, Optimizely Opal’s chat and suggestions pane is right there, offering to generate content or pull in relevant assets. This in-context integration is powerful: it eliminates the friction of switching to another tool to use AI, and it allows the AI to automatically take into account the page context (URL, existing content, metadata) when giving suggestions. The key idea is AI should be a natural part of the content creation flow, not an afterthought.

Similarly, if you’re running A/B tests or personalization campaigns via an experimentation platform, let AI act as a co-pilot. Optimizely Opal users have access to just that—features such as a one-click AI Results Summarizer for experiments. This not only saves analysts time, it encourages more people on the team to consume results (because a plain-English summary is easier to digest than a stats dashboard).

What’s next for AI in marketing?

The marketing industry in 2025 is experiencing nothing short of an AI revolution. Beyond the individual use cases and best practices, it’s important to understand the big-picture trends shaping AI adoption. Enterprises are heavily investing in AI, marketers are shifting from isolated tools to orchestrating AI across workflows, and entirely new market structures (like agent marketplaces) are beginning to emerge. Let’s look at the data and the trajectory for the short, mid, and long term.

General market trends

As we look toward the future, the marketing landscape is being reshaped by a surge in AI adoption. Marketing teams are transitioning from isolated AI tools to comprehensive, integrated platforms, enabling workflow orchestration and enhanced interoperability.

Interoperability standards like Google's A2A, Anthropic's MCP, and Microsoft's NLWeb indicate a significant shift towards a web optimized for AI agents. Optimizely Opal embodies this trend, integrating seamlessly across our product ecosystem, empowering marketers to streamline operations and amplify strategic efforts.

Short-term (2025): AI across marketing operations

Currently, companies are operationalizing AI across various marketing functions. Marketers leverage AI for efficiency gains, content optimization, and workflow automation, freeing teams to focus on creative and strategic tasks. Key challenges remain in data quality and team adoption.

Mid-term (2025–2026): Multi-agent orchestration

The next two years will see AI tools becoming interconnected, creating workflows with multiple specialized agents collaborating seamlessly. Agent marketplaces will emerge, offering tailored solutions and significantly accelerating AI adoption. Organizations need strong governance to manage complexities and ensure seamless integration.

Long-term (2027 and beyond): Generative experience optimization

Further into the future, marketing will become highly personalized and automated at every touchpoint. AI agents will dynamically adjust user experiences in real-time across digital platforms. The concept of 'marketing to AI'—where marketing strategies target AI agents rather than human consumers directly—may become prevalent. This shift requires marketers to rethink strategies fundamentally, ensuring their messaging resonates with both human and AI-driven decision-makers.

What could you do with an infinite workforce?

We stand at the precipice of marketing’s most profound transformation since the marketing teams went digital. Once defined by manual processes and siloed systems, marketing teams struggled with slow insights, shallow personalization, and fragmented execution.

The emergence of agentic AI—exemplified by platforms like Optimizely Opal—is reshaping the marketing landscape. AI agents now handle complexity at scale: generating content, optimizing experiences, personalizing interactions, and uncovering insights with speed and precision. By automating the mundane, AI has freed marketers to do what only humans can do: think strategically, innovate boldly, and create experiences that move people.

The most successful marketers today aren’t those who are worried about being replaced by AI—it’s those that want to harness it. They understand that competitive edge doesn’t come from the tools alone, but from how skillfully those tools are orchestrated.

Optimizely Opal was built for this new era; making every marketer a force multiplier, every campaign a continuous source of learning, and every customer interaction an opportunity for meaningful connection.

The idea of the “infinite workforce” is not just a vision—it’s a mandate. It signals a future where marketing potential is amplified, not diminished. By investing in AI fluency, adopting practical best practices, and preparing for emerging standards of interoperability, marketing teams can unlock unprecedented value. At Optimizely, we’re committed to leading this journey; helping marketers not only adapt, but thrive, in the age of intelligent automation.