Optimizely says enterprise marketing teams are rapidly embracing hands-on AI training, as early participants in its Opal University program built hundreds of AI agents designed to automate marketing workflows. The company reported that more than 1,100 marketing and digital leaders have already enrolled in the initiative, signaling growing enterprise demand for practical AI implementation across the marketing lifecycle.

Enterprise marketers are increasingly experimenting with artificial intelligence tools, but many organizations still struggle to move beyond isolated pilots. A new training initiative from Optimizely suggests the next phase of adoption may depend less on new technology—and more on practical education.

Optimizely recently shared results from Opal University, a hands-on training program designed to teach marketing leaders how to build AI agents within its Optimizely Opal platform. The program focuses on helping marketing and digital teams automate everyday workflows using AI-driven agents embedded within the company’s digital experience platform.

The results from the first cohorts highlight the speed at which marketers are beginning to operationalize AI. According to the company, more than 375 AI agents were built by participants in just five days across two cohorts, demonstrating how quickly teams can deploy automation when given direct access to tools and training.

A Rapid Rise in Enterprise AI Training

Demand for the program has grown rapidly. Optimizely reported more than 1,500 registrations and a waitlist exceeding 1,500 additional applicants, reflecting widespread interest among marketing leaders in learning how to integrate AI into everyday processes.

Participants represent a cross-section of global enterprises, including organizations such as LinkedIn, Zoom, DocuSign, KPMG, and Deloitte.

During each five-day program, participants build three AI agents tailored to their organization’s needs. Those agents can automate marketing tasks such as content creation workflows, experimentation analysis, search optimization, research, and campaign management.

According to Optimizely, the program is designed specifically for senior marketing and digital leaders, emphasizing practical applications rather than theoretical AI concepts.

AI Agents for Marketing Operations

The early results illustrate how marketing teams are beginning to use AI agents to automate complex workflows.

Across the initial cohorts, participants created agents covering a wide range of marketing and digital operations. These included agents focused on search optimization, content operations, conversion rate optimization, competitive research, customer success support, and compliance checks.

Some of the reported productivity improvements are significant. For example, a conversion rate optimization (CRO) prioritization workflow that previously required several hours was reduced to about 30 minutes. Performance benchmarking tasks that once took six hours were completed in less than 20 minutes.

Content migration timelines also improved substantially, shrinking from a typical seven-to-ten-day process to roughly two days when automated agents were involved. Prospect research and landing page generation tasks that previously consumed hours per week could be completed in minutes.

Those improvements highlight how AI agents are becoming an operational layer across marketing teams rather than simply a content generation tool.

Moving Beyond AI Experiments

Optimizely executives say the training initiative was created in response to a recurring pattern in enterprise AI adoption. While many marketing organizations are experimenting with generative AI tools, few have established repeatable frameworks that integrate those tools into day-to-day workflows.

Allison Skidmore said successful AI adoption often depends on empowering marketers to build tools that directly support their own processes.

When teams experience immediate productivity benefits, she said, adoption tends to spread more quickly across the organization.

That dynamic reflects a broader shift in enterprise software: the rise of agentic AI systems designed to perform tasks autonomously or semi-autonomously.

Platforms from companies like Microsoft, Google, Salesforce, and Adobe are also increasingly embedding AI agents and copilots into their enterprise software ecosystems.

AI Orchestration in the Marketing Stack

Optimizely’s Opal platform is positioned as an AI orchestration layer within the company’s digital experience platform. The system connects marketing functions such as content creation, experimentation, personalization, and campaign management.

Shafqat Islam said many marketing teams struggle with fragmented technology stacks that make it difficult to deploy AI consistently across campaigns.

Opal attempts to solve that challenge by managing governance, brand guidelines, and workflow orchestration so that AI agents can operate within defined marketing processes.

The approach appears to be gaining traction. According to Optimizely, organizations using its platform have reported improvements in marketing velocity and execution speed. Internal benchmarks indicate a 79% increase in experimentation velocity, an 85% increase in campaigns delivered, and significantly faster time to market.

The Future of AI-Native Marketing Teams

The strong response to Opal University highlights a larger transformation underway in enterprise marketing operations.

Industry analysts increasingly view AI not as a standalone productivity tool but as an infrastructure layer embedded across the marketing technology stack.

Research from Gartner suggests that by 2028, more than 40% of marketing teams will rely on AI-driven automation agents to manage campaign workflows and data analysis. Meanwhile, McKinsey & Company estimates that AI-powered marketing automation could increase marketing productivity by 20–30% in many organizations.

Optimizely’s strategy reflects that shift. The company is expanding its ecosystem of prebuilt AI agents, with more than 15 new out-of-the-box agents introduced in 2026 alone.

As those tools evolve, platforms may begin handling entire marketing processes—from campaign planning to optimization—through coordinated networks of AI agents.

For enterprise marketing teams, the next challenge will not simply be adopting AI tools but learning how to manage AI-native workflows that operate across content, experimentation, and personalization systems.

Programs like Opal University suggest that the future of marketing may depend as much on AI literacy and operational training as on the technology itself.

Market Landscape

The enterprise marketing technology market is rapidly integrating AI capabilities into core platforms. Digital experience platforms, marketing automation suites, and customer data platforms are embedding AI agents that assist with content creation, campaign analysis, and personalization.

According to IDC, global spending on AI-enabled marketing technology is expected to grow significantly over the next five years as organizations prioritize automation and data-driven decision-making.

Training initiatives such as Opal University highlight a critical aspect of this transition: organizations must develop internal AI capabilities alongside adopting new platforms. Without practical training and governance frameworks, many companies struggle to scale AI adoption across marketing teams.

Top Insights

• Optimizely’s Opal University program shows strong demand for hands-on AI training, with over 1,100 marketing leaders enrolling and hundreds of AI agents built during the first cohorts.

• Participants created 375 AI agents in five days, automating workflows across SEO, content operations, experimentation, research, and campaign management.

• Early adopters reported dramatic productivity gains, with marketing tasks such as benchmarking, CRO prioritization, and content migration completed significantly faster using AI agents.

• The program reflects a broader enterprise shift toward agentic AI systems that automate marketing processes across the full campaign lifecycle.

• As AI adoption accelerates, organizations are prioritizing training programs that help marketing teams move beyond experimentation toward operational AI deployment.

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