Optimizely training sparks surge in marketing AI agents

Participants in Optimizely's Opal University training programme built 375 AI agents in five days across its first two cohorts, while demand has pushed the waitlist beyond 1,500 people.

The figures suggest growing interest from large marketing and digital teams in practical AI training rather than limited pilot projects. More than 1,100 senior marketing and digital leaders signed up in the first two weeks after launch, according to Optimizely.

Aimed at senior marketing leaders, the programme is structured as a five-day certification course. Participants are guided through building three AI agents tailored to their organisation's workflows, focusing on tasks teams carry out regularly.

Across the first two cohorts, more than 60 participants built agents for search engine optimisation, content operations, conversion rate optimisation, research, customer success, compliance and internal operations. Of those, 70 were created for SEO, GEO and AI search optimisation, 39 for content operations, and 30 for CRO and experimentation.

Many of the agents are already being used in day-to-day work, the company said. Reported examples include a performance benchmarking and analysis process reduced from six hours to 18 minutes, content migration cut from seven to 10 days to about two days, and a CRO prioritisation workflow shortened from several hours to 30 minutes.

Teams reported time savings of 80% to 95% across recurring weekly workflows, according to Optimizely. In the initial cohort alone, 50 participants built 170 AI agents in five days.

Enterprise Demand

Participants came from a range of global companies, including Canva, Asana, LinkedIn, Zoom, DocuSign, KPMG, Deloitte, Bloomberg, EY and Foot Locker. The mix points to demand from established enterprise teams trying to move AI into routine business processes rather than testing isolated tools.

That shift is central to Optimizely's case for the programme. Many organisations have adopted generative AI tools but remain at an early stage in using them in a structured, repeatable way across campaigns, content and experimentation, it said.

Allison Skidmore, chief customer officer at Optimizely, said the challenge is less about initial interest than adoption within teams. “The teams that are actually winning with AI right now are focusing on change management and ensuring adoption happens not just because of top-down push but because marketers can get time back to create and optimize powerful campaigns,” Skidmore said.

She linked the training model directly to that adoption effort. “That's exactly why we built Opal University. When marketers get hands-on time building agents that work for their workflows, adoption follows because they feel the benefit directly. That's how you scale AI across the entire marketing lifecycle,” she said.

Platform Push

The training programme also serves as a route into broader use of Optimizely's Opal platform, which the company positions as a system for coordinating AI agents across marketing and digital work. It says the platform connects content creation, campaign management, experimentation and personalisation in a single workflow.

Optimizely argues that many businesses still run AI in disconnected pockets because marketing technology stacks have become too fragmented. Its aim is to let teams create agents that can work with brand context, internal data and existing processes, then reuse those agents across departments.

Shafqat Islam, president at Optimizely, said fragmented systems remain a barrier to broader AI adoption. “Most teams are still running AI in pockets because MarTech has become too complex for it to work any other way,” Islam said.

He added: “What Opal does is absorb that complexity - the governance, the brand context, the orchestration - so teams can build agents that understand their brand, their data, and their processes, and reuse them across the whole organisation. That's why we're seeing adoption accelerate the way we are.”

Optimizely also cited broader platform benchmarks that it said reflect increased use of AI-driven workflows. According to the company, customers using its system recorded a 79% increase in experiment velocity, an 85% increase in campaigns delivered, a 54% faster speed to market, and an 80% increase in pages created.

The company is expanding its directory of ready-to-use agents and has launched more than 15 prebuilt agents this year for tasks including GEO performance, competitive analysis and experimentation. Weekly cohorts will continue as more marketing teams look for structured ways to apply AI in daily work, it said.