The news: Typeface launched Marketing Orchestration Engine, an end-to-end platform designed to help marketers break down bottlenecks around AI campaign-generation workflows.

Marketing Orchestration Engine features three main capabilities:

• A context graph that trains AI on brand guidelines, governance, previously deployed assets, and other context signals.
• Customizable agent workflows that can develop on-brand content that’s repeatable and scalable across channels and can be published as agents.
• IT controls that help teams handle tasks like plugging in Typeface across apps or into GPTs and clouds.

Zooming out: AI outputs are only as good as the data and context that’s informing them, Typeface CMO Jason Ing told EMARKETER.

“As you use AI, it should get smarter and the performance of your campaign should feed it and inform how it gets smarter over time. … Context is everything when it comes to really strong AI usage, otherwise you end up with inconsistencies, or what some people might refer to as AI slop,” Ing said.

Why it matters: Limited customization is the top challenge to AI adoption among 35% of global marketers, per Canva.

By using customized workflows with knowledge of brand history, guidelines, and other institutional information, companies can effectively orchestrate campaign workflows, personalize outputs, and create content for emails, ads, social, web, or video.

“There’s no one company we work with that has identical workflows when it comes to how they do campaigns, depending on their product, segments, (and the) geographies they operate in. To be able to create bespoke workflows that mimic that is really, really important,” Ing said.

Recommendations for marketers: Enterprise AI adoption could be constrained by integration and fit rather than awareness or interest. Tools that can merge with existing work stacks and hold institutional knowledge have an advantage over standalone generators.

• Audit where AI breaks down. Pinpoint where workflows may stall, such as brand approval, integrations, or versioning, and adopt tools to support customized versioning and creation.
• Start with high-volume, low-risk use cases. Agentic AI could make the most sense where scale is the pain point, like creating paid social and email marketing variations.
• Clarify ownership. As workflow automation increases, define who is accountable for outputs to avoid governance gaps.