Many Organizations Can't Name Their Own Workflows
Asana completed its acquisition of StackAI in May, according to Diginomica. The deal adds no-code agentic workflow building and multi-system orchestration to the platform. It also surfaces a problem CEO Dan Rogers says is blocking AI agent adoption across enterprises.
Rogers put it directly: "CEOs say to me, one of the biggest blockers is, I don't even have a list of my workflows. I don't have a visual representation of my workflows, and actually, my employees and teams that are working within workflows almost can't self-realize what that workflow is."
Employees know the steps they take to finish a task. But those steps live as tribal knowledge, never mapped as a repeatable process. Undocumented workflows are, in Rogers's telling, one of the biggest blockers to AI agent adoption.
What StackAI Adds to the Platform
Asana already operates AI Studio, its agentic workflow builder, with integrations into Gmail, Outlook, Slack, HubSpot, Figma, and Canva. StackAI brings capabilities for complex multi-system workflows, hundreds of integrations, and pre-built templates for regulated industries.
Chief Product Officer Arnab Bose cited know-your-customer workflows for financial services firms and customer onboarding for healthcare and life sciences as examples of those templates. Bose also said the acquisition pulled forward capabilities previously as much as a year out on the AI Studio roadmap.
The Shift to Outcome-Based Integration
Bose described what makes agentic orchestration different from earlier API-based integration. The traditional step-by-step approach, he said, requires catching every exception case upfront. The new model works differently.
"It's an outcome-based approach, where you set a goal, and then you can leverage AI capabilities under the covers to determine what is the best possible path to get there." Bose added that these new agents are goal-oriented and will keep working in a long-horizon way until that goal is achieved.
The Diginomica author's own editorial take is that clearly defining the desired outcome matters more than documenting every individual step, and that over-specifying individual steps may handicap the AI's ability to find the best path. If that framing holds, an ill-defined goal could produce an agent that works persistently toward the wrong thing — a question worth testing before any production deployment.
The Forward Deployed Engineer Dependency
StackAI brings a team of Forward Deployed Engineers who work with customers through discovery and post-sale adoption. Bose said this support is currently necessary because customers need help re-imagining business-critical workflows as agentic processes. He expects that need to diminish over two to three years as the practice matures.
For buyers evaluating the platform today, that team is a real dependency. The article does not address typical engagement cost or data residency handling. Those are questions worth raising before signing.
The Audit That Reveals Whether You're Ready
Rogers's observation reflects what CEOs tell him directly. The practical implication is narrow and testable.
Pick one candidate workflow. Ask whether it is written down as a repeatable process. If the answer is no, that workflow is not ready to agentify, regardless of what the platform can do.
That single mapping exercise reveals whether the foundation exists to move forward. Rogers notes that many organizations have let employees organically figure out the best path to getting work done, with the result that many crucial workflows have never been formally documented. That is the gap AI agents expose, and the gap that has to close first.