Embedding AI into Trusted Workflows

This shows how the AI wave first spread through SaaS by arriving inside trusted software that companies were already paying for. Brex did not begin with a lab style AI roadmap. It began by watching vendors like Intercom turn AI into a working feature inside a daily workflow, then moved to embed similar automation into finance jobs like expense review, receipt itemization, and policy checks where accuracy and clear ROI matter most.

• Intercom was an early proof point because it put LLMs directly into a workflow companies already understood, customer support. Fin could ingest help docs, answer questions in natural language, and charge per resolved issue, which made AI feel like a concrete operating tool rather than a science project.
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• Brex had different constraints than Intercom. Support software can tolerate faster experimentation, but finance software touches approvals, books, and policy enforcement. That is why Brex described a slower, more formulaic rollout, focused on narrow tasks such as memo completion, receipt parsing, and flagging out of policy spend.
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• The broader pattern is that incumbent SaaS vendors became AI distributors for their customers. Once teams saw AI working inside products they already used, internal adoption got easier, budgets followed, and companies like Brex spun up dedicated AI teams to decide where the technology could improve an existing product instead of replacing it.
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Going forward, the winners in B2B SaaS are likely to be the companies that turn AI into a dependable workflow step inside software buyers already trust. In finance especially, that favors products that automate small but repeatable decisions first, then expand outward from assistive features into higher value approvals, audits, and end to end operating workflows.