AI Driven Financial Workflows: Lessons from Scaling for SMEs
summary
Tide says it already serves >10% of UK SMEs and 1M+ small businesses worldwide and lays out a concrete stack: data extraction, autocategorization and planning, tax computation and automated filing with human review. Engineering rules: use classical ML for bounded extraction tasks, deploy LLM-driven workflow agents where latency and control matter, and only compose into workflow → semi-autonomous → autonomous agents after accuracy and compliance (GDPR, DPDPA, CCPA, anti–fincrime) are proven. Trade-offs: higher autonomy raises latency, cost and audit requirements.
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chapters (6)
- 0:00Introduction and business context
- 3:58AI evolution and agentic systems
- 10:19Enterprise GenAI challenges
- 13:54Tide’s connectivity chains
- 17:04Accounting workflow case study
- 20:55Key takeaways and conclusion
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