AI didn’t break your processes—it exposed them. Most companies automate chaos instead of redesigning workflows. The fix: outcomes over tasks, streamline first, treat data as fuel.
The story
AI didn’t “break” your processes. It just turned the lights on.
Problem
Most orgs are trying to bolt AI onto workflows that were already limping:
– Rule-based flows that collapse the second an invoice is ugly or a customer does something unscripted. – Legacy SAP/Oracle setups where every integration feels like open-heart surgery. – Black-box models in regulated spaces with zero audit trail. – Teams afraid or confused because nobody explained *why* we’re changing, just that “AI is the future.”
No surprise 55% of firms blame outdated processes when their AI pilots flop. They automated the mess instead of redesigning it.
Solution
The leverage isn’t “more AI.” It’s AI-native process redesign:
1. Start with outcomes, not tasks. “Reduce invoice cycle time” beats “Let’s add an LLM to this step.”
2. Streamline before you automate. Kill redundant approvals *then* let AI auto-approve low-risk expenses or route contracts.
3. Treat data as a product, not exhaust. Clean, labeled, accessible data is the fuel for fraud detection, resume parsing, and predictive supplier alerts.
4. Design for transparency. Build in logs, explanations, and policy checks so compliance isn’t a suspense thriller.
5. Make it cross-functional by default. IT, ops, finance in the same room, owning one workflow, not three silos.
The real skill set now? Align tech with business goals, architect hybrid data flows, and iterate fast without blowing up the core.
AI is making old workflows obsolete. Curious, adaptable humans who can reengineer them? Very much not obsolete.
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