Why Enterprises That Automate Broken Processes Will Only Break Faster
Automating a broken process doesn't fix it—it scales the failure. Here's what enterprise leaders are getting wrong about AI adoption.
Why it matters
As enterprises move AI from pilot to production, this piece warns that blindly automating legacy workflows without first fixing underlying process failures will amplify operational damage rather than create value. A critical governance and strategy lesson for CTOs and operations leaders.
The key facts
8 to knowEnterprise AI moving from experimentation to scale phase
Early friction should be treated as leadership signal
Process quality must precede automation
Risk: scaling broken workflows through AI deployment
Article published June 2026 — reflects current enterprise AI deployment maturity
Frames process automation as leadership/governance signal, not just technical decision
Addresses scale phase friction in enterprise AI adoption
Implies observed pattern: early-stage failures in enterprise AI rollouts driven by process debt
Go to the source
Forbes Innovationforbes.com
Publisher excerpt: As enterprise AI moves from experimentation to scale, early friction should be treated as a leadership signal.