AI Does Not Transform a Broken Process — It Only Accelerates It

When an AI initiative starts, the temptation is to ask what can be automated, summarized, predicted or delegated to an agent.

But there is a more important question that should come first: is the process itself worth accelerating?

AI does not remove unnecessary approvals, broken hand-offs, duplicated work or unclear ownership by itself. It can simply help all of them happen faster.

Three ways AI can amplify a broken process

Faster wasteIf the process contains low-value steps, AI may increase throughput without removing the waste.

Faster inconsistencyIf rules, policies or knowledge are contradictory, AI can reproduce those contradictions at greater speed and scale.

Faster costMore automation can add integration, monitoring and exception-handling cost to a process that should have been simplified first.

The research signal is consistent

30%

Deloitte says only about 30% of organizations are redesigning key processes around AI.

2×

PwC says AI leaders are about twice as likely to redesign workflows around AI rather than simply add AI tools.

Redesign

Gartner's 2026 research explicitly links stronger AI ROI to fundamental process and value-stream redesign.

BCG makes the same point from an economics angle: productivity does not automatically become value, and “acceleration without simplification” can leave the organization doing more of the wrong work.

A simple pre-AI test

Before adding AI to a process, ask:

Which steps exist only because the old system or policy required them?
Which approvals genuinely reduce risk, and which merely move responsibility?
Where is work repeated because the first pass is incomplete or unreliable?
Which decisions could disappear entirely if the process were redesigned?
What outcome should become easier for the customer or employee?

What this looks like in practice

In several transformation situations, the biggest opportunity was not “automate the task.” It was first to understand the end-to-end journey, identify failure points and redesign the process. Only then did automation, analytics or AI become useful enablers rather than expensive overlays.

The best AI opportunity may be a process step you decide not to automate at all—because you remove it.

Go deeper

The practitioner deep dive provides a 7-step “simplify before automate” method and a practical readiness checklist.

Read the full practitioner deep dive →

Sources

BCG — Making AI Productivity Pay Off — 5 May 2026. BCG argues that productivity gains do not automatically become lower cost or better performance; capacity must be deliberately redirected and work redesigned.
Gartner — Why You’re Not Getting AI ROI — And How to Build Compounding AI Value — 13 May 2026. Public abstract: deploying AI into existing workflows often creates isolated projects and marginal gains; core processes and value streams need fundamental redesign.
Deloitte — State of AI in the Enterprise 2026 — 2026. Deloitte reports widespread productivity gains but only 34% of organizations truly reimagining the business; only 30% are redesigning key processes around AI.
PwC — 2026 AI Performance Study — 13 Apr 2026. PwC reports that 75% of AI economic gains are being captured by 20% of companies; leaders are twice as likely to redesign workflows around AI and are more focused on growth, not just productivity.