AI in the Chain

Why most supply chains are stuck reacting instead of deciding

Ask almost any supply chain team how their week went, and you will hear the same answer: firefighting. Expediting late orders, resolving shortages, managing escalations, responding to disruptions, and explaining misses.

Firefighting has become normalized. It is often even rewarded. The best firefighters are seen as indispensable.

But firefighting is not a sign of resilience. It is a symptom of missing decision ownership.

This article explains why modern supply chains are trapped in reactive mode, how this erodes performance over time, and how AI enables a shift from constant firefighting to structured, accountable decision-making.

Why firefighting never ends

Firefighting persists because decisions are unclear, fragmented, or delayed.

In many organizations, no one truly owns decisions such as order prioritization, inventory allocation, or customer promise trade-offs. Decisions are made implicitly, under pressure, and often differently each time.

When accountability is unclear, problems resurface. Teams solve symptoms rather than causes.

Technology alone does not fix this. Dashboards show problems faster, but they do not decide what to do.

The hidden cost of constant reaction

Firefighting creates the illusion of control, but it hides structural weaknesses.

Service becomes inconsistent. Inventory grows in the wrong places. Customer trust erodes. Teams burn out. Improvement stalls because everyone is too busy reacting to fix root causes.

Over time, firefighting becomes the operating model.

AI reframes the problem

AI does not replace human judgment. It clarifies it.

By codifying decision logic, AI forces organizations to define who decides what, based on which criteria, and within which constraints.

Instead of reacting to each exception as a unique event, AI treats exceptions as signals to trigger predefined decisions.

This shift turns chaos into flow.

How AI enables decision ownership

Explicit decision models

AI requires decisions to be modeled explicitly. For example, how orders are prioritized when supply is constrained, or how inventory is allocated across regions.

This makes trade-offs transparent and repeatable.

Consistent execution

Once decision rules are defined, AI executes them consistently. This removes emotional bias, politics, and inconsistency from day-to-day operations.

Learning from overrides

When humans override AI recommendations, those overrides are captured and analyzed. Over time, decision quality improves instead of resetting each crisis.

Focus on true exceptions

AI handles routine variability, allowing humans to focus on genuinely novel or strategic issues.

Firefighting volume drops, but decision quality rises.

What leaders often misunderstand

Many leaders believe firefighting proves agility. In reality, it proves fragility.

Others fear that formalizing decisions will reduce flexibility. In practice, it increases it by freeing teams from ad hoc debates.

Structure enables speed.

Implications for supply chain leadership

Supply chain leaders must shift their attention from solving problems to owning decisions.

This requires defining decision rights, escalation thresholds, and success metrics.

AI becomes the execution layer of these decisions, not the owner of strategy.

Practical prompts to break the cycle

Which decisions generate the most recurring firefighting?

Where do teams argue repeatedly about the same trade-offs?

Which exceptions should be automated rather than escalated?

What would change if these decisions were made consistently every time?

These questions expose where decision ownership is missing.

The deeper lesson

Firefighting feels productive, but it is expensive and exhausting.

Supply chains that escape permanent crisis mode do not hire better firefighters. They design better decision systems.

AI is the enabler that makes those systems scalable, consistent, and learnable.

The future of supply chain leadership is not reacting faster. It is deciding better.

References

Harvard Business Review – Stop Firefighting and Start Leading
https://hbr.org/2016/07/stop-firefighting-and-start-leading

McKinsey – Decision making in a crisis
https://www.mckinsey.com/capabilities/risk-and-resilience/our-insights/decision-making-in-uncertain-times

MIT Sloan Management Review – Why Good Leaders Make Bad Decisions
https://sloanreview.mit.edu/article/why-good-leaders-make-bad-decisions

BCG – Decision effectiveness and organizational performance
https://www.bcg.com/publications/2017/people-organization-decision-effectiveness