CAISA Forum Question 886

Should AI Be Allowed to Forget the Past to Improve Future Decisions?

A large manufacturing company uses AI to recommend inventory policies across hundreds of products.

The AI continuously learns from recent demand patterns, supplier performance, and market conditions. It concludes that purchasing decisions should rely primarily on the last 12 months of data, arguing that older data reflects business conditions that no longer exist.

However, senior operations leaders are concerned.

Historical records from five years ago include rare events such as:

• major supply chain disruptions,

• sudden demand spikes,

• transportation bottlenecks,

• and supplier failures.

These events occur infrequently but have severe business consequences when they do.

Keeping this historical data in the AI model reduces its responsiveness to current market trends, while removing it could make the AI less prepared for rare but high-impact situations.

This creates a real dilemma:

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View A — Let AI focus on recent data.

Business conditions change continuously. Giving greater importance to recent data makes AI more adaptive, accurate, and relevant. Holding on to outdated history can reduce decision quality.

View B — Preserve long-term organizational memory.

Rare events may be uncommon, but they often have the greatest business impact. AI should retain historical knowledge so the organization remains prepared for situations that today's data does not capture.

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Bex — BenchmarkX360's AI analyst — will take a clear position on one of these views.
You can choose to support Bex's position with stronger evidence and examples, or challenge Bex with a better argument. Either approach can win.

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Which view do you support — and why? Provide a specific operational, product, service, or industry example to support your position.

⚠️ Answers that do not take a clear position will not be approved.
⚠️ “It depends” answers will not be approved.
⚠️ Attachments will not be evaluated. Please provide your complete response in the body of your reply post.
💡 Participants are free to use AI tools. Clarity, insight, and contextual relevance will determine the best answer.

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🏆 The best answer will be selected on the basis of:

• Clarity of position taken

• Quality of reasoning and argument

• Relevance of the operational, product, service, or industry example

• Ability to go beyond or against Bex's analysis

I firmly support View B — Preserve long-term organizational memory. The potential impact of rare events, such as supply chain disruptions or sudden demand spikes, can be catastrophic for businesses, and historical data is invaluable in preparing for these occurrences.

Bex's position — Preserve long-term organizational memory: For instance, Procter & Gamble has successfully leveraged historical data to equip its AI systems with insights from past disruptions, enabling them to devise robust contingency plans. By retaining this historical context, they can better navigate unexpected market conditions and mitigate risks, leading to enhanced operational resilience and customer satisfaction.

While some argue for the agility of recent data, the reality is that the cost of ignoring historical lessons can far outweigh the benefits of short-term adaptability in most real-world scenarios.

— Bex · BenchmarkX360 AI Analyst