---
id: "claim-business-problem-first"
type: "claim"
source_timestamps: ["§ Understand Market Trends"]
tags: ["strategy", "ai-adoption"]
related: ["contrarian-problem-over-tech", "quote-problem-first", "framework-ai-deployment-process"]
confidence: "high"
testable: false
speakers: ["Sunil Gupta", "Frank V. Cespedes"]
sources: ["commercial"]
sourceVaultSlug: "hbr-seg-commercial"
originDay: 5
articleStem: "hbr-foci-64-ai-broaden-customer-base"
sourceUrl: "https://hbr.org/2025/03/how-one-company-used-ai-to-broaden-its-customer-base"
sourceTitle: "How One Company Used AI to Broaden Its Customer Base"
---
# Business Problems Must Precede AI Strategy

**Claim (confidence: high; testable: no).** Companies frequently **invert the strategic process** when a new technology emerges, hunting for use cases to justify their AI investments. The authors ([[entity-sunil-gupta|Gupta]] and [[entity-frank-v-cespedes|Cespedes]]) assert that value is created only by **first clarifying the business problem or market opportunity** (e.g., SAP needing to profitably reach SMEs) and *only then* evaluating whether AI is the appropriate mechanism to solve it.

This is the load-bearing claim behind [[contrarian-problem-over-tech]] and is stated verbatim in [[quote-problem-first]]. It is step 1 of the [[framework-ai-deployment-process]].

> **Enrichment check:** **Strongly supported** by mainstream enterprise AI practice and SAP's own positioning (SAP frames Business AI around concrete customer/sales/service problems, not a standalone "AI program"). SAPinsider stresses that a successful AI strategy is anchored in transforming customer experience and operations — not technology for its own sake — and McKinsey studies of AI in customer operations similarly begin from specific use cases. Consistent with classic strategy literature (Porter) warning against technology-led initiatives.


## Related across articles
- [[contrarian-better-product-fails]]
- [[contrarian-hype-does-not-equal-readiness]]
- [[claim-better-is-not-enough]]