---
id: "prereq-cross-functional-talent"
type: "prereq"
source_timestamps: ["§ 3. Cross-department communication"]
tags: ["talent-management", "team-composition"]
related: ["concept-ai-center-of-excellence", "framework-four-pillars-of-ai-success"]
reason: "Data science skills alone are insufficient; operational and engineering expertise is required to ground AI projects in practical business realities."
source_url: "https://hbr.org/2025/01/what-companies-succeeding-with-ai-do-differently"
source_title: "What Companies Succeeding with AI Do Differently"
sources: ["execution"]
sourceVaultSlug: "hbr-seg-execution"
originDay: 8
articleStem: "hbr-cl-89-companies-succeeding-with-ai"
sourceUrl: "https://hbr.org/2025/01/what-companies-succeeding-with-ai-do-differently"
sourceTitle: "What Companies Succeeding with AI Do Differently"
---
# Cross-Functional Talent Integration

**Prerequisite:** Successful AI deployment requires more than data scientists — it needs the integration of **operational gurus and engineering experts**.

**Configuration:** Whether centralized in an [[concept-ai-center-of-excellence|AI CoE]] or decentralized in business-unit teams, this cross-functional mix is required to ensure AI solutions actually solve real-world operational problems.

**Why it's required:** Data-science skills alone are insufficient; operational and engineering expertise grounds AI projects in practical business realities. Underpins pillar #3 of [[framework-four-pillars-of-ai-success]].