Living with AI: Bridging the Capability-to-Production-Value Gap
Report Coverage
- Broker
- Morgan Stanley
- Region
- United States
- Sector
- Information Technology
- Report Type
- Company Report
- Primary Focus
- Cognizant AI strategy and the enterprise capability-to-production-value gap
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Report Summary
MS examines Cognizant’s three-vector AI strategy: productivity, industrialization, and agentification. Management frames context engineering as a $5-6T opportunity vs legacy ~$1T SI market. Despite ~$1T invested in AI infrastructure, enterprise ROI remains limited. Equal-weight, $63 PT.
Key Takeaways
- Context engineering = $5-6T opportunity vs legacy ~$1T SI market ($1T systems + ~$4.5T ops labor exposed to agentification)
- Three vectors: V1 AI productivity, V2 AI industrialization, V3 enterprise agentification — V2/V3 monetization early
- Enterprise ROI on ~$1T AI investment largely disconnected from outcomes; CTSH as intermediary for context and model routing
- Four structural changes needed: IP acceptance, clearer AI returns, faster implementation, SaaS pricing evolution
- Equal-weight, $63 PT; CIO survey shows flat IT budget growth for CY26
Why This Report Matters
Cognizant’s AI capability-to-value gap framing highlights a critical challenge for the entire IT services sector’s growth and pricing model.
Topics Covered
Companies Mentioned
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This summary is for users researching the Morgan Stanley Living with AI report. It helps users review Living with AI: Bridging the Capability-to-Production-Value Gap coverage, key takeaways, and related broker or sector research paths across AI Enterprise Adoption, Context Engineering, IT Services Monetization; Cognizant Technology Solutions.
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