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
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
Who this summary is for
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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