Gartner® Innovation Insight: Context Engineering
Context engineering is the discipline of designing, managing and optimizing the information provided to GenAl models to improve the AI system’s accuracy and performance. It achieves this by building comprehensive systems that dynamically provide Al models with the knowledge and constraints needed for multistep task execution.
In this research report, Gartner® finds that context engineering enables teams to build AI systems with:
- Improved operational efficiency and scalability: By optimizing token consumption and reducing latency, context engineering makes Al applications more cost-efficient and practical for large-scale, real-world deployments.
- Higher adoption and production readiness: It increases the likelihood that exploratory Al initiatives and proofs of concept will successfully transition into fully operational, enterprise-grade deployments by ensuring reliability, accuracy and relevance.
- Enhanced trust and user experience: Consistent and accurate outputs, along with robust performance and adherence to instructions, build greater user trust. This allows Al applications to be more dependable, fostering improved user experience.
Download the report to learn how to apply the key principles of Context Engineering to build AI systems that successfully transition from prototype to production.
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Gartner, Innovation Insight: Context Engineering, By Akis Sklavounakis, Manjunath Bhat and Philip Walsh, 01 September 2025
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Gartner Cool Vendors in AI Engineering, Arun Chandrasekaran, Manjunath Bhat, Arup Roy, George Brocklehurst, 6 November 2024
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