As enterprises move into 2026, the way artificial intelligence success is defined and measured is undergoing a fundamental shift. Across large global organizations, the focus is moving away from isolated AI benchmarks and technical trials toward a clearer understanding of how AI delivers measurable, end-to-end business value.

In approved executive commentary shared by JPMorganChase, this shift is framed through the lens of enterprise-scale execution, productivity, and long-term growth. The perspective reflects how large institutions are reassessing AI impact not as a collection of individual use cases, but as a driver of systemic value across workflows and operations.

The commentary is attributable to Arvind Joshi, COO and CFO for Global Technology at JPMorganChase, who oversees technology operations, investment discipline, and modernization strategy for an organization deploying nearly $18 billion in annual technology spend. His insights outline how AI success in 2026 is increasingly measured by its ability to enhance organizational capacity, efficiency, and delivery at scale.

Commentary, attributable to Arvind Joshi, COO & CFO for Global Technology at JPMorganChase:  

As we enter a new year, we’re also entering a new era for implementing and measuring AI success. The paradigm of evaluating progress by technical benchmarks—such as model accuracy, the number of use cases, AI adoption in process components—is giving way to a more sophisticated, E2E value-driven approach. The true measure of AI will stand in its ability to deliver meaningful, measurable impact on organizational productivity, strategic agility, and long-term growth. 

Rather than focusing solely on obvious metrics like dollar savings and efficiencies generated, which can sometimes oversimplify or obscure the true impact, leading organizations will emphasize how AI meaningfully enhances and changes end-to-end workflows, resulting in step function change in value. At JPMorganChase, coding assistant tools have enabled software engineers to shorten the coding phase of development by 10-20%, allowing them to dedicate more time to high-value, strategic initiatives. We are now looking at how AI will optimize the entire SDLC, which includes planning, development, testing, review and deployment. These productivity gains will directly expand our capacity to deliver more for our clients, accelerate cycle times and drive business growth.

Looking ahead, organizations that empower their teams to re-imagine full business processes from start to finish, leveraging the entire AI toolset, will set new standards for digital productivity and industry leadership.

AI-Driven High Value Work

A central theme is the growing emphasis on how artificial intelligence contributes to organizational productivity at scale. Rather than evaluating AI through isolated technical metrics, the focus is placed on understanding how technology investments translate into tangible improvements across the workforce.

This perspective reflects a broader shift in how enterprises are assessing AI outcomes in 2026. Productivity gains are increasingly viewed in terms of how effectively employees are enabled to deliver higher-value work, supported by AI-driven tools and reengineered workflows.

In the context of JPMorganChase’s technology strategy, this approach highlights how AI is being aligned with business priorities and operational execution, ensuring that technology investments support measurable improvements in capacity, efficiency, and delivery.

Discover the future of AI, one insight at a time – stay informed, stay ahead with AI Tech Insights.

To share your insights, please write to us at info@intentamplify.com