The use of AI (Artificial Intelligence) applications has seen explosive growth as individuals look to ChaptGPT, Grok, Claude, Gemini, and other generative AI platforms for answers to any type of question.  Similarly, businesses have begun to adopt AI agents and tools to perform a wide array of tasks such as responding to customer inquiries, preparing management presentations, performing financial analyses and internal audits, automating production and quality assurance processes, and making operating and strategic recommendations.  Companies such as Authentic Brands Group, maker of Reebok and Champion athletic apparel and footwear, have encouraged employees at all ranks to embrace AI tools such as Anthropic’s Claude Cowork that uses natural language prompts to automate workflows and perform work tasks.  The company’s marketers use AI tools to generate mock-ups of ads, its finance personnel rely on AI to perform financial analyses, and its legal department conducts AI reviews of licensing agreements.[i]  

By mid-2026, it was estimated that 100 percent of Fortune 500 companies utilized AI in their business operations with 80 percent using active AI agents embedded in workflows across sales, finance, security, customer service and product innovation.[ii]  Microsoft reported that in industries ranging from software and technology, to manufacturing, financial services, and retailing used AI agents to perform complex tasks such as drafting proposals, analyzing financial data, triaging security alerts, and automating repetitive processes.[iii]  In addition, a Microsoft study showed that 29 percent of employees were using unsanctioned AI agents to complete work tasks assigned to them by their employers.[iv]  

Human-AI Collaboration: Best Practices from JPMorganChase

EY, a global consulting firm, advised that human-AI collaboration could enhance the benefits of AI adoption by allowing companies to reimagine jobs to boost human creativity and strategic thinking.  Key considerations for senior managers include how to maintain human-centric values, create healthy organizational cultures in AI-augmented workforces, what will be the role of human talent, and how to foster human-AI collaboration.  

JPMC has developed and implemented ML and IA projects seeking to expand value and efficiency from customer personalization, securities trading, operations, fraud management, and credit decisioning.  Rather than lowering headcount as technology boosts productivity, JPMC provides AI upskilling and education to enable employees to master AI tools and shift their jobs to higher value-adding activities.  AI tools used by employees across the organization in 2026 includes JPMC’s LLM Suite that simplifies work for 200,000 users and its Employee Assistant, which is a personalized AI Agent for employees.  Employees may use the LLM Suite generative AI platform for content and idea generation and querying specific documents and presentation slide decks.  JPMC provides training programs and leverages LLM Suite superusers to assist employees with integrating AI tools into their work.

JPMC’s EVEE Intelligent Q&A, is a Generative AI tool that provides call center staff with accurate and concise answers to myriads of customer questions.  The solution improves call center efficiency, call resolution times, and employee and client satisfaction. The firm’s Coding Assistant is used by more than 40,000 JPMC’s software engineers.  The coding assistant performs repetitive and mundane tasks previously performed by programmers as well as being utilized for code creation and code conversion.  JPMC has experienced a 10 percent to 20 percent increase in programmer productivity since launching the program.  Predictive AI technology has been utilized in the Consumer & Community Banking (CCM) segment to block high-risk transactions originating from social media or Zelle®, detect suspicious login activity, and prevent other fraudulent transactions.  CCM’s technology enhancements resulted in a 21 percent year-over-year reduction in fraud across payment methods in 2025.

AI applications utilized in the Asset & Wealth Management unit includes its proprietary SpectrumIQ suite of AI tools. SpectrumIQ has automated nearly 75 percent of equity trades and almost 85 percent of foreign exchange trading, saving clients approximately $4 billion since its inception.  The suite of AI tools covers approximately 90,000 securities and 22 million documents and analyzed about 7,000 broker research reports daily.  The Smart Monitor component of SpectrumIQ studies each investors’ preferences and delivers prioritized insights in real time, eliminating the need manual research on specific securities.  Connect Coach is another AI tool utilized by AWM that provides more than 12,000 private banking and wealth management users with 25 specialized AI agents.  The platform provides 5,000 front-office users with more than 1 million personalized AI-driven insights. Advisors used Connect Coach to speed meeting preparation, support portfolio analysis, and generate call summaries—all of which provided front-office users to spend more time with clients.    The firm has an additional 100 Generative AI solutions in production and 450 active proof of concept projects.  JPMC plans to initiate as many as 1,000 proof of concept AI projects by year-end 2026.

Key Considerations in AI Adoption and Deployment

Best practices established by JPMorganChase and other early adopters of AI applications act as use cases and provide guidance for firms wishing to build stronger customer relationships, increase sales revenue, and improve productivity.  Rather than looking at AI adoption to merely reduce headcount through automation of labor-intensive tasks, organizations should view AI applications as tools to enhance employee efficiency and effectiveness.  These tools may not only be used to lower costs but may also boost revenues when employees have better quality data needed to meet customer expectations.  Customer-AI interactions are less likely to enhance customer loyalty and selling activity than employee-customer relationships strengthened by high value AI support.  Organizations seeking AI solutions only to lower costs may find that revenues also decline as key relationships between the organization and its customers are diminished.  Successful AI adoption should focus on revenue enhancement to the same extent as productivity enhancement.