This CIO doesn’t ‘hire engineers to write code’: 3 AI

What happened

Evidence suggests that delivering value from AI is hard. With 91% of professionals saying their firm still falls short on AI, business leaders and professionals have lots of work to do to ensure emerging tech explorations become useful production services.

” Haus explained how employees use the agentic platform and its models to create new products and services. ” He gave the example of using emerging technology to improve the experience of a customer who calls the bank. “We use machine learning to understand intent so we can get you to the right person quickly,” he said.

” Haus said the key to success is embedding agents and algorithms deep into the operational process, whether that’s a staff member using an internal interface or customers using a web service or mobile app. Emerging technology is available to Chase employees who work with the systems every day, but its inner workings must be seamless to people who use the bank’s services.

“The real magic is making things easier for a customer, so they don’t even realize that the experience has been made better,” he said. ” While great AI-enabled customer services are crucial, those products must be delivered securely, with the highest possible priority placed on data protection. ” Data protection is an absolute must, as is consent and privacy.

“If you use data for something, we ensure our customers know,” he said. “We would never use the data in an insecure way or against any of our privacy, compliance, or regulatory guidelines. ” Security isn’t just a customer-facing consideration. Haus said AI also assists Chase behind the scenes, particularly in developing software quickly and effectively.

Why it matters

Gill Haus, chief information officer at Chase, the consumer banking arm of JPMorgan Chase & Co, recognized that creating value in the age of AI is about much more than deciding to implement a hyped-up model or service. “Saying that you’re going to be efficient by putting a target in place is not the same thing as reimagining your processes through an agentic lens,” he told ZDNET.

Haus said it’s crucial to understand that roles and responsibilities will shift, and AI is already transforming the work that Chase staff fulfill, both in the IT department and beyond. “We are seeing that our traditional engineer, who was writing code in the past, can do more than just write code,” he said.

” As agents become part of the internal operating fabric, the resulting workplace will blend AI and humans. Haus said it’s already possible to see this transformation at Chase, particularly in coding, and the people who fulfill engineering roles. This impact shows up in ways that would have seemed surprising only six months ago. “I don’t really hire engineers to write code.

Now, I know that sounds weird because that’s what I should hire engineers to do,” he said. “But today, I hire engineers to know what code to write. There’s a big difference. Until six months ago, you had to write the code. But now you don’t have to because an agent can help you.

” So, with a tight focus on outputs and not just inputs, how does Haus ensure Chase has the right approach to AI? The answer centers on three core fundamentals: creating seamless services, delivering secure products, and enabling reliable outputs. Haus said his organization thinks deeply about AI’s role in the operating model, with all staff trained to use these tools effectively.

A crucial element of this approach is LLM Suite, the firm’s internal agentic platform that staff can use to ask questions, review documents, and create specifications. LLM Suite was released in summer 2024 and provides access to large language models, both frontier and open-source technologies, in a secure environment. “It’s a platform that anyone in the organization can use,” he said.

What to watch

Haus said the AI-enabled tools professionals use help them identify bugs, prevent bad actors, and deliver better customer experiences. For other professionals and business leaders, the watchword for secure software development in the AI age is proactivity.

“The thing that I believe is incredibly important is continuing to make sure, outside of what we do to make AI work well, that we’re focused always on our perimeter, ensuring that we are keeping our software updated, and that we are working on addressing vulnerabilities in a timely fashion,” he said.