Earlier we did episode one of this with Grady Booch where we discussed the principled view of that what's changing and what remains unchanged, what is hyped and what is actually naturally coming with the AI changes. We also spoke about that what is the difference between the design and the architecture and what teams are focusing and what they might be missing.
As the Director of CIBC's AI Applications Development team, you will lead a high-performing, full-stack team of AI engineers, developers, and QA specialists responsible for developing and supporting enterprise-grade AI solutions. In this leader-of-leaders role, you will provide technical leadership to ensure the successful design, development, and deployment of advanced AI applications across CIBC. You will oversee collaboration with other technology and business units to define solution architecture, integration contracts, and ensure seamless interaction between services, aligning with strategic business needs and technical standards.
Across every industry, organizations are investing heavily in the potential of artificial intelligence to reshape how they operate and grow. Nearly 80% of executives expect AI to significantly contribute to revenue by 2030, yet only 24% know where that revenue might come from. This isn't an awareness gap. It's an architecture gap. The companies already capturing AI's value aren't waiting to discover it through pilots and proofs-of-concept.
In the first article we looked at the Java developer's dilemma: the gap between flashy prototypes and the reality of enterprise production systems. In the second article we explored why new types of applications are needed, and how AI changes the shape of enterprise software. This article focuses on what those changes mean for architecture. If applications look different, the way we structure them has to change as well.
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