Product-IT operating model in financial services: Why IT must move closer to business value in the AI era

2026-07-14 · Source: Everest Group Research Portal · Field: Business & Management — Operations & Process Management, Project & Product Management, Corporate Strategy & Leadership · Depth: Intermediate, medium

Summary

The Product-IT operating model is becoming essential for financial services firms to effectively apply Artificial Intelligence (AI) and align technology investments with business value. Traditional project-led IT models, which optimize applications and functions separately, struggle to deliver value in an AI-first enterprise where outcomes are measured through customer journeys, resilience, and overall business performance. This shift requires IT to move closer to products, experiences, and value streams, rather than remaining organized around systems and projects. Key changes include transitioning from temporary projects to durable product teams, adopting portfolio-based funding, decentralizing governance within guardrails, and evolving talent, sourcing, and performance metrics to focus on OKRs, unit economics, and AI/control health. Implementing this model also demands significant evolution in workforce systems, procurement strategies, and change management to ensure accountability and continuous value realization.

Key takeaway

For Directors of AI/ML or VPs of Engineering in financial services evaluating their operating model, you must transition from project-led IT to a product-led approach. This shift ensures your AI investments directly translate into measurable business value, improving customer journeys, resilience, and productivity. Prioritize areas with direct business impact for full product ownership, and evolve your workforce and procurement strategies to support durable, cross-functional teams focused on continuous outcomes. Failing to adapt risks funding AI activity without clear proof of impact.

Key insights

AI necessitates a Product-Led IT operating model in financial services to align technology with business value streams.

Principles

• Business value creation shifts to products and experiences.
• IT accountability must extend beyond project delivery.
• Continuous improvement requires cross-functional ownership.

Method

Transition to Product-Led IT involves shifting structure, funding, governance, talent, sourcing, and performance metrics towards durable product teams, portfolio funding, and OKR-led outcomes.

In practice

• Prioritize product ownership for direct customer/operational impact.
• Modernize entangled capabilities before productizing them.
• Evolve procurement to outcome-linked capacity sourcing.

Topics

• Product-Led IT
• Financial Services
• AI Operating Models
• Value Stream Management
• IT Governance
• Workforce Transformation

Best for: CTO, Executive, AI Product Manager, Director of AI/ML, VP of Engineering/Data, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Everest Group Research Portal.