AI-Driven Modernization: Tackling Tech Debt in Financial Services—A Deep Dive into Services-as-Software and New Operating Models

Financial services organizations—banks, insurers, and asset managers—are at a pivotal crossroads. Decades of incremental technology investments have left many with a tangled web of legacy systems, siloed data, and mounting technical debt. Global estimates put the accumulated tech debt across major enterprises at up to $2 trillion, with financial services bearing a disproportionate share. This burden is more than a technical liability; it’s a strategic threat that hinders innovation, operational efficiency, and the ability to deliver secure, personalized experiences at scale.

The Five Debts: Barriers to AI-Driven Modernization

Through extensive industry engagement and executive roundtables, five critical forms of “debt” have been identified as the primary barriers to AI-driven modernization in financial services:

Technology Debt: Outdated core systems and fragmented architectures slow innovation and increase risk.
Data Debt: Poor data quality, siloed information, and lack of governance hinder AI adoption and regulatory compliance.
Process Debt: Manual, paper-based, or inconsistent processes limit scalability and efficiency.
Skills Debt: A shortage of AI and data talent impedes the ability to implement and scale new solutions.
Cultural Debt: Resistance to change and a lack of an “AI mindset” can stall transformation before it begins.

Addressing these debts holistically is essential for rapid, sustainable AI value creation. Leading institutions are demonstrating that tackling these debts—by building AI/ML catalogs, modernizing data infrastructure, and driving new business models—lays the foundation for enterprise-scale AI adoption.

Why AI Is the Game Changer

AI is not just another tool in the modernization toolkit—it is the catalyst capable of dismantling even the most persistent forms of tech debt. Over 80% of senior executives in financial services believe AI is the breakthrough needed to overcome entrenched technical debt. However, technology alone is not enough. Success demands a shift in mindset, delivery models, and operating architecture.

The Rise of Services-as-Software and AI-Led Service Models

A key insight from recent research is the emergence of “services-as-software”—a new paradigm where technology, not just people, delivers services. For financial services, this shift is critical. Traditional IT services often focus on maintaining legacy systems rather than driving transformation. AI-led service models, by contrast, enable:

Faster innovation and time-to-market
Operational agility and cost savings
Enhanced customer and employee experiences
Proactive risk management and regulatory compliance

Three in four enterprise leaders now expect a pivot from staff augmentation to services-as-software, and 71% are ready to switch providers for better AI execution and leadership. The message is clear: financial institutions that fail to embrace AI-driven modernization risk being left behind.

From Labor-First to Platform-Led: The New Operating Model

The traditional labor-first model—outsourcing, staff augmentation, and FTE-based pricing—has reached its limits. These approaches often perpetuate complexity and tech debt, rather than eliminating it. The future is platform-led, agentic, and software-driven:

Platform-Led Services: Integrated platforms like Publicis Sapient’s Slingshot streamline the software development lifecycle, enabling rapid modernization and reducing reliance on manual processes.
AI-Led Agentic Services: AI agents, such as those orchestrated by the Bodhi platform, augment human capabilities, automate routine tasks, and drive decision-making at scale.
Services-as-Software: This model delivers services primarily through technology, minimizing human intervention and maximizing efficiency. It enables outcome-based, subscription, or consumption-driven commercial models.

Practical Frameworks for CIOs: Five Moves to Break the Cycle of Tech Debt

Don’t manage tech debt—demolish it: Treat tech debt like financial debt—track it, prioritize it, and pay it down with discipline. Use AI to understand, refactor, and retire legacy systems—starting with what slows your business the most.
Rebuild around AI—not on top of it: Rethink workflows, data models, and governance from the ground up, with intelligence as the foundation.
Break up with FTE-first vendors: Shift to partners who offer productized, AI-driven capabilities, not bodies in seats. Look for reusable platforms, IP, and enterprise context.
Price for performance—not presence: Push for pricing that maps to impact—not effort. Embrace outcome-based, subscription, or consumption-driven models.
Redesign your operating model before AI redesigns you: Redefine roles, governance, and delivery around AI-native ways of working. Think platforms, not projects; guardrails, not gatekeepers.

Publicis Sapient’s SPEED Capabilities and Proprietary Platforms

Publicis Sapient’s integrated SPEED capabilities—Strategy, Product, Experience, Engineering, and Data & AI—provide a holistic framework for AI-driven modernization. By connecting business strategy with technology execution and customer experience, this approach ensures that transformation is actionable, compliant, and sustainable.

Slingshot: An AI-powered delivery model that accelerates modernization by automating code migration, streamlining integration, and orchestrating the entire development lifecycle.
Bodhi: An enterprise-scale agentic AI platform that enables cognitive, context-aware, and scalable transformation across the financial services value chain.

These platforms, combined with deep industry expertise, enable financial institutions to move from experimentation to enterprise-scale impact—delivering measurable improvements in efficiency, compliance, and customer experience.

Real-World Impact: Case Studies

Deutsche Bank: Built an AI/ML catalog, modernized data infrastructure, and drove new business models—laying the foundation for rapid, sustainable AI value creation.
Operational Efficiency: For a multinational investment bank, AI-powered document imaging and automation streamlined email and unstructured data handling, saving tens of millions of dollars and driving significant process efficiencies.
Data Modernization: A UK-based retail bank accelerated time to insights for data scientists, enhancing productivity and enabling the bank to stay ahead in a competitive market.
Regulatory Compliance: AI integration into compliance workflows has automated regulatory processes, reduced manual effort, and improved accuracy—critical in a sector where compliance is non-negotiable.
Asset & Wealth Management: A global asset manager used AI to unify data access, streamline operational processes, and accelerate decision-making cycles, all while ensuring compliance and traceability.

The Path Forward: Building Future-Ready Financial Services

The future belongs to financial institutions that can break free from tech debt and harness AI as a driver of innovation, efficiency, and customer value. By addressing technology, data, process, skills, and cultural debts in tandem, banks, insurers, and asset managers can move from incremental change to enterprise-scale transformation.

Publicis Sapient stands as a trusted partner for this journey—combining deep industry expertise, proven frameworks, and a relentless focus on outcomes. With AI as the catalyst, financial services organizations can rewrite the rules of modernization and lead the next wave of industry innovation.

Ready to smash through tech debt? Let’s talk about your modernization journey.