Regional Playbook: Overcoming the Five Debts to Gen AI Adoption in Banking
Generative AI (Gen AI) is rapidly redefining the future of banking, promising operational efficiency, hyper-personalized customer experiences, and new business models. Yet, the journey from pilot projects to enterprise-wide transformation is far from straightforward. Across North America, EMEA (Europe, Middle East, and Africa), and APAC (Asia-Pacific), banks face a common set of barriers—technology, data, process, skills, and culture—known as the "five debts." While these debts are universal, their impact and the strategies to overcome them are deeply shaped by regional realities. This playbook explores how leading banks in each region are tackling these challenges, offering actionable insights for transformation teams seeking to accelerate Gen AI adoption.
The Five Debts: Universal Barriers, Regional Nuances
- 1. Technology Debt: Outdated core systems and fragmented architectures slow innovation and increase risk.
- 2. Data Debt: Siloed, poor-quality data and lack of governance hinder AI adoption and regulatory compliance.
- 3. Process Debt: Manual, inconsistent processes limit scalability and efficiency.
- 4. Skills Debt: A shortage of Gen AI and data talent impedes implementation and scaling.
- 5. Cultural Debt: Resistance to change and lack of an “AI mindset” can stall transformation before it begins.
While every bank faces these debts, their manifestation—and the path to overcoming them—varies by region.
North America: Innovation Amidst Complexity
Key Challenges
- Highly complex legacy systems, especially among large, established banks
- Stringent regulatory requirements around data privacy and consumer protection
- Intense competition from fintechs and big tech
How the Debts Manifest
- Technology Debt: Decades-old infrastructure makes Gen AI integration challenging. Modernization is often slowed by the need to maintain compliance and minimize disruption.
- Data Debt: Regulatory scrutiny demands robust data governance, yet data remains fragmented across business lines.
- Process Debt: Manual compliance and risk management processes persist, limiting Gen AI deployment speed.
- Skills Debt: While the region boasts a strong AI talent pool, demand outpaces supply, especially for roles blending technical and regulatory expertise.
- Cultural Debt: Large institutions can be risk-averse, with innovation often siloed in digital labs rather than embedded enterprise-wide.
Success in Action
A major North American investment bank partnered with Publicis Sapient to implement AI-powered document imaging and automation, streamlining the handling of unstructured data and saving tens of millions of dollars. By embedding Gen AI into compliance workflows, the bank reduced manual effort and improved accuracy—demonstrating how targeted modernization can deliver both efficiency and regulatory confidence.
Actionable Insights
- Prioritize cloud-native modernization and unified data platforms to break down silos.
- Foster cross-functional teams that bridge business, technology, and compliance.
- Leverage outcome-based partnerships and proprietary accelerators to move from experimentation to enterprise-scale Gen AI adoption.
EMEA: Regulation as Both Barrier and Catalyst
Key Challenges
- Highly fragmented regulatory landscape (GDPR, PSD2, local authorities)
- Diverse legacy environments across mature and emerging markets
- Heightened focus on responsible AI and ethical considerations
How the Debts Manifest
- Technology Debt: Many banks operate on legacy mainframes; modernization is complicated by evolving EU and national regulations.
- Data Debt: GDPR and other privacy laws require rigorous data management, but data silos persist, especially in cross-border operations.
- Process Debt: Regulatory reporting and compliance processes are often manual and resource-intensive.
- Skills Debt: Shortage of Gen AI talent with deep understanding of both technology and regional regulatory requirements.
- Cultural Debt: Innovation is a priority, but risk aversion and regulatory uncertainty can slow adoption.
Success in Action
Deutsche Bank’s partnership with Publicis Sapient exemplifies how EMEA banks can overcome the five debts. By building an AI/ML platform and catalog, modernizing data infrastructure, and embedding responsible AI practices, Deutsche Bank accelerated Gen AI adoption, improved customer engagement, and enhanced compliance—all while aligning with strict regulatory expectations.
Actionable Insights
- View regulation as a catalyst for modernization, not just a barrier.
- Invest in robust data governance, responsible AI frameworks, and agile, cross-functional teams.
- Use strategic partnerships and proprietary platforms to accelerate modernization while ensuring regulatory alignment.
APAC: Leapfrogging with Digital-First Strategies
Key Challenges
- Rapid digital adoption and mobile-first customer expectations
- Varied regulatory maturity across markets
- Intense competition from digital-native banks and super-apps
How the Debts Manifest
- Technology Debt: Many banks, especially in emerging markets, can leapfrog legacy constraints by adopting cloud-native, modular architectures. Established banks still face integration challenges.
- Data Debt: Data fragmentation is common, but there is strong momentum toward unified, cloud-based data platforms.
- Process Debt: Manual processes persist in some markets, but digital-first strategies are driving rapid automation.
- Skills Debt: Significant shortage of Gen AI and data talent, particularly outside major hubs.
- Cultural Debt: Strong appetite for innovation, but organizational silos and legacy mindsets can impede progress.
Success in Action
A leading APAC retail bank, with support from Publicis Sapient, accelerated time to insights for data scientists by modernizing its data infrastructure. This enabled the bank to deliver hyper-personalized experiences and stay ahead in a highly competitive market. In Australia, banks are leveraging AI to deliver personalized services and proactive support, but must also address customer concerns around data privacy and the loss of human touch.
Actionable Insights
- Capitalize on digital-first momentum by investing in cloud-native platforms and unified data strategies.
- Collaborate with experienced partners to bridge skills gaps and ensure scalable, compliant Gen AI solutions.
- Prioritize customer education and transparency to build trust in AI-driven services.
Accelerating Gen AI Adoption: A Regional Playbook
While the five debts are universal, the path to Gen AI value is shaped by local realities. Banks seeking to accelerate Gen AI adoption should:
- Assess regional regulatory and market dynamics to tailor modernization strategies.
- Invest in cloud-native, unified data platforms to break down silos and enable real-time insights.
- Foster cross-functional, agile teams that bring together business, technology, and compliance expertise.
- Prioritize responsible AI and robust governance to build trust and ensure regulatory alignment.
- Leverage proven frameworks and platforms—such as Publicis Sapient’s SPEED model—to accelerate transformation and scale Gen AI impact.
The Path Forward
Gen AI is not just a technology upgrade—it is a catalyst for reimagining banking in every region. By addressing the five debts in a regionally tailored way, banks can move from isolated pilots to enterprise-wide transformation, delivering operational efficiency, regulatory confidence, and customer-centric innovation. Publicis Sapient’s global expertise and local experience position us as the trusted partner for banks ready to lead in the Gen AI era.
Ready to accelerate your Gen AI journey? Connect with Publicis Sapient’s experts to unlock the full potential of generative AI in your market.