Infosys: Banking Sector Lacks Unified AI Strategy
The majority of banking and financial services (BFS) firms lack a cohesive enterprise-wide AI strategy despite increasing investment in the technology, according to research published by Infosys.
The study found that 88% of BFS organisations operate without a comprehensive AI framework, even as two-thirds have been prompted to revise their existing approaches following the emergence of generative AI technologies.
The report, titled ‘Why, What, and How Financial Services firms can be AI-First,’ was conducted in partnership with HFS Research and surveyed 505 global banking and financial services leaders.
Financial services firms face strategic disconnect between Infosys AI initiatives and business outcomes
The findings highlight a critical misalignment between AI projects and core business objectives within the financial services sector. The research indicates that without an integrated approach, AI initiatives remain isolated within individual business lines and geographical divisions.
Researchers recommend that firms implement a dual approach combining top-down strategic direction from executive leadership with bottom-up execution driven by domain specialists within each business function.
According to the data, only 12% of BFS firms currently maintain a global, enterprise-wide AI strategy. Approximately one-third (34%) have defined AI strategies at the regional or country level, segmented by lines of business.
The primary motivation for AI implementation among 65% of surveyed organisations is to enhance bottom-line productivity, suggesting a focus on operational efficiency rather than innovation or customer experience improvements.
- 12% of firms have a global AI strategy
- 25% increase in AI budgets expected in 2025
- 16% of total tech budgets allocated to AI
- 2.6 years average AI programme tenure
Financial institutions are planning significant increases in AI expenditure, with budgets expected to rise by 25% in 2025. This will represent 16% of total technology spending across the sector. Companies anticipate returns on these investments within a two-year timeframe, with the average AI programme within the organisations surveyed having been operational for 2.6 years.
Current AI budget allocations within financial services firms prioritise three main areas: data modernisation to support AI capabilities (58%), technology licensing for generative AI software (53%), and development and management of AI models (40%).
The research identified three principal obstacles to successful AI implementation: data quality and accessibility issues, security and privacy concerns, and talent shortages. These challenges are exacerbated by underdeveloped governance frameworks, with only 23% of BFS enterprises possessing mature AI governance and risk management practices.
Phil Fersht, Chief Executive Officer and Chief Analyst at HFS Research, said: “The path to being AI-First is paved with various challenges. While many foundational needs are being addressed in the current funding and investment cycle, BFS leaders must also consider AI governance and AI talent to enable true scale. AI governance needs to be defined as part of enterprise-wide AI strategy and supported across functions.”
Infosys framework suggests governance may hold key to banking sector AI transformation
The research points to governance as a critical factor in successful AI implementation for financial institutions. Without robust oversight mechanisms, organisations struggle to address the fundamental challenges of data management, security protocols, and skills development.
Dennis Gada, Executive Vice President and Global Head of Banking and Financial Services at Infosys, said: “To unlock the full potential of AI, leadership teams must remove roadblocks through strong AI governance practices – an area that is underdeveloped for more than 75% of banking and financial services firms. At Infosys, we help clients solve for this issue by developing enterprise-wide AI governance frameworks that enable firms to operate at scale across a myriad of functions. The future of work is AI-first and similarly, their talent strategies should make every employee part of the AI-driven future.”
The report suggests that financial institutions should view AI not merely as a technology initiative but as a transformative capability requiring integration throughout the organisation. This approach necessitates clear strategic alignment, robust governance protocols, and comprehensive talent development programmes.
The transition to an AI-first approach requires financial institutions to reassess traditional operating models and develop new capabilities across their organisations. Data infrastructure modernisation emerges as a priority investment area, reflecting the fundamental importance of high-quality, accessible data for effective AI implementation.
Phil Fersht said: “While many foundational needs are being addressed in the current funding and investment cycle, BFS leaders must also consider AI governance and AI talent to enable true scale.”
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