The advent of gen AI has driven two-thirds (66 percent) of banking and financial services (BFS) enterprises to update their AI strategy - yet the majority (88 percent) of BFS firms lack a comprehensive, enterprise-wide AI strategy, according to a new study from Infosys (NYSE: INFY), a global leader in next-generation digital services and consulting.
The new report titled "Why, What, and How Financial Services firms can be AI-First," conducted in collaboration with HFS Research, underscored the critical gap at many BFS firms between AI initiatives and overarching business objectives. A cohesive, global enterprise-wide AI strategy, however, ensures that AI investments directly contribute to revenue growth, cost optimization, and enhanced stakeholder value.
The study, which sampled 505 global banking and financial services leaders, found that despite BFS enterprises being heavily invested in AI, they need to better assess, adopt, and apply AI in strategically meaningful ways. Without a strategic alignment of AI in the broader business strategy, AI efforts are fragmented across individual business lines and geographic silos. To maximize enterprise-wide value, a top-down strategic framework with clear and purposeful guidance from C-suite leadership, coupled with bottom-up execution driven by domain experts within each business function, is essential. This integrated approach capitalizes on the burgeoning AI opportunity for BFS firms and ensures that its deployment consistently advances the enterprise's strategic priorities.
Key data highlights include:
- Only 12 percent of BFS firms have a global, enterprise-wide AI strategy, with roughly a third (34 percent) having an AI strategy defined by lines of business at the country or regional level.
- The top AI objective for nearly two-thirds (65 percent) of banking and financial services (BFS) enterprises is to boost bottom-line productivity.
- BFS firm's AI budgets are expected to increase 25 percent in 2025, commanding 16 percent of total tech budgets. Return on investment (ROI) expectations are set at two years and the average tenure of formal AI programs within firms is 2.6 years.
- The top three initiatives in BFS firms current AI budgets are data modernization to support AI (58 percent), technology licensing of gen AI software (53 percent) and AI model development and management (40 percent).
- The top three challenges to AI success - data quality and access, security and privacy, and talent - are exacerbated by the fact that only 23 percent of BFS enterprises have mature AI governance and risk management practices, which hinder their ability to effectively address these critical issues.
Phil Fersht, Chief Executive Officer and Chief Analyst, 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."
Dennis Gada, EVP and Global Head of Banking and Financial Services, 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 percent 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."
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