Code to Culture: AI-Driven Workforce Transformation in Financial Services

Across global financial institutions, leadership teams are reimagining business models and organizational structures for an AI-enabled future, aiming to drive productivity, deepen insights, improve processes, and ultimately increase profitability.

From Goldman Sachs deploying “Devin” — an AI-agent that’s also a software engineer, to Mastercard using advanced AI to fight fraud, to JPMorgan Chase being “fundamentally rewired” for the AI era, AI-driven transformation in financial services is well under way.

Yet despite rapid AI adoption, transformations of workforces themselves are lagging. RRA’s Global Leadership Monitor survey indicates only 30% of financial services leaders feel prepared to address the issue of workforce transformation over the next 12-18 months. Similarly, just 32% feel their employees possess the technical skills to implement GenAI effectively, and fewer than a quarter report active GenAI programs in their teams’ day-to-day workflows.

To offer leaders a perspective on this evolving landscape, we set out to understand the why, what, and how of AI-driven workforce transformation in financial services organizations. Our research highlights three core insights:

1. Despite rapid AI adoption, financial services workforce and operating models have yet to evolve, highlighting an organizational readiness gap
2. The functional leaders driving effective workforce transformation exhibit distinct competencies that balance innovation with risk
3. Financial services leaders are redefining workforce transformation by coupling AI ambition with professional judgment

Despite rapid AI adoption, financial services workforce and operating models have yet to evolve, highlighting an organizational readiness gap

Financial services organizations are accelerating their GenAI adoption, with 91% reporting taking steps towards implementing the tech in their function/team’s day-to-day workflow in H1 2025 – up from 71% a year prior (Figure 1).

AI’s productivity benefits are proving themselves across financial institutions. Take BNY: its upgraded AI platform, Eliza, helps develop client briefings in minutes versus hours, and 98% of BNY employees are now trained on GenAI.

Figure 1: H1 2024 vs H1 2025 generative AI implementation progress in financial services
% of financial services leaders answering, “To what degree has your function or team implemented generative AI”

_{Source: Russell Reynolds Associates’ H1 2025 Global Leadership Monitor, n = 329 Financial Services CEOs, C-level leaders, and next generation leaders; H1 2024 Global Leadership Monitor, n=245 Financial Services CEOs, C-suite, board, and next generation leaders}

While the industry is making bold strides in terms of GenAI implementations, this has yet to translate to broader workforce transformation. Less than half of financial services leaders believe their workforce is moderately (39% agreeing) to well-adapted (7%) for the future, and only 52% express confidence in their organization’s ability to effectively transform its workforce to keep pace with changing needs (Figure 2).

Figure 2: Leadership readiness for workforce transformation in financial services

_{Source: Russell Reynolds Associates’ H2 2024 Global Leadership Monitor, n = 312 Financial Services CEOs, C-level leaders, and next generation leaders}

This misalignment points to potential gaps between ongoing GenAI initiatives and the functions where transformation is most needed. Indeed, 88% of leaders acknowledge that senior leadership must evolve, and 15% believe their leadership teams require a complete overhaul (Figure 3). Corporate functions are even more in need: 91% of leaders say some level of transformation is required.

Without targeted skills, mindset, and training interventions, organizations risk underperforming despite AI investments. Closing this gap requires focused upskilling, reskilling, and a culture of adaptability.

Figure 3: Functions in financial services where transformation is needed, by segment
% of financial services leaders selecting complete or some transformation needed

_{Source: Russell Reynolds Associates’ H2 2024 Global Leadership Monitor, n = 312 Financial Services CEOs, C-level leaders, and next generation leaders}

The functional leaders driving effective workforce transformation exhibit distinct competencies that balance innovation with risk

AI adoption is reshaping corporate functions in financial services – from finance and risk to technology, legal, and human resources. Leaders report tangible benefits: 57% note improved productivity, 57% expanded capabilities, and 41% enhanced internal process quality from AI initiatives (Figure 4).

Figure 4: AI-driven organizational impacts today in financial services
% of financial services leaders reporting AI-driven increases / decreases on the following

_{Source: Russell Reynolds Associates’ H1 2025 Global Leadership Monitor, n = 283 Financial Services CEOs, C-level leaders, and next generation leaders}

Yet, these gains are tempered by real concerns, ranging from threats to product and process quality, to the deeper risk of eroding critical thinking and judgment. In fact, 59% of financial services leaders worry that over-reliance on AI could diminish the essential skills and judgment on which their organizations rely (Figure 5).

Figure 5: Financial services leaders’ concerns about AI’s long-term organizational impacts by GenAI implementation stage

_{Source: Russell Reynolds Associates’ H1 2025 Global Leadership Monitor, n = 312 Financial Services CEOs, C-level leaders, and next generation leaders}

Against this backdrop, the functional leaders driving effective workforce transformation in financial services consistently demonstrate four key competencies, that enable them to harness innovation while proactively managing risk:

1. Perpetual adaptability: Thriving in ambiguity and rapid change, guiding teams through evolving regulations and business models, while fostering workforce resilience through the transformation journey.
   
   
2. Data fluency: Translating vast AI-generated data into actionable insights, while recognizing biases and limitations, ensuring that decision making remains sound and human-centered.
   
   
3. High learning quotient: By fostering a culture of continuous learning and experimentation, high-impact functional leaders accelerate critical thinking ability across their workforce.
   
   
4. Culture drivers: Shaping a resilient, engaged workforce by promoting transparent communication and reinforcing the value of human insight alongside technological innovation.

By demonstrating these competencies, financial services functional leaders capitalize on the opportunities AI presents while protecting their organizations from potential risks. This balanced approach creates a foundation for the sustained development of professional judgment.

Financial services leaders are redefining workforce transformation by coupling AI ambition with professional judgment

As AI adoption grows more ubiquitous, leaders are increasingly concerned about the erosion of critical thinking amid accelerated AI adoption.

Historically, next-gen leaders developed professional judgment through foundational analysis and routine tasks. But now, much of this sense-making work is being automated. Recent studies indicate that when individuals rely heavily on AI for generative thinking, their neural engagement decreases, resulting in lower retention rates. If next-gen leadership pipelines bypass these cognitively essential steps, we risk cultivating leaders whose fluency is artificially generated, rather than genuinely developed.

To ensure that AI-driven workforce transformation endures without impacting individuals’ professional judgement, financial services organizations should focus on four interconnected strategies:

1. Look for and elevate leaders with a strong set of growth factors and enterprise thinking: Identify and develop leaders who demonstrate systems thinking, adaptability, resilience, and social intelligence, grounded in self-awareness and purpose. In financial services, where specialization has been prioritized since the Global Financial Crisis, it’s vital to elevate those with broad networks and enterprise thinking. By fostering leaders with these qualities, organizations can drive transformation while preserving the human-first aspects that make them unique.
   
   
2. Develop next-generation talent through immersive, scenario-based training: Targeted development programs should combine technical upskilling with mentorship, real-world assignments, and exposure to complex challenges to build future-ready leaders. This experiential approach develops future leaders who are not only proficient with AI, but also possess the judgment, agility, and critical thinking required to thrive in ambiguous and rapidly changing environments.
   
   
3. Cultivate a learning-driven and collaborative culture: Organizations that succeed foster environments where learning, open dialogue, and cross-functional collaboration are part of everyday work. They encourage teams to challenge assumptions, share insights, experiment and  remain agile – ensuring that professional judgment and human capability evolve in lockstep with technological advances.
   
   
4. Complement AI investment with organizational re-design to maximize impact: To fully realize the potential of AI-driven transformation, financial services organizations must augment their investment in AI with organizational re-design. Thoughtful organizational design determines how technology is integrated, clarifies roles, and ensures human expertise remains central to decision-making. This approach enables technology to enhance — rather than replace — professional judgment, promoting impactful, ethical, and sustainable decisions across the organization.

Transformation endures only when people, organizational programming and structures, and cultures evolve alongside technology. The financial institutions that champion the human element of change will define and lead the future. Now is the time to ensure that AI-driven workforce transformation is built to last.

Authors

Nicholas Anderson is a senior member of Russell Reynolds Associates’ Leadership Advisory group. He is based in Hong Kong.
Chris Davis co-leads Russell Reynolds Associates’ global FinTech Practice. He is based in New York.
Amelia Stubbs leads Russell Reynolds Associates’ global Risk, Regulation, and Controls Practice across Financial Services. She is based in London.
Jerwin Antony is a member of Russell Reynolds Associates’ Financial Services Commercial Strategy & Insights team. He is based in Singapore.
James Baek is a member of Russell Reynolds Associates’ Financial Services Commercial Strategy & Insights team. He is based in New York.
Cem Turan leads Russell Reynolds Associates’ Financial Services Commercial Strategy & Insights team. He is based in London.