The AI Imperative in Financial Services – The Human Capital Agenda

Leadership StrategiesTechnology and InnovationTransformation InnovationFinancial ServicesTechnologyHuman ResourcesTechnology, Data, and DigitalLegal, Risk, and ComplianceExecutive Search
記事アイコン Report
9月 26, 2023
4 記事アイコン
Leadership StrategiesTechnology and InnovationTransformation InnovationFinancial ServicesTechnologyHuman ResourcesTechnology, Data, and DigitalLegal, Risk, and ComplianceExecutive Search
EXECUTIVE SUMMARY
AI adoption in financial services is less about technology and more about leadership. Is your team ready for the impending transformation?
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With $25 trillion in potential economic impact, generative artificial intelligence (AI) has captured our attention and imagination. Our 2023 Global Leadership Monitor research reveals that 74% of CEOs believe their industry is currently being disrupted by technology, as generative AI ushers in a new era of talent, transformation, and culture of ethical human leadership.

To understand the impact of generative AI on talent strategies across financial services, Russell Reynolds Associates connected with over 50 HR executives across the ecosystem. The insights gathered revealed a clear message: AI's influence on the financial services industry goes beyond technology—it's about leadership.

Our observations indicate that every leader, starting with the CEO, must take ownership of driving the AI agenda. In this period of technological evolution, leaders who embrace AI will be better equipped to navigate disruption and uncertainty. However, financial services leaders are likely to find themselves faced with the challenge of balancing the associated risks with rewards while shaping their AI adoption strategies. The way leaders position their organizations in this context will therefore vary, ranging from being innovators, early adopters, or fast followers to late adopters.

 

Changing landscape of AI use-cases and organizational design

Embedding AI into your organization requires a harmonized and holistic approach. Given the wide range of current, planned, and promising use cases for AI in financial services (see Figure 1), leaders need to make coordinated decisions on high value opportunities to ensure a competitive edge. While downside protection against competitive threats, cyber breaches, and industry disruption is top of mind, the upside potential is extraordinary. The good news: your organization does not need to excel in every area. Your approach depends on your organization’s strategic priorities and corresponding use cases, the cost-benefit across all functions, and existing cultural and leadership dynamics.

 

Figure 1: Current and planned usage of AI use-cases in financial services

Current and planned usage of AI use-cases in financial services

Source: “Banking on a game changer: AI in financial services,” The Economist Intelligence Unit.

 

The evolution of AI organizational design is intricately linked to your business strategy. Our market analysis and client interactions reveal that AI is nested where the financial institutions are most invested. We observed three nascent and evolving constructs with varying degrees of centralization in financial services as outlined below (see Figure 2):

AI is decentralized and embedded in the digital/customer experience (CX) organization

Pros – Creates distinctive focus on customer-facing use cases and promotes strong collaboration between technology and lines-of-business partners

Cons – May overlook or deprioritize promising non-CX related AI use cases, such as back-end IT operations

AI is bifurcated into two groups; one focused on AI research, the other on AI implementation

Pros – Ensures clear decision rights around idea generation vs. implementation, which can promote innovation and speed to market

Cons – If not well aligned, the AI research group can lose sight of key implementation challenges/constraints and run the risk of chasing ‘shiny objects’ 

AI is centralized with a Center of Excellence (CoE) coordinated under a chief technology officer/head of innovation

Pros – Strongly promotes enterprise-wide synergies, organizational alignment, and AI governance best practices

Cons – Runs the risk of becoming overly bureaucratic, slowing speed to market

 

Figure 2: AI organizational structures across financial institutions

AI organizational structures across financial institutions

Source: Proprietary research on organizational structures, Russell Reynolds Associates, 2023.

 

When scaling AI, focus on leadership and talent implications

AI is the new battleground for talent in financial services – it’s both an arms race and a war of attrition. Banks are jostling to attract AI talent; at the most enthusiastic banks, about 40% of all open roles are for AI-related hires, including data engineers and quants, as well as ethics and governance roles (see Figure 3).

 

Figure 3: Available AI roles in banking

Available AI roles in banking

Source: “Wall Street Banks Are Using AI to Rewire the World of Finance,” Bloomberg, 2023.

 

It’s important to ensure your leaders have the necessary AI knowledge, as well as the ability to galvanize the organization around a culture of ethical, human-centered innovation. Drawing from our market insights, we have observed four distinct profiles emerging across financial services (Figure 4).

 

Figure 4: AI leadership archetypes across financial services

AI leadership archetypes across financial services

Source: Russell Reynolds Associates, 2023.

However, acquiring talent is only part of the battle, and research shows that financial services firms need to improve retention, especially in the face of fierce competition from other industries. On average, for every AI employee a financial institution hires, it loses one during the same period. What's more, nearly 80% of those employees leave the financial services industry entirely (see Figure 5). Addressing the risk of a leaky AI talent pipeline requires leadership to effectively manage organizational ambiguity and complexity, acknowledging the inevitable uncertainty associated with AI.

 

Figure 5: Leaky AI talent pipeline

Leaky AI talent pipeline

Source: “Wall Street Banks Are Using AI to Rewire the World of Finance,” Bloomberg, 2023.

 

Planning for the future: key human capital questions to shape AI adoption

We are already seeing financial institutions start to make bold moves. A leading global investment bank is educating the entire organization on AI through an interdisciplinary team of ethicists, while simultaneously adapting and leveraging AI models to improve trading optimization, portfolio construction, and risk assessments.

Organizations should employ a multi-dimensional approach to best harness the power of AI. Below questions can offer leadership teams guidance from a human capital perspective (see Figure 6):

 

Figure 6: Key human capital questions shaping AI adoption

Key human capital questions shaping AI adoption

 

The approach and solutions will be unique to each organization's needs. Perspectives and frameworks in this paper are intended to help financial services leaders determine the best AI strategy for their organizations. While there are still unknowns surrounding AI, it is imperative for financial services leadership to take action now—leading with human creativity, balanced judgment, and strategic thinking to shape a future that is both technologically advanced and human-centric.

 


 

Authors

  • James Baek is a member of Russell Reynolds Associates’ Financial Services knowledge team. He is based in New York.
  • Chris Davis co-leads Russell Reynolds Associates’ global FinTech Practice. He is based in New York.
  • Cem Turan leads Russell Reynolds Associates’ Financial Services knowledge team. He is based in London.
  • Robert Voth co-leads Russell Reynolds Associates’ global Consumer & Commercial Financial Services Practice. He is based in Chicago.

 

 

 

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The AI Imperative in Financial Services – The Human Capital Agenda