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How can banks close the AI talent gap?

Tuesday, July 16, 2024

15:00-16:00 BST / 10:00-11:00 EDT

Virtual Roundtable

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Katherine Savage

Partner, People Advisory Services; EMEIA Reward Sustainability Advisor, EY

Katherine is a leader in EY’s People Advisory Services practice. She has extensive experience in creating effective reward and HR strategies across leading Financial Services global organizations. A large proportion of her career has been spent within emerging markets and organizations in periods of unprecedented change and crisis management; focused on building out HR functions, establishing governance controls, achieving cost and total reward optimization and regulatory alignment.

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Noémie Ellezam

Global Head of Artificial Intelligence, Société Générale

Noémie has fifteen years of experience Business transformation and Financial services (retail & consumer finance, wealth management, corporate & investment banking). She joined Société Générale in 2006 in General Inspection, and led international strategic reviews & business transformation projects across multiple businesses & geographies, before being promoted Head the Strategic & performance steering division for French retail from 2014 to 2018.

Alexandra Mousavizadeh

Co-founder & Co-CEO, Evident

Alexandra has spent the last 25 years ranking and quantifying complex societal and political forces. She started her career at Moody’s, then Morgan Stanley, later became CEO of ARC Ratings and then Director of the Prosperity Index. Most recently, Alexandra was a Founding Partner at Tortoise Media, where she ran Tortoise Intelligence, the Index and data business. Here, she was the architect of the groundbreaking Global AI Index, the first benchmark to track the strength of national AI ecosystems. She holds a degree in economics, mathematics and game theory from the University of Copenhagen.

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Colin Gilbert

VP of Intelligence, Evident

Colin leads Evident's Intelligence Team. focused on developing new content offerings and expanding our customer-facing diagnostics. Colin has spent the last 15 years working in Research & Advisory services, specializing in using quantitative benchmarking to measure an organization's digital aptitude vs. performance. Previously, he served as a Managing Vice President at L2 Inc. (acquired by Gartner in 2017), where he worked on the Digital IQ Index® as it expanded to cover nearly 1,500 leading brands across 15x B2C industries.

Watch the full Roundtable here:

In this roundtable, we explored: What AI talent is critical to executing a bank's AI strategy? What banks are doing to develop their existing talent capability? Where banks currently stand in the race to recruit and retain the best and brightest in a highly competitive marketplace? And what role can external partners play in building capability in the short- and long-term?

We dived into the latest data and trends from Evident’s AI Talent Report and focused on practical insights from leading subject matter experts and industry practitioners.

Over the past six months, the overall pool of AI talent across the 50 banks in the Evident AI Index increased by 9%, double the rate of growth in overall headcount. And, in the last quarter alone, we've seen a 25% quarter-on-quarter increase in AI Development job listings.

But all banks are not growing equally. The recent growth in AI Development roles has primarily been driven by the US banks. And the most AI mature banks - the banks that already lead the way in the Evident AI Index ranking - appear to be accelerating their hiring efforts and pulling away from the pack.

Key slides:

Table defining AI and technology talent. It categorizes capabilities like AI Development, Model Risk, Data Engineering, and AI-focused Implementation, providing a definition for each and listing top job profiles such as Data Scientist, ML Engineer, Model Risk Analyst, Data Engineer, Software Engineer, and AI Product Manager.

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Presentation slide titled 'Deep Dive on AI Talent Capability'. The left side features a scatter plot charting 'AI Talent Volume vs. Absolute Change, by Bank' from September 2023 to March 2024, showing various banks' positions, with JPMorgan Chase as a top outlier in both volume and change. The right side displays a quote from Prem Natarajan, Chief Scientist & Head of Enterprise AI & Data at Capital One, emphasizing that 'One of the great challenges of our time is the state of readiness of many enterprises to harness the latest advances in AI – whether it is the sophistication of their data operation, the modernity of their tech stack, or the quality of their tech talent. Many companies are realising they don’t have their data act together.' A small headshot of Prem Natarajan is included.

Dashboard slide titled 'Interim Update on Key Metrics (March 2024) - AI Development'. Features three charts: a scatter plot on 'Reliance on Specified Talent Source, Relative to Index Average' for AI hires in banks, showing different sectors and types of hirers; a bar chart detailing 'Previous Experience of AI Talent Joining Banks' by category (new graduates, lateral hires, experienced hires); and another bar chart identifying 'Top 10 Sources of AI Talent, Excluding Universities' by company, including IBM, Accenture, and others.

4 Priority Areas of Talent Development are listed: Long-term workforce planning, Group-wide onboarding for technical talent (Builders), Upskilling and educating both Leaders and Users, and Balancing central coordination with decentralized training. Below, two quotes: Amanda Miller, Director, Brand & Marketing at Capital One, states, 'We think it’s important to work with a wide range of business partners to understand not just who is needed today to fill this role, but how to think about that future talent profile, and making sure that we’re bringing in the right talent who have the skills and experiences that ultimately will help deliver on future goals.' Ian Glasner, Head of Venture Investment, Innovation, and Digital Partnerships at HSBC, states, 'AI training can’t be one-size-fits-all, especially at an international bank like HSBC. We invest in both global training and more tailored training paths for four broad groups of employees: senior leaders, AI technologists, AI product owners and non-specialists who are learning about AI.'