The AI Talent Race

In the dynamic world of technology, the race for artificial intelligence (AI) talent has reached unprecedented heights. The launch of ChatGPT by OpenAI in November 2022 marked a turning point moment, transforming the market for AI labour. Zeki Research, a market-intelligence firm, estimates that around 20,000 companies in the West are actively seeking AI experts. Rapid advancements in machine learning and the potential for a "platform shift"—the creation of an entirely new technology layer—have redefined the skills employers demand and the destinations of those who possess them. This has led to a more distributed market for AI talent, previously concentrated in tech giants, but now spreading across a wider array of firms.

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The Quest for Cutting-Edge Skills

Tech giants like Microsoft and Google, despite laying off non-engineers, are in fierce pursuit of star researchers capable of understanding and building state-of-the-art AI models. Entire teams are sometimes acquired en masse, as seen when Microsoft recruited most of the staff of Inflection AI, a startup focused on advanced models, including co-founder Mustafa Suleyman. This aggressive talent acquisition has drawn the attention of regulators.

Mark Zuckerberg, CEO of Meta, has also been actively courting researchers from DeepMind, Google’s AI lab, highlighting the intense competition among tech behemoths for AI luminaries. However, the impact of generative AI on the talent market extends beyond these high-profile hires.

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Generative AI and the Broader Talent Pool

Generative AI, the technology behind ChatGPT, has significantly expanded the demand for AI-related skills among software developers. Data from Indeed shows a 100-fold increase in job listings mentioning generative AI skills since early 2023. Amit Bhatia, co-founder of Datapeople.io, notes that medium-sized tech firms, which once employed a few AI engineers to handle small-scale models, now rely on generative models for superior performance. Consequently, AI engineers are increasingly tasked with integrating AI systems into company data, leading to a surge in demand for "MLops" (machine-learning operations) skills.

Kelsey Szot, co-founder of Adept, emphasises the value of individuals who can quickly learn and apply AI tools to develop innovative solutions. These practitioners, often without traditional academic backgrounds, are essential in the fast-paced world of AI startups, where solving problems quickly is crucial.

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Shifting Talent Flows

The distribution of AI talent is undergoing significant changes. Historically, engineers gravitated towards the big-tech quintet—Alphabet, Amazon, Apple, Meta, and Microsoft. However, since the release of ChatGPT, the net flow of AI workers to these giants has reversed, with a notable outflow observed over the past nine months. While big tech companies continue to add AI talent by poaching from less traditionally prestigious firms like IBM and Oracle, they have not regained their previous net inflows.

Many AI experts are now joining firms like Nvidia, the chipmaker at the forefront of the AI revolution, or mature startups such as Databricks and OpenAI. Notably, one in seven AI workers leaving big tech are joining stealth mode startups, including several authors of the influential 2017 paper "Attention is All You Need," which laid the groundwork for modern generative AI. These moves are driven by financial incentives, the pursuit of meaningful work and the desire for greater autonomy.

Nonetheless, the supply of AI talent is growing, driven by academia and international hiring. According to Stanford University, the percentage of AI PhDs entering industry roles rose from 41% in 2011 to 71% in 2022, with universities offering more AI-related degree programs.

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Reskilling and Upskilling: A Strategic Imperative

As AI and automation reshape industries, companies must adapt by reskilling and upskilling their workforces. Traditionally seen as a way to mitigate layoffs and fulfil social responsibilities, reskilling is now recognised as a strategic imperative. Effective reskilling initiatives allow companies to quickly develop in-house talent and fill critical skill gaps, providing a competitive edge.

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Embracing Reskilling

Several major companies have successfully implemented reskilling programs. Infosys, for instance, has reskilled over 2,000 cybersecurity experts, while Vodafone aims to fill 40% of its software developer roles internally. Amazon's Machine Learning University has transformed thousands of employees into machine learning experts. Given the rapid obsolescence of skills—averaging less than five years—ongoing reskilling is essential.

Reskilling is now part of the employee value proposition at companies like Mahindra & Mahindra, Wipro and Ericsson. These firms provide resources and platforms to facilitate career transitions. Reskilling also enables companies to tap into broader talent pools. ICICI Bank’s academy-like program prepares graduates for managerial roles, while CVS used a similar approach during the COVID-19 pandemic to staff its vaccine and testing services.

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Leadership and Reskilling

Successful reskilling requires a commitment from top leadership. According to BCG, only 24% of companies link reskilling efforts to corporate strategy. At firms like Ericsson, reskilling is integrated into strategic objectives and regularly reviewed by executives. For instance, CVS’s business leaders design and deliver reskilling plans and Amazon highlights reskilling in its leadership manifesto. Such high-level involvement ensures reskilling initiatives align with company goals and achieve scale.

Reskilling resembles a change-management initiative, requiring a conducive organisational context. Employees and managers need to adopt the right mindset and behaviours. BCG data shows that 68% of workers are willing to reskill to remain competitive, highlighting the importance of clear communication and respect.

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Collaborative Reskilling Efforts

Reskilling often involves collaboration with external partners. Industry partnerships, such as the Technology in Finance Immersion Programme in Singapore and the European Union’s Automotive Skills Alliance, can pool resources and knowledge to address common challenges. Partnering with nonprofits and educational institutions can expand access to diverse talent and provide practical technical training. For instance, BMW collaborates with German institutions to support the transition to electric vehicles.

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Upskilling for AI in the Financial Services Sector

The financial services industry is heavily investing in AI technology and must equally invest in talent to leverage AI effectively. Over 95% of firms in a Broadridge study are integrating AI into various business functions, from customer service to risk management. AI and machine learning (ML) have the potential to add up to $4.4 trillion in value annually to the global economy, driving digital transformation across the sector.

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The Digital Transformation Journey

Financial service firms are modernising their technology platforms to support AI integration. Digital leaders in the industry are investing significantly in generative AI (GenAI), setting an example for others. However, even these advanced firms often lack a defined strategy for reskilling their workforce to use AI effectively.

While IT staff such as developers and data engineers are the obvious candidates for upskilling, firms must train employees across all business functions. AI is becoming integral to nearly every role, necessitating widespread AI literacy. Despite recognising the need, only a quarter of firms directly train staff on using GenAI tools.

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Empowering Employees

Firms must help employees understand how AI will transform their roles and workflows. AI applications can automate routine tasks, allowing employees to focus on higher-value activities. For instance, LTX’s BondGPT+ can process vast amounts of market data, freeing up traders’ time for strategic decision-making. Financial service firms should work with employees to maximise the benefits of AI, enhancing both business outcomes and job satisfaction.

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Cultivating Analytical and Critical Thinking Skills

As AI reshapes job requirements, analytical and critical thinking skills will become increasingly important. Large-language models (LLMs) are already enhancing data-driven decision-making. Companies must develop comprehensive upskilling programs that empower employees to leverage these tools effectively.

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The Future of AI Talent and Workforce Transformation

The war for AI talent is reshaping the tech industry, distributing expertise more widely and driving innovation across sectors. As AI continues to evolve, reskilling and upskilling will be critical for maintaining a competitive edge. Companies must adopt strategic reskilling initiatives, supported by leadership and collaborative efforts, to address skill gaps and prepare their workforce for the future.

In the financial services sector, integrating AI into business functions requires significant investment in both technology and talent. Comprehensive upskilling programs will empower employees to harness AI’s full potential, driving business growth and enhancing job satisfaction.

The journey towards an AI-driven future is complex and requires a holistic approach to talent development. By embracing reskilling and upskilling, companies can navigate this transformation successfully, ensuring they remain at the forefront of innovation and competitiveness in the AI era.

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