How to Attract, Grow, and Retain AI Talent

Key Insights on Attracting and Retaining AI Talent

The demand for AI professionals has reached unprecedented levels, yet the available talent pool is notably sparse. To effectively attract and retain these highly sought-after employees, companies must focus on four key areas:

• Prioritize acquiring specific skills over predefined roles.

• Understand the desires of AI professionals and uncover hidden talent pools.

• Present a clear and compelling career path for AI employees.

• Integrate AI talent seamlessly within the organization.

By grasping the distinct needs of AI talent and offering a robust employee value proposition, organizations can secure a sustainable competitive edge in the AI space.

The 10-20-70 Rule for AI Success

Leading companies leveraging AI often adhere to the 10-20-70 rule:

• 10% of their AI focus is on algorithm design.

• 20% is dedicated to building foundational technologies.

• 70% is centered around empowering people and reshaping business processes.

Achieving maximum value from AI requires addressing three critical questions:

1. How can I attract, nurture, and retain data and analytics talent to build lasting AI capabilities?

2. How can I rapidly scale AI solutions to drive meaningful business transformation?

3. How do I restructure my organization to fully capitalize on AI at scale?

This article, the first in a three-part series, delves into the initial challenge: how to attract, develop, and retain AI talent.

The Urgency for a Strategic AI Talent Approach

Artificial intelligence is currently in the spotlight, with advancements like ChatGPT, AI-powered Bing, and Google Bard dominating the discourse on AI’s revolutionary potential. To maintain leadership in the next five years, organizations need a well-defined AI talent strategy today. However, many are hitting a wall. While demand for AI talent is at an all-time high, the limited supply forces companies to distinguish themselves amidst fierce competition.

AI Talent is Not Business as Usual

The approach to acquiring and retaining AI talent must differ from conventional methods. Companies need to present a distinct and appealing value proposition to attract—and keep—top AI recruits. Rather than merely filling job openings, companies should:

• Focus on the skills required.

• Understand what AI professionals are looking for.

• Invest in reskilling and advancement opportunities.

• Keep AI talent deeply engaged within the organization.

Common Pitfalls in AI Recruitment

Despite the growing need for AI and machine learning professionals, businesses often stumble in their recruitment efforts. Mistakes such as these are common:

• Competing head-to-head with tech giants without emphasizing non-tech-related advantages.

• Relying on slow, generic recruitment processes.

• Paying top dollar for cutting-edge data scientists without considering the broader skill set required.

• Onboarding AI talent without fostering community or embedding them under AI-knowledgeable leaders.

• Failing to offer clear career advancement opportunities.

• Neglecting reskilling efforts within the organization.

These missteps not only hinder companies from attracting top talent but also lead to high attrition rates, a serious concern in today’s job market. Fortunately, recruiting AI talent doesn’t have to result in a bidding war. By understanding what drives AI professionals, companies can build a more compelling offer.

Four Strategies for Building an AI Advantage

To develop and retain top AI talent, organizations must excel in four key areas:

• Anticipate talent needs

• Attract best-in-class candidates

• Develop talent quickly

• Engage talent with a compelling value proposition

Anticipate: Building an Effective AI Workforce

Hiring for an AI transformation involves more than just securing data scientists. It requires a diverse skill set, including data architects, solution architects, software engineers, and data governance experts. Companies should:

• Develop a clear skills taxonomy.

• Focus on acquiring the necessary skills rather than predefined roles.

• Structure AI teams to foster collaboration and innovation.

Additionally, as AI talent becomes embedded within business processes, companies must anticipate how this will impact the broader workforce, likely requiring upskilling and process adjustments.

Attract: Standing Out in a Competitive Market

In the race for AI talent, companies must take proactive steps:

• Understand what AI workers want: AI professionals value opportunities to work on cutting-edge projects and seek clear career progression. Companies must communicate their data strategy and advancement paths effectively.

• Look for untapped talent: Secondary markets offer extraordinary talent at lower costs. Remote work further expands talent pools, providing flexibility and access to talent across borders.

• Tailor recruitment to maturity: From anchoring hires with key AI experts to leveraging specialized recruiters, companies should adjust their approach based on their AI maturity level.

• Streamline the recruiting process: Timely, efficient recruitment processes are vital to securing top talent.

Develop: Nurturing AI Talent from Within

Retention challenges often stem from a lack of career advancement opportunities. However, reskilling existing employees presents a solution. These individuals are already familiar with the organization’s values and can quickly contribute to AI efforts. By fostering internal mobility, companies can:

• Boost job satisfaction.

• Strengthen loyalty.

• Increase retention.

For new recruits, companies must define clear career paths and promote employees at a rate that matches the tech industry’s faster advancement timelines.

Engage: Keeping AI Talent Invested

Companies that aren’t tech-first often struggle to keep AI talent engaged, especially if their product development cycles are long. To overcome this:

• Articulate a strong purpose: Companies need to emphasize their unique mission and differentiate themselves from traditional tech giants.

• Embed AI talent within the organization: AI employees should be integrated into the organization through a structured onboarding process and impactful, quick-win projects.

Case Study: Rapid AI Expansion in Biopharma

One leading biopharma firm offers a prime example of these principles in action. The company:

• Reshaped job architecture to focus on skills over roles.

• Created stronger communities of practice for AI talent.

• Refined its recruitment strategy and established a specialized team of AI recruiters.

In just six months, the firm increased its AI workforce by 10% in drug discovery and reduced attrition in its data and analytics teams.

Conclusion: Securing a Long-Term AI Advantage

Talent scarcity is a major concern for executives worldwide, but this trend is changing as companies refine their AI strategies. By adopting a thoughtful approach to AI recruitment, development, and engagement, organizations can secure a long-term advantage in a field that’s reshaping the future of business.