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Posts from the ‘AI for Human Resources Management’ Category

What’s Next For You? How AI Is Transforming Talent Management

Bottom Line: Taking on the talent crisis with greater intelligence and insight, delivering a consistently excellent candidate experience, and making diversity and inclusion a part of their DNA differentiates growing businesses who are attracting and retaining employees. The book What’s Next For You? by Ashutosh Garg, CEO and Co-Founder and Kamal Ahluwalia, President of eightfold.ai provide valuable insights and a data-driven roadmap of how AI is helping to solve the talent crisis for any business.

The Talent Crisis Is Real

  • 78% of CEOs and Chief Human Resource Officers (CHROs) say talent programs are important, with 56% say their current programs are ineffective.
  • 83% of employees want a new job yet only 53% want to leave for a new company.
  • 57% of employees say diversity and inclusion initiatives aren’t working, and 40% say their companies lack qualified diverse talent.
  • Nearly 50% of an organizations’ top talent will leave their jobs in the first two years of being hired.
  • 28% of open positions today won’t be filled in the next 12 months.

The above findings are just a sample of the depth of data-driven content and roadmap the book What’s Next For You? delivers. Co-authors Ashutosh Garg’s and Kamal Ahluwalia’s expertise in applying AI and machine learning to talent management problems with a strong data-first mindset is evident throughout the book. What makes the book noteworthy is how the authors write from the heart first with empathy for applicants and hiring managers, supporting key points with data. The empathetic, data-driven tone of the book makes the talent crisis relatable while also illustrating how AI can help any business make better talent management decisions.

“Businesses are having to adapt to technology changes and changes in customer expectations roughly every 10 years – a timeframe that is continuing to shrink. As a result, business leaders need to really focus on rethinking their business strategy and the associated talent strategy, so they have the organizational capability to transform and capitalize on the inevitable technology shifts,” writes John Thompson, Venture Partner, Lightspeed Venture Partners and Chairman of the Board at Microsoft in the forward.

The book cites talent management researchers and experts who say “our current knowledge base has a half-life of about two years, and the speed of technology is outperforming us as humans because of what it can do quickly and effectively“ (p.64). John Thompson’s observations in the forward that the time available for adapting to change is shrinking is a unifying thread that ties this book together. One of the most convincing is the fact that using today’s Applicant Tracking Systems (ATS) and hiring processes prone to biases, there’s a 30% chance a new hire will not make it through their first year. If the new hire is a cloud computing professional, this equates to a median salary of $146,350 and taking best-case 46 days to find their replacement. The cost and time loss of losing just one recruited cloud computing professional can derail a project for months. It will cost at least $219,000 or more to replace just that one engineer. Any manager who has lost a new hire within a year can relate to how real the talent crisis is and how urgent it is to solve it.

The Half-Life Of Skills Is Shrinking Fast

The most compelling chapter of the book illustrates how today’s talent crisis can be solved by taking an AI-enabled approach to every aspect of talent management. Chapter 4, The Half-Life Of Skills Is Shrinking Fast, delves into how AI can find candidates who can unlearn old concepts, and quickly master new ones. The book calls out this attribute of any potential new hire as being essential for them to adapt.  Using higher quality data than is available in traditional ATS systems, the authors illustrate how AI-based systems can be used for evaluating both the potential and experiences of applicants to match them with positions they will excel in. The authors make a convincing argument that AI can increase the probability of new candidate success. They cite a well-known Leadership IQ statistic of 46% of all new employee hires failing to adapt within 18 months, and the Harvard Business Review study finding between 40% to 60% of new upper management hires fail within 18 months. The authors contend that even Leonardo Da Vinci, one of the primary architects of the Renaissance, would have trouble finding work using a traditional resume entered into an ATS system today because his exceptional capabilities and potential would have never been discovered. When our existing process of recruiting is based on practices over 500 years old, as this copy of Leonardo Da Vinci’s resume illustrates, it’s time to put AI to work matching peoples’ potential with unique position requirements.

When Employees Achieve Their Potential, Companies Do Too   

Attracting the highest potential employees possible and retaining them is the cornerstone of any digital business’ growth strategy today and in the future. The book addresses the roadblocks companies face in attaining that goal, with bias being one of the strongest. “For example, McKinsey & Co., a top consulting agency, studied over 1,000 companies across 12 countries and found that firms in the top quartile of gender diversity were a fifth more likely to have above-average profits than those in the bottom quartile,” (p. 105). Further, “diverse executive boards generate better financial returns, and gender-diverse teams are more creative, more productive and more confident.” (p. 105).

In conclusion, consider this book a roadmap of how hiring and talent management can change for the better based on AI. The authors successfully illustrate how combining talent, personalization at scale, and machine learning can help employees achieve their potential, enabling companies to achieve theirs in the process.

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