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The gaps and limitations of applicant tracking systems (ATSs) and recruiting management systems (RMSs) are driving the development of new AI-infused approaches to modern talent management. Lessons learned from ATS and RTS limitations form the basis for new kinds of talent management platforms and systems at the same time as labor shortages surface in the wake of COVID-19.

But, while AI-based platforms are essential to new styles of talent management, their implementation is a matter of no small concern.

This was driven home by a recent study by Harvard Business School (HBS) and Accenture that found over 10 million workers are excluded from consideration due to the way ATSs are wired. The study, “Hidden Workers: Untapped Talent,” finds that inflexibly configured ATSs and RMSs completely miss qualified workers. Making matters worse, 90% of companies rely on ATS and RTS alone to screen for middle-skill and high-skill candidates.

According to a recent Wall Street Journal story, current talent tracking systems are working more or less as designed, screening millions of resumes on keywords and phrases that match job descriptions but leaving many capable applicants out.


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And this is not the sole challenge to responsible talent management strategy. While outside job applicants may be mistakenly overlooked, the same may be true for existing staff — people who are capable of helping in new positions, but who are filtered out from consideration.

Still, augmenting ATS and RMS with an AI-based platform approach to talent management is seeing accelerating adoption across enterprises. Hiring on capabilities is proving to deliver better business performance gains, according to many customer presentations at Cultivate ’21, a recent user conference hosted by, maker of the Talent Intelligence Platform tool.

Talent mobility dominated sessions and discussions at Cultivate. It is clear organizations are turning to AI and machine learning for new insights into closing talent gaps and managing upskilling and reskilling more effectively.

How AI is used in hiring

Just ahead of Cultivate ’21, reported results of the survey “HR’s Future State Report 2021: The Impact of Artificial Intelligence on Talent Processes.” This and the summit together provided a candid, pragmatic look at where AI is transforming the nature of work and what needs to improve. The following are key insights from the survey.

Improving candidate experience

The two leading uses of AI in hiring and recruiting are

  • finding the best possible candidates by filtering on innate skills and capabilities, and
  • improving candidate experiences.

Eightfold’s survey finds that most HR leaders in enterprises first rely on AI to improve candidate filtering based on their potential, capabilities, learnability, fit for a role, and likelihood to succeed. The goal is answering the question of what the next best position for the candidate is. This technique goes far beyond the keyword-matching approach of existing ATS and RMS platforms.

HR teams also rely on AI to create positive candidate experiences through chatbots and self-service systems. Matt Hill, director of talent acquisition at Dexcom, explained at the Cultivate ’21 Summit that AI technology streamlines the company’s recruiting process by finding the most qualified candidates for positions. One way it does this is by helping candidates quickly identify positions they are most qualified for and auto-populating work experiences for them in their applications. As a result of these efficiencies, the company has seen a 40% conversion of website visitors into unique applicants.

Increasing contextual intelligence

Achieving greater efficiency and scale is the most significant benefit HR teams say AI provides today.  AI also enables companies to reduce turnover because it allows them to build employee career paths and present growth opportunities. When internal mobility is high and turnover is low, HR teams can focus their time and resources on scaling the organization. That is a key benefit identified by survey respondents.

Another significant benefit is that technology and humans perform better in combination than they do working alone, a key point made in the recent Harvard Business Review article “Why AI Will Never Replace Managers.” AI can’t solve all the problems HR faces; however, it can provide contextual data and intelligence to help reframe a problem, so HR teams know what needs to be solved. Contextual intelligence is the goal, with AI supporting HR teams’ experience, insights, and intuition.

Streamlining hiring processes

About 57% of HR teams are currently using AI-related tools to manage workforces and hiring processes. In addition, the survey found that, through AI-powered tech stacks, HR teams are streamlining parts of the recruiting, hiring, and onboarding processes, with a high priority placed on creating positive candidate experiences.

Similarly, HBS and Accenture’s study on Hidden Workers emphasizes the need for HR teams to take a customer experience mindset in designing recruitment and onboarding processes. “AI is how we lead,” says Diane Gherson, former chief HR officer for IBM and current Harvard Business School faculty member. IBM relies on AI in HR to achieve various outcomes, including more personalized experiences for employees, positive chatbot interactions, accurate skills inferences for workforce management, and improved productivity for HR team members.

Transforming corporate culture

Nearly 82% of enterprise HR teams plan to adopt more AI tools in five years. Enterprise customers presenting at Eightfold’s Cultivate ’21 Summit reinforced this finding with the AI and talent transformation roadmaps they referenced during the virtual event.

Bayer’s Bijoy Sagar, EVP and chief IT and digital transformation officer, and Holly Quincey, global head of talent acquisition and HR, discussed the essential role of AI in their talent transformation initiatives, including unleashing the potential of Bayer’s Employee Entrepreneurs program. In addition, Jolen Anderson, global head of human resources at BNY Mellon, shared how AI is helping to bring greater scale to diversity and inclusion efforts company-wide, helping to create a foundation for changing corporate culture.

Cultivate shows AI is high priority’s Cultivate ’21 Talent Summit provided a series of insights that create a strong case for how AI and machine learning can help enterprises improve talent management. Bayer, Dexcom, Ericsson, Micron Technology, Nationwide, Prudential, and Tata Communications were a few of the customers who shared the results they achieved using Eightfold’s Talent Intelligence Platform and their plans for the future. According to Kamal Ahluwalia, Eightfold’s president, the company has grown to serve customers on four continents, 110 countries, and over 15 languages since 2018.

The summit’s two days of customer interviews provided insights into how Eightfold is helping enterprises take a data-driven approach to solving their most challenging problems using AI, machine learning, and neural networks.  A replay of all the sessions is available online, and together they provide a glimpse into how enterprises are getting results from their AI strategies.

Enterprises emphasize talent mobility

Talent mobility, diversity, equity and inclusion, talent acquisition, talent management, and governance were the leading topics covered in the 33 sessions. Based on customer presentations, it’s clear Eightfold is concentrating on helping their customers accelerate and improve talent acquisition. Customers including Dexcom and Micron explained how they’re relying on Eightfold for each stage of talent acquisition, including sourcing, screening, interview scheduling, diversity hiring, candidate experience, candidate relationship management, and on-campus hiring.

Talent mobility dominated many of the sessions and discussions at the event. By definition, talent mobility relies on a company’s current employees to meet current and future talent needs through reskilling and redeployment across the organization. Eightfold’s approach to talent mobility uses algorithms to identify and match open positions to provide internal employees with work that best matches their innate capabilities and skills.  The data needed to train and fine-tune predictive models based on employees’ innate capabilities and skills are currently available, yet scattered across enterprise HR systems and external sources.

Eightfold looks to solve this challenge by integrating public sources and global data sets with HR systems to identify a candidate’s potential, capabilities, learnability, fit for a role, and likelihood to succeed. Sachit Kamat, chief product officer, provided an overview of the Eightfold Deep Learning AI architecture as part of his roadmap presentation. Central to this is Eightfold’s use of neural-network-based deep learning able to learn from 1-billion-plus profiles, billions of global data points, and over 1 million unique skills to deliver what the company says are bias-free, data-driven insights.

Above: Eightfold’s neural networks learn from more than a billion profiles, billions of global data points, and over a million unique skills.

Systems that improve talent mobility can open possibilities for workers and organizations alike, according to Betsy Summers, principal analyst for future of work and HCM at Forrester. Summers provided an insightful presentation that included an excellent analysis of talent mobility and the role of talent marketplaces at Eightfold’s event.

Her presentation, “Future-Fit Talent Mobility and Talent Marketplaces,” explained the measurable benefits of talent mobility and talent marketplaces. Organizations that adopt talent mobility initiatives internally find that retention increases, costs to fill roles versus external hires drop, and the quality of hires increases, she said.

She also pointed out that providing employees with career planning improves employee experiences and long-term retention.

“Artificial intelligence itself helps enable scalability, diversity and inclusion, and adoption because you can reduce the manual effort required by all employees … by proactively suggesting matches across the pool. So imagine what you could unlock in terms of employee potential and employee experience by harnessing AI to help do that work for you,” she told event attendees.

Above: Forrester analyst Betsy Summers outlines the benefits of talent mobility in the face of labor shortages

AI in talent management

Three principles guide Eightfold’s product strategy and ongoing investment:

  1. Enable organizations to use AI for efficient hiring at scale.
  2. Power mission-critical use cases for customers.
  3. Allow effective career transformations for all.

At the company’s event, Sachit Kamat, Eightfold’s chief product officer, presented the Eightfold Product Vision & Roadmap, highlighted by these features:

  • App marketplace: The App Marketplace is designed to provide customers with the opportunity to create and share apps tailored to specific use cases and requirements across their organizations at scale. Today, there are 30 third-party apps on the Marketplace, and Kamat demonstrated how GitHub and Slack integrations are ready today.
  • Expanded career hub with talent mobility improvements: In response to customers’ requests for greater talent mobility support, Eightfold launched an enhanced personalization and career navigation experience that provides employees the ability to explore other career options with their current employer. Eightfold also demonstrated a mobile app interface to the new career hub, allowing employees to review and consider career options on their own time.
  • New interview scheduling and feedback tools: Looking to replace the repetitive, manual tasks of recruiters and free up their time to find more qualified candidates, Eightfold announced a new set of tools for automating the interview scheduling and feedback process.
  • Updated Eightfold career site: Eightfold’s well-known career site, in use across multiple industries, added new features that enable hiring organizations to develop and launch marketing programs to build long-term relationships with candidates. What’s unique about the new release is how it provides organizations the flexibility of guiding candidates to fill skills gaps by sponsoring learning content. As a result, when the best possible role is available, the candidates are qualified and ready. The career site also has talent analytics that provides insights into how, where, and when potential candidates visited the career site, indicating their interest in a position.
  • Intelligent platform update for role architectures: Breaking down roles into capabilities and skills is essential for improving talent mobility, ensuring the right fit of candidates with positions, and closing the talent gap. Eightfold announced a new feature that can analyze any role, transforming it into a set of skills and skill proficiencies so candidates can see if they’d be successful in a given role. Eightfold believes this will also help employees determine what’s next for them in regard to capabilities, skill, and long-term learning. Eightfold also announced Talent Flex, a new feature that gives customers the flexibility of sourcing full-time employees and contract workers in a single platform.

Competencies, not credentials

For many organizations, talent mobility is becoming the most reliable strategy for closing the talent gap and staffing positions pivotal to a company’s growth. By using AI and machine learning, organizations can factor in what’s best for a candidate from a skills and capabilities perspective and still meet their talent management needs.

Data-driven approaches to improving every aspect of talent acquisition and management prove the most successful because they simultaneously bring greater personalization for candidates and scale for organizations.

How filters are applied will help determine the future, as AI moves deeper into talent management system operations. For their parts, HBS and Accenture both say hiring companies should shift from negative to affirmative filters in configuring their ATS and RMS, as well as emphasize finding talent within the corporation.

Their study on hidden talent points out that today, “[An] ATS/RMS largely relies on ‘negative’ logic to winnow the applicant pool … [and] most use proxies (such as a college degree or possession of precisely described skills) for attributes such as skills, work ethic, and self-efficacy. Most also use a failure to meet certain criteria (such as a gap in full-time employment) as a basis for excluding a candidate from consideration irrespective of their other qualifications.”

AI-based platforms are essential to improving every aspect of talent management, starting with recruiting, according to HBS and Accenture. But the power of AI will be best harnessed only when companies gain an understanding of “the background of current employees that correlate to their success.”

“That data can then be translated into a new and powerful framework — hiring on the basis of skills and demonstrated competencies, not credentials,” according to the report.

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