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Post-Hire Employee Engagement and Workforce Management: Leveraging AI in the Workplace

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(Editor’s Note: The following is an excerpt from “AI and the World of Work: Embracing the Promises and Realities,” a free white paper available on the Allegis Group website that tackles the rise of AI and its influence on workforce strategy and innovation.)

Much of the job of talent acquisition is about establishing a relationship between a company and an employee. Once the offer is made and the candidate accepts, a new journey begins — one that focuses on fulfilling an initial promise of value and growing it over time. It’s about employee engagement, performance management, skills development, and a host of related time- and resource-intensive functions. Moving forward, artificial intelligence (AI) will provide a significant advantage in helping companies to better understand and engage with their workers. AI’s impact will be felt across these key areas of employee experience.

  • Post-Offer Acceptance and New Hire Onboarding: Once a candidate accepts a job offer, an AI could engage and follow up with the candidate to accelerate acceptance and reduce the gap between hiring decision and start date. Following the hire, a candidate undergoes onboarding and orientation. While orientation introduces new hires to company culture, processes, and policies, an AI can fill in the gaps by answering common questions and providing information and resources. Considering that 90 percent of employees forget what was covered in a meeting, training, and conference calls, the information and learning reinforcement of AI can prove valuable.
  • Re-Engagement: Maintaining contact with past candidates can help an organization improve its future talent supply; unfortunately, candidates’ records often go untouched after the job requisition closes. AI can help address this issue by allowing an organization to re-engage a targeted group of candidates to determine their interest in a role while also using the engagement opportunity to keep abreast of new skills or experience the candidate may acquire. By automating this process, AI can remain in contact with past candidates and maintain a potentially valuable portion of the future talent pool.
  • Skills Development: Training can be a key to employee value and retention. Unfortunately, many organizations take a passive approach to administering their programs. A curriculum and resources may be available, but it is often up to the employee to decide whether to use those learning resources. Machine learning computer algorithms could “learn and recommend” when it comes to employee training, helping to understand the employee and push skills development opportunities in a way that is relevant and compelling. This improved communication can lead to higher participation in learning programs, improved return on training investment, and, most importantly, a workforce with growing skills.
  • Career Development: Employees have questions and need support. They may need customized training, learning, and career path information that a boss or leader can’t provide. Along with advanced training and skills development guidance, AI offers the ability to facilitate a more holistic career development, mentorship, and company coaching program.
  • Employee Relations: Some employee questions are simple (e.g., benefits, vacation, and pay) while others are complex and require an in-depth conversation with an HR manager or coordinator. AI technology can be used in chat form, email, or a virtual meeting room, answering many questions, understanding the issue, and, if needed, booking a meeting between HR generalists and employees. Automating this activity can significantly reduce a time-consuming communications burden and allow HR to focus on critical employee interactions.
  • HR Compliance and Case Management: Many case management software solutions provide employees with resources and information based on the questions they send to an email inbox. After that submission, if the resources and information are not clear or helpful, HR and legal resources may become involved in answering those questions. AI opens the door to more advanced functions where incidents are documented and employee investigations are submitted with an automated assistant tool. The tool would ask a series of questions and gather information when a complaint is registered, helping to reduce the need for expensive human interaction early in the case management process.
  • Attrition Mitigation: AI can quickly identify factors affecting high staff turnover. For example, a company’s current pay scale may match the market, but if it veers toward the lower end, the business risks losing talent to competitors. Historical data might also reveal who out of a group of candidates is most likely to remain in the position for the longest time.

These areas of workforce management represent a taste of the challenges and opportunities that AI is poised to address as new solutions enter the market. As with previous waves of innovation, an initial flurry of standalone, niche applications may be followed by increased adoption within larger solutions. If the history of enterprise systems, applicant tracking systems, recruitment marketing, and related technologies are any indication, the pace of change may vary, but the strategic value will continue to grow as AI applications begin to span the multiple functions of HR, from recruiting to compensation and performance management.

Talent Implications, Ethics, and the Forces of Change

The examples of innovations so far show that most solutions are aimed at solving specific challenges in talent management, but on the whole, AI is not limited to a single function. As AI evolves to work across the silos of talent, the solutions will likely grow more impressive.

Imagine a recruiter speaking into a mobile device and saying, “Cortana, I need a data engineer with SQL skills.” What if the program asked more questions about the type of person needed for the job, then looked into its database, found the right person, scheduled an interview, facilitated the selection process, oversaw onboarding, and managed that person’s payroll, benefits, and skills development program? That’s a powerful capability, and it’s one that the larger players in the space are reaching to achieve. The vision is likely part of the reason Microsoft acquired LinkedIn.

Along with its powerful promise, AI also poses ethical questions as pointed out by an active player in the AI space, Shon Burton, CEO and founder of HiringSolved. “AI is good for pattern matching and prediction, but is it ethical to predict race, gender, honesty, intelligence, performance, reliability, or culture fit? ... Imagine how it might be to have to qualify, negotiate pay or communicate healthcare concerns to an AI-based system who all the while is analyzing your interactions with it and using that information to predict your suitability for the role or the lowest salary you are likely to accept.”

While the concerns are real, they also highlight another fact about AI and talent. That is, HR depends on humans to do the most important parts of its function, interacting with candidates and employees, finding talent, determining strategy, and evolving with the business. Innovations in technology will not only help HR do its job better, but they will change what that job is. More than ever, a static, process-driven approach to talent will be replaced by a focus on strategic vision and agility.

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