With the introduction of many new technologies, the hype often exceeds reality, and the public slowly loses interest. Artificial intelligence (AI) appears to be bucking that trend, rapidly gaining traction in part because of its wide-ranging capabilities and applications. Recent SIA research backs that viewpoint, with 39% of current manual staffing tasks expected to be automated through AI within three years. According to Viren Yadav, vice president of LanceSoft, “AI has the potential to become the tool that automates and manages mundane, repetitive tasks, enabling people to focus on more important strategic work that improves business outcomes.”
These mundane tasks permeate nearly every step of the traditional candidate acquisition value chain and promise to transform the industry and provide a competitive advantage to early adopters. However, the use of AI does raise compliance concerns, and even companies that rely on their staffing providers to leverage AI — which is a large percentage of staffing firms — are generally held legally responsible for any AI used on their behalf, whether they are directly involved or not. Therefore, it is critical for contingent workforce programs to stay current in the ways their staffing partners implement AI as its usage and related regulations grow and evolve.
In this article, we profile AI usage in staffing through the lens of industry pioneer LanceSoft and highlight its impact, use cases and risks.
The Impact of AI
The impact of AI in the staffing industry has been compared to the rise of the internet — creating a wide range of opportunities to reimagine today’s processes while making possible new capabilities not previously seen. According to Anju Abel, CEO of LanceSoft, “We are seeing it decrease costs, increase efficiencies, validate our candidates and create better communications with us, our clients and candidates.”
Industry-specific approaches are emerging, and the technology will impact companies in different ways and to varying degrees. For example, at LanceSoft, Yadav uses AI effectively for highly specialized use cases, including automated candidate communications that are sent according to data-based parameters and candidate behavior patterns. Another is email sequencing based on specifics like average response times in a geographic region/city and best lapse times between follow-up messages.
While there is concern that AI may replace human workers — like any new technology promising improved efficiencies — many in staffing and recruiting expect few, if any, staff reductions. Time saved through the elimination of mundane tasks can be reallocated to higher ROI activities. Recruiters can focus on developing relationships and filling a candidate’s human needs, not processing paperwork.
Key Staffing Industry AI Use Cases
AI will continue to reshape staffing and recruiting, yielding better experiences for companies and candidates. For many candidates, this also offers a more pleasant hiring process, which itself could remove hiring friction and expand the growing pool of contingent workers. Abel and Yadav pointed out six major use cases where AI could improve today’s manual processes:
Candidate experience. While candidates benefit from AI, they look for a mix of AI and human interactions during their job searches. For quick responses to basic questions, bots and other real-time chat tools provide exactly what candidates are looking for. In Yadav’s experience, higher-level issues with emotional components that arise are often more effectively resolved by people.
Automated communication. Candidates respond positively to automated communications, as they offer consistency and recognition for actions taken. When candidates interact with AI tools, organizations can collect data which then helps establish new patterns that can improve processes and best address candidate needs.
Candidate vetting. For companies, vetting candidates continues to become more efficient through automated skills reviews, testing and background validation. Administration and scoring of skills testing and other evaluations is already commonplace; outcomes are used to rank individual candidates and create amalgamated data sets to improve parameters for specific jobs.
Fraud checking. Some companies are even relying on AI to ensure résumés, candidates and references are real so no one falls prey to scams. Yadav notes that LanceSoft uses AI to review and then compare résumés to publicly available online sources like LinkedIn to ensure candidates are representing themselves consistently. They also use automated emails and texts to check references; these can also be verified so applicants cannot present multiple references that are actually one person or source. All of these quality control measures yield higher-quality candidates and better overall hiring outcomes.
Onboarding. During onboarding, AI can serve as a reminder when any sort of due date is approaching or a deadline has passed. Paperwork, start dates, meetings, provisioning, badging and more can be finalized automatically, which speeds processes and reduces human error.
Credentialing. In some industries, credentialing and certifications are being verified via email and/or text message. For these functions, final review by an in-person compliance team can be essential in certain industries. At LanceSoft, AI is used to verify credentials and licensure, which sped up hiring during the pandemic for a client that provides nationwide health clinic services. “We were able to help our client hire quickly and give workers more control over where and when they worked, which addressed the volume needs and urgency of the situation,” Yadav says.
AI Regulation and Implementation
It is critical that organizations work with their staffing partners to stay compliant with the regulatory landscape, which, as is common with other new technologies, significantly lags behind actual practice. For example, in New York, employers are required to disclose the use of AI to candidates and must conduct annual AI audits to ensure the tools are bias free. Illinois prohibits employers from using facial recognition software without applicant consent. Many others are likely to be added, and as noted earlier, users of staffing firms may be held legally responsible for bias, regardless of their involvement in the process.
Beyond regulation, AI presents change management challenges that, if not fully addressed, can thwart even the most promising use cases. When partnering with firms that use AI, organizations should evaluate their internal systems, processes and people to ensure the success of incorporating new technology. A well-articulated change management plan built on clear communication that answers the “why change?” question and provides education can smooth the journey.
While it is impossible to predict exactly the degree to which AI will impact the staffing industry over the next few years, one thing is certain: The companies that embrace change and choose to lead have a greater likelihood of success.
No matter where AI is used during the hiring process, Abel says, it is important to remember that it supports us. “As we evolve along our AI journey, we need to recognize that this technology enables what we do — it is a complement to our work and can truly make us better.”
To learn how your organization can benefit from LanceSoft’s AI-powered solutions, contact Anju Abel at email@example.com today.