Tech advancements today are not only directly influencing the nature of gig work but have also resulted in business changes that facilitate the growth of the gig economy. So has been the case with the use of AI in employing gig workers. With a large percentage of companies today waking up to the potential of digital tech within their processes, the prospects of a gig economy seem appealing to many.
With the shelf life of many technical skills also shortening as a result of tech advancements, companies often resort to working with freelance skilled professionals on a project basis rather than hiring a full-time employee for the position. Lower labor costs, less contractual obligations, and the ability to hire for niche skills are some benefits that employers drive out of the gig economy, and the use of AI has made this process more streamlined.
In spite of the growth of the gig economy, finding the right talent remains to be a difficult proposition for both employers and HR professionals; the problems of skills mismatch are equally present in cases of hiring gig workers. Not just recruitment but also monitoring performance and productivity often becomes difficult. Skepticism on the eventual benefits of the gig-based model remains, with the persisting concern surrounding proficiency of skills.
According to a survey by Deloitte, a majority of the gig economy workforce worldwide belonging to the millennial cohort will join the labor market even before they complete their education. While market economics means that such workers will find gigs based on their skills, companies remain skeptical in employing many, even on a contractual basis to avoid inefficiencies.
This can be markedly improved with the use of AI.
Application of AI and ML in managing the gig economy
As the application of AI and ML across business processes improves, recruiting and hiring gig workers is also bound to become more efficient. There already exist platforms that promote flexible work culture while enabling companies to hire the best of freelance workers depending on their domain. Even recruiters, aware of the potential of the gig economy, are creating newer ways of assessing talent and skill levels. The use of AI can certainly improve the efficiency of such efforts.
For example, when it comes to screening gig talent, A.I. can aggregate data using various parameters to create shortlists of qualified candidates and suggest better hires based on previously set expectations. They also have the scope to reach out to the candidates on such shortlists and make it easier for recruiters to narrow their search for qualified talent. Programs can help HR professionals assess the suitability of candidates, thus helping refine the pool of candidates most suited to any given project. The right AI application can do this by quickly mining candidate data, giving organizations insight into each prospect’s skills and career goals.
AI and ML can further be used directly towards simplifying interviews with A.I.-driven human-machine interfaces and automatically schedule second-level interviews with the most qualified applicants. This helps companies build their capabilities for identifying the right talent. This also helps remove the dependence solely on job portals, social media, databases, and similar resources to gauge a candidate’s value to a project.
As such digital places get overcrowded with people looking for gig work, having robust assessments becomes a vital part of hiring right.
AI impact on process efficiency for gig workers
Companies have also begun using AI to allocate work to gig workers and keep a track of their work. With many companies preferring to work with gig workers on a project basis, AI can assist employers to allocate specific portions of work to gig workers and can provide feedback to ensure efficiency is maintained. After successfully recruiting talent, companies can benefit from using A.I. to organize their teams. Rather than trying to galvanize a group of strangers around the company’s mission, employers can utilize software that quickly and effectively builds teams in batches to focus on specific projects
Today a wide range of A.I. applications are actively enabling employers to drive greater value out of the gig economy. Many of the challenges experienced by HR professionals revolve around staff co-ordination, balancing internal and external teams of personnel, and efficient project management, aspects which can be improved upon with the right contextual use of AI algorithms. AI widens the scope of the gig economy and can enable the maturity of the gig-based work model. They can do this by automating rote tasks within project management and providing organizations with clear workflows for co-ordinating hybrid teams of internal and external experts.