How to Best Use AI Recruiting Software
About the Author
- What are AI and ML: Artificial intelligence (AI) is the ability to apply automated actions to data. AI complements machine learning (ML), which organizes and cleanses data.
- How to use it: The best use of AI recruiting software is to empower humans, providing them with the ability to remove redundant tasks, and have deeper insights for decision-making.
- What the future holds: AI empowers recruiters with deeper insights to get the job done faster and better. AI will continue to make advancements and improve efficiencies.
In three years, 47% of the services that organizations receive will be delivered via a mix of AI-enabled and non-AI-enabled automation, according to IDC FutureScape 2020.
Despite the inevitable future, artificial intelligence (AI) and machine learning (ML) are both desired and feared in today’s fast-paced hiring landscape.
Colin Day, our founder and chairman, recapped the sentiment expressed at our annual analyst event, iNFLUENCE. Colin heard firsthand from customers and industry pundits the love/hate relationship that talent acquisition has with AI and ML.
Employers are intrigued by the idea of bringing in smart technology to aid in making faster hiring decisions. There isn’t a recruiting team out there that would pass up the opportunity to propel their day-to-day operations as they try to do more with less. However, they also fear the repercussions of relinquishing control and giving AI and ML a bigger stake in the recruiting process.
The uncomfortable stories of AI capabilities cause us to pause when considering how to best build a strategy around the technology. However, properly implementing smart technology that allows us to make better decisions shouldn’t be feared by organizations.
At the core of a successful AI recruiting software use case is a stronger human + technology partnership.
iCIMS ARI communicates, screens, and schedules interviews with candidates.
Human-led decision making with AI recruiting software
Human-led AI is the application of technology to empower users, not replace them. Human-led AI gives recruiters full autonomy, using automation and predictive insights as tools for recruiters to make stronger decisions and drive better outcomes. When your recruitment software and talent teams work together, technology provides the guard rails, and recruiters receive the highest level of transparency and control to make hiring decisions.
Industry analysts, customers, partners, and internal tech teams agree that the best use case of smart technologies is to bring forward deeper decision-making rather than replace human jobs.
How you can be more efficient and proficient with AI and ML
AI and ML provide insights by recognizing patterns and processing large amounts of data, then logically applying actions to that data without ever being explicitly programmed to do so. AI, ML, and automation should exist together within your talent acquisition platform.
Here are some examples of how we use it:
- Remove mundane tasks. Recruiters need time to make informed decisions, but we all know they don’t have that luxury. Resume parsing and chatbots remove mundane tasks to give recruiters more time in their day. Recruiters can then use AI-powered predictive analytics to make informed decisions.
- Foster better decision-making. Candidate matching provides recruiters with recommendations on which candidates in your talent pool might be a fit for a specific job opening. This allows recruiters to review quality contacts that you already have in your pipeline, resulting in less time spent and a lower cost to fill.
- Expose more job postings to qualified candidates. Intelligent job discovery on career sites eliminates discrepancies in spelling, acronyms, and works to better understand user intent to surface next-best keywords or job descriptions. Job discovery also highlights recommended job postings based on geographic or commuting-time preferences.
What to look for in the coming year
Continue to look for solution providers that not only make your end user’s day-to-day tasks easier but also provide the level of control and transparency needed for the tech to be truly “human-led.” As Colin noted, “we now need to find ways for people and humans to work better together as we move into the future.”
Learn more about industry reactions to and expectations for AI and ML by reading Colin’s article on iNFLUENCE.