What Is AI and How Is It Applied?
Artificial intelligence is an umbrella term for applications in which machines perform human-like intellectual tasks such as learning, judging, and solving problems. Today, artificial intelligence is based on processing very large volumes of data. Current forms of AI use neural networks and develop self-learning systems in the form of machine learning.
The term “AI” has been discussed in expert circles for 60 years and tends to be viewed skeptically by the public, out of fear that it could replace humans. However, artificial intelligence has long since arrived in everyday life and, depending on the area of application, is widely accepted. If you take a closer look, intelligent algorithms ease our daily work and solve some of our problems. Gartner’s 2019 CIO Survey found that 37 percent of companies currently use AI. A KPMG study reports successful areas of application and continued adoption. But which specific areas of talent acquisition can AI cover, and how can it deliver real added value?
Specific Areas of Application in Talent Acquisition
KPMG’s study “Rethinking Value Creation” identified three key areas of application for AI in HR
- Support in selecting applicants
- Creating training materials
- Employee apps
In this blog post, we explain in detail how AI can help select suitable applicants. Widely used AI applications in recruiting include chatbots, matching platforms, and so-called “Recualizers,” which help qualify and pre-screen candidates.
a) Chatbots
There are two types of chatbots. The first type works on the basis of pre-programmed rules and cannot help with questions it has not been programmed to answer. When a question is entered in the chat window, the bot first breaks it down into its components and analyzes it. The system responds to certain keywords and structures and, based on these, selects a predefined answer. These chatbots are well suited when the exchange consists of simple questions and no real conversation develops.
The second type is the smart chatbot, which is based on AI or machine learning. The capabilities and potential of learning chatbots are becoming increasingly comprehensive. For example, this second type of chatbot can not only provide intelligent answers but also assess a candidate’s suitability for the targeted position and even proactively suggest suitable jobs to the applicant. It draws on application documents, social media activity, and web interactions to do so. The current market shows that most companies use chatbots for one reason: to answer standard questions quickly. Speed plays a major role here, because the moment a candidate asks a question is when their attention is at its highest. Fast, clear communication automatically increases the appeal of the company and employer.
b) Matching Platforms for Pre-Screening
So-called “active sourcing” involves a matching process based on an algorithm that uses predefined criteria to search profiles on platforms such as Xing and LinkedIn for potential candidates. The more intelligently this algorithm works, the more likely the searcher is to get suitable results, allowing recruiters to reach out directly.
Such matching algorithms are used not only on these professional networks but also in the HR market. For example, the company Moberries used AI to develop a matching platform that brings candidates and employers together simply and transparently. Candidates create a profile, list their core skills and preferences, and, based on this data, are introduced to companies that could be a good fit. Employers also create profiles and can publish their open positions on the matching platform. Using job-specific criteria, the AI searches for actively job-seeking candidates who meet these criteria and generates matches accordingly. The process is automated and notifies both parties as soon as a match occurs. If both parties say “yes” to each other, nothing stands in the way of getting to know each other in a job interview or similar setting.
c) Trend Case “Recualizer” from the KPMG Study
The “Recualizer” is an application designed to reduce the workload involved in hiring. As a first step, the HR professional defines the framework for the position to be filled. Using this information, the system generates various application tasks aligned with the given requirements. Once applicants have completed the tests and the results are available, the employer receives evaluation scores. Based on these, the most suitable candidates can be invited to an interview.
AI in the Future – Intelligent Interview Guidelines in Development
Recently, another innovative approach was presented that could significantly influence recruitment. An interview with Sara Lindemann, Head of Enterprise Customer Development & Co-Founder of Viasto GmbH, makes clear that the company is already working on solutions that could make personnel selection more efficient, flexible, and reliable.
"We are currently working on AI solutions for the automated development of job-specific interview guidelines. After all, differentiation as an employer also takes place in the personal conversation.” Sara Lindemann
An interview guide is meant to draw on data from questions and conversation strategies that are actually used and based on findings from personnel assessment. This means that data from analyses of past employee selections and placements that demonstrably led to success is used, with the help of artificial intelligence, to develop an interview guideline.
More specifically:
“With a simple click on a parsed job ad, HR and the hiring department receive the optimal interview guide.” Sara Lindemann.
The AI learns from applicant feedback and recognizes when additional skills or requirements are missing from the job ad. Building on this, it can make suggestions and thus improve the quality of personnel selection.
Risks and Conclusion
In summary, AI systems can make a significant contribution not only to making the application process more efficient and more engaging, but they will also be used more widely in the future and turn our way of working into a genuine innovation.
That sounds promising!
But the risks must also be considered, because there is a danger that the systems learn from a company’s past mistakes. Companies that have always favored one-sided applicant profiles run the risk of their AI systems applying the same filters. AI systems are only as good as the data they process. Poor data can even lead to racial, gender-based, or ideological bias in the results. It is therefore important to develop and train these systems with data that is fair and free from negative influences.
If you have now recognized the added value of using AI in your recruiting processes, don’t wait for change – actively shape it!
Because one thing is certain: Artificial intelligence is already established and will continue to spread in the coming years.
Sources:
Saatkorn. A blog by Gero Hesse. Interview with Sara Lindemann, Head of Enterprise Customer Development & Co-Founder of Viasto GmbH, on the study: AI in Personnel Selection. Published on December 11, 2018.
IBM: AI in HR: Technology Sets the Pace. Author: Sven Semet. Published on March 26, 2018.
KPMG AG study: Rethinking Value Creation: Artificial Intelligence: Applications in Companies and Development Scenarios up to 2040. Of Humanoids, AIs, and Robot Colleagues. Published 2018 in Berlin.