Recruiting AI in 2020: Guide to augmenting the hiring team

One of the biggest challenges that HR professionals are facing is finding the right talent. Recruitment teams spend time on partially automatable tasks such as resume screening, interview scheduling and interviewing. By using the latest advances in artificial intelligence, businesses can reduce the load of HR professionals and increase hiring effectiveness.

What is AI recruiting?

AI recruiting is applying machine learning on the recruiting related big data to improve the recruiting process of the organization. AI in recruitment is designed to reduce the time spent on repetitive, high volume tasks through automation. Read more


AI in HR: In-depth guide with top use cases [2020 update]

AI is used in hiring, analytics and churn management in HR

Companies form HR departments to handle hiring and compensation. Soon, HR leaders find themselves tackling, retention, performance management, culture and a myriad of other responsibilities. And now CEOs are asking them: What’s your AI strategy?

The short answer is: AI will transform HR creating a lean department that is less intrusive yet more impactful. But how?

HR analytics is a must for any large company

Software has eaten the world and now AI is eating software. The first application of AI is advanced analytics, enabling companies to have instant access to insights. HR analytics is also the first AI use case HR professionals need to explore. Read more


6 reasons to set up HR analytics [2020 update]

HR analytics has been rising in popularity in the past 5 years

Human Resources experts, well-versed in psychology and organizational development, have been relatively slow to integrate analytics into their operations and decision making. Once HR leaders realized benefits of advanced analytics, interest in the area quickly increased as you can see explosion in google queries above.

HR analytics enables HR managers to improve their operations and decision making with data. HR analytics enables HR personnel to run advanced analytics to enable:

Improved HR performance

  • 1- Improved hiring: Running machine learning algorithms on existing workforce allows companies to identify which traits lead to success. However, this may also formalize existing biases in the company. Therefore HR managers should question machine learning outputs and make sure that irrational past biases based on attributes like gender or race do not get incorporated into the decision making. Once managers know who will be the right fit for the company they can shape their brand building, outreach and candidate engagement efforts accordingly.
  • 2- Improved retention: Running machine learning algorithms on churn data can uncover churn patterns and predict employees who are likely to churn. This can enable HR to manage churn proactively. Such insights can also help improve onboarding, training and performance management systems if they cause issues which can trigger churn.
  • 3- Objective performance management: The dreaded mid-year reviews end up being subjective and demotivating. Granular performance data can be used for objective, frequent and automatic feedback which can support face-t0-face reviews backed by data.

Improved understanding of the company and its progress

  • 4- Better understanding of productivity and motivation: Uncovering what drives motivation and productivity can help shape HR strategy, including training, performance management and other HR policies. For example if productivity of remote workers can be analyzed, then company’s policy of remote working can be fine-tuned.
  • 5- Better understanding of company culture: Sentiment and network analysis of anonimized communication between employees can help HR managers understand company morale and culture in detail. Since this requires analysis of confidential and personal data, care needs to be taken to ensure anonimity.
  • 6- Accurate record of progress: By tracking key HR data over time, companies can compare themselves in different time periods and observe changes.

If your company is not working with an HR analytics solution provider already, this is a good area to investigate. Additionally, you can check out AI applications in marketing, sales, customer service, IT, data or analytics. And If you have a business problem that is not addressed here: Read more