Ai in HR Tech: Use Cases, Arising Startups and M&A Activity

This piece was originally created by Data Root Labs, edited and republished here with permission.

HR is one of those “human” jobs that will be hard to replace with AI. Akin to psychology, it requires a high level of EQ (quotient of emotional intelligence) and profound personal touch. The common preconception is that it’s very hard to augment, let alone automate. Over the last half-decade, this line of logic has come under fire, with data-driven approaches penetrating more and more human resource practices.

With the cost of AI adoption plummeting and the data science community growing by the minute, business leaders are starting to reach out to process automation and augmentation opportunities in the people operations realm. Gartner predicts that by 2022 (three years from now!) one in five workers engaged in non-routine tasks will rely on AI to do their jobs.

The key drivers fueling the growth of HR tech market include increasing need for managing the widespread workforce, growing demand for replacing the legacy systems, the increasing importance of candidate experience and technological proliferation in Big Data analytics, Machine Learning, Artificial Intelligence (AI), and Internet of Things (IoT). Thus, new report by Grand View Research, Inc. projects the global human resource management market to reach USD 30.01 billion by 2025, registering a CAGR of 11.0% from 2019 to 2025.

PwC forecasts that 20% of U.S. companies with AI initiatives will roll out AI across their business this year to both re-imagine jobs and work processes as well as grow profits and revenue.

A lot of AI use cases revolve around eliminating the tedious and routine tasks, while HR managers handle the most important side of the job – human interaction. We have identified the following key problems that AI can solve:

• Efficiency improvement: automating repetitive tasks.
• Recruitment and candidate assessment: more efficient and less biased hiring.
• Employee development: coaching and engaging employees to enable personal growth.
• Culture maintenance and HR management: identifying cultural issues and key areas for improvement.

Let’s look at those cases one by one:

Efficiency improvement

Automating repetitive tasks.

AI in HR and recruiting gets people to move away from repetitive tasks not to waste their talents. As a result, they can target their energies on more high-level tasks, such as finding promising employees and working to keep them with the company. HR staff will focus on being a strategic partner to business divisions rather than crunching data as a task processor. AI will empower companies to make faster decisions by:

• Accessing up-to-date information.
• Spotting trends through pattern recognition.
• Using machine learning to identify past mistakes to avoid and accelerating processes.

Recruitment and candidate assessment

More efficient and less biased hiring.

One of the major disruptors in candidate hiring is HireVue’s artificial intelligence platform. It identifies and analyzes the tone, word choice, body language, question context, and answers of candidates who have recorded video interviews to determine if they’re a good fit – by skillset and culture. Their quantifiable score compares all the candidates, ensuring HireVue makes the optimal unbiased hiring decisions – all thanks to AI and Machine Learning.

AI helps companies through the process of pre-hire assessments. While assessments are nothing new, in the era of AI, a company can predict which candidate will be a better hire in the future. Sample this, a candidate applies for a role in a company by entering his resume. An AI-powered system analyses the resume and compares it to the successful employees in the same role.

A chatbot reaches out to the candidate and asks some pre-screening questions. They collect candidate data, and AI uses it to score the candidate and present the result to a recruiter.

Pymetrics uses AI-based gamified assessment to screen candidates. One of their customer’s hiring success rate has gone up by over 30% while eliminating all the “educational pedigree bias” inherent to the recruitment process faced by almost all companies out there. AI in recruitment is already huge.

Another player in the HR assessment game, Sapia, helps big brands to get the candidate experience right. They already have text data on 15% of the Australian population that helps identify with 85% accuracy the personality profile of applicants into all customer-facing roles (retail, sales, customer service, etc.). To reduce the hiring bias, the company doesn’t use CV data, nor it builds data models off the existing employees. They only use the text data ensuring that everyone gets a fair go at the role. That allows their clients to hire for the right values and behaviors. In addition, Sapia provides personalized personality reports to every applicant for every role. Amid low unemployment and the rule of social media, this is particularly important to consumer brands who measure the impact of poor candidate experience on customer attrition.

Employee development

Coaching and engaging employees to enable personal growth.

Learning and development (L&D) is a young HR practice and yet the global L&D industry is worth over $200B. Nearly half of the L&D opportunities organization forget, inappropriately apply, or waste on people that don’t want or need it.

Companies like Fuse are now building AI-based coaching tools that request feedback, read comments, and glean sentiment from employees and entire teams. They use data to match these individual and team issues against higher performing teams, giving managers and supervisors the requisite tools to do better.

As part of it, HR undertakes activities such as talent acquisition, employee management, performance management, succession management, etc.

For example, organizations like Greenhouse Software are integrating IBM-AI capabilities through the IBM Watson Candidate Assistant. It is a suite of AI-powered tools that matches jobs to the candidates and vice-versa based on their personalities, skills and interest areas. Greenhouse collects candidate data through various funnels including social media.

It observes minute details such as whether an employee submitted their work sample through LinkedIn or Glassdoor. It maintains scorecards for all the employees based on its own analysis with zero human intervention. This helps the interviewers sort through the applications ahead of time and keep the talent funnel ready.

Culture maintenance and HR management

Identifying cultural issues and key areas for improvement.

AI can look at organizational network data like email traffic, survey results and sentiment of comments to identify areas of stress, arising ethical dilemmas, and various forms of spreading toxicity within a company culture. This helps HR managers identify red flags faster and act in a preventive rather than reactive way.

Employee mental health is extremely important. People are the foundation of your company and they better be happy if management aims to achieve some lofty goals. To remedy some ongoing cultural issues, AI now identifies behaviors that cause poor work performance and disrupt the balance of your working environment. A new breed of intelligent chatbots can ease these situations by providing interactions in an intelligent and easy-going manner while alerting the HR department of any cases that go beyond the red line and need in person handling.

The above are some of the key cases that new technologies enable. For a deeper understanding of the innovation happening in HR tech, take a look at the following infographic by Will Saborio at Silicon Salsa.

Many of these companies already have AI and Big Data components.

(fig. 1) The early-stage HR tech landscape

M&A activity in HR sector

The mergers and acquisitions activity in the past year has been on the rise in HR tech, characterized by both more deals and bigger volume of deals. The trend for consolidation is strong as companies look to increase scale, add new customers and product lines, and penetrate new geographies.

From Recruit acquiring Glassdoor for $1.2B and K1 Investment Management acquiring Jobvite for $135M to SAP’s acquisition of Qualtrics for $8B in cash, there is no lack of jaw-dropping deals in HR tech from both financial and strategic buyers.

What are the most important factors for the buyers? The buyers are willing to pay more for high growth, SaaS product offering, dominance in a particular vertical or geography, ability to scale current solution, sticky enterprise customers, and clean financials. Yet the ultimate factor that determines the highest price possible is the 2nd (or even 3rd) acquisition offer on the table forcing buyers compete for a given company.

With a changing and developing technology landscape, we predict a continuous increase in HR tech M&A activity. In the table below, we summarize the key recent M&A events in HR tech:

Startups and investments

In Q2 2019 alone, VCs have poured $1.448B of VC investment into HR tech. The categories that saw a spike in investments are Wellness (Gympass, $300M round ), Benefits (Collective Health, $205M), and Core HR (HR Path, $112.5M, Payfit $78.6M). When it comes to AI-focused startups, the results are also impressive. In the table below we summarize the biggest rounds and most interesting deals around companies using AI in HR:

Final thoughts and real cases

The human-AI collaboration model is essential for a people-oriented domain like HR. It’s unlikely that AI will replicate the nature of human relationships and its nuance. That said, advantages of AI in HR can help us attune to people operations and make better decisions supported by solid data.

Since AI is developing and new opportunities are opening up, the ways companies use AI and the impact of AI in HR and recruiting will also change. The future of AI in HR processes is clear – AI will affect every organization. The question is how companies adapt and which processes they choose to reinvent or improve.

“Companies will need to be mindful of existing biases and work to ensure that AI does not perpetuate the problem”Ben Reuveni, the CEO of Workey

We at DataRoot Labs work with various HR-tech enterprises and startups. We help them build out AI-powered MVPs or transform enterprises by reinventing their HR systems with AI. Below, you may find practical cases on how we have solved real HR challenges with AI technologies:

• Candidate Scoring Models for a Job Search Platform