As we wrap up our series on Artificial Intelligence, we’ve learned that AI isn’t as scary as some people make it out to be and that we can use it in a variety of ways- but with some caution- in order to impact our workplaces in a positive manner. 

We’ve tried to emphasize that AI is best to leverage when: 
You do the task a lot, 
It is a manual process, 
It is prone to human error, therefore:
It’s time consuming. 
So if you have the data sources you need and the technology to do it,
Let AI help. 
And go do something more value added with the time you save.

As I’ve wrapped up my personal deep dive into AI for HR, I’ve found our friend Ben Eubank’s book Artificial Intelligence for HR to be a useful tool in framing the technologies that can impact HR by functional area.  Here, I’ll summarize some practical uses by functional areas based on Ben’s insights as well as some of my own.  I’ll also recommend some tools I have seen in action. 

Workforce Management (Time & Attendance) 

• Clocking in and out with facial recognition
• New companies are capturing the market of the uberfication of staffing with AI tools to provide labor on demand to fill gaps in staffing.  Check out Onin Flex as an example. 

Payroll & Benefits

• Automating many of the payroll processes and checking for errors that many companies still do manually.  
• Analyzing pay data for pay parity issues
• Offering on demand pay. Check out Immediate as an example. 
• Voice activated and/or chatbot technology to respond to benefit inquiry questions or how employees can perform certain tasks on his/her own. 

Recruiting/Talent Acquisition

• Screening resumes by keyword search (you’ve probably been doing this for quite some time) 
• Take it a step further, once you have your technology query candidates by your filters, have the technology reach out to them to schedule the first step in the selection process
• Use tools to rediscover applicants and match old candidates for other jobs
• Use tools to rank candidates and let it learn from your rankings to screen candidates (caution: if you put bias in, you will get bias out)
• Check out LinkedIn Recruiter that has a variety of features to help identify candidates based on a variety of criteria.  One criteria that I find most interesting (and Ben points this out in his book) is Candidate Receptivity. In other words, how likely will a potential candidate be interested in your opening and company? 
• Use some pretty cool assessment tools.  One company I’ve been following since 2018 when I met them at the HR Tech conference is Pymetrics.  They are worth checking out.

Learning and Development and Talent Development and Management

• There isn’t a day that goes by that I don’t hear about the “skills gap”.  It’s a macro issue and an issue at every company with internal talent.  There are tools on the market now that help you understand your internal talent’s skills and then help you hire internally or place people on projects based on skills analysis (Remember, tools like this are only as good as the data you put in them.  If skills aren’t in the database or aren’t accurate, it won’t work.)   A quick google search will give you a list of software tools in this space. 
• Tools to recommend learning content for users at the individual level and at the organizational level.  Think of your Amazon Recommendation list for learning content. Take a look at page 153 of Ben’s book to understand how this works.
• Giving leaders tools for coaching based on performance data and feedback so learning content is customized by user.  Voice technology tools that can listen and help coach a manager through specific issues. 
• Insights to help you better understand correlation and causation between a number of dimensions and employee performance and engagement.  Features can include what if analysis (What if employee engagement rose by X percentage points, how much would turnover decrease?) to sentiment analysis (taking a large amount of qualitative employee survey data, summarizing it and making recommendations for action). 

Diversity, Equity, Inclusion and Belonging  

• Identifying biased communication in email, Slack, etc. and in job postings.  Check out Textio as another company I’ve been following since 2018 in this space. Their technology helps with bias and receptivity in job postings and they also have a product for writing better performance feedback.
• Blind screening tools for recruiting, removing information that would indicate dimensions in which bias may occur. 

Of course, this isn’t an exhaustive list of things AI is doing in HR, but it is a start. If you are thinking about vetting technology vendors, this may be a good list to begin with by walking through these items and asking, can your technology do this? 

If it is a comprehensive list HRM system and it can’t do most of these things, or provide API technology to connect to tools that can, you may need to vet other vendors. 

What functional area in HR are you most interested in leveraging AI technology?