AI is making its way into multiple facets of talent acquisition. Some see that as an opportunity and some see it as a potential risk to the current ethos in the space. Workflow automation means less human interaction with every part of the process. But that could also mean more focus on specific areas that need the human touch. Below you will find multiple opinions on what AI’s involvement means to industry leaders in regards to their workflow automation and retention practices today and in the future.
What Talent Acquisition areas will be most impacted by AI by the year 2020? There are several popular areas that repeatedly are mentioned –
1) Diversity and Inclusion in TA (eliminating bias);
2) Workflow Automation of repetitive tasks;
3) Increasing employee engagement and retention by using Predictive Analytics.@xor_ai asked dozens of #TalentAcquisition leaders what they think will be most impacted by #AI by 2020. Check out what the experts have to say:Tweet This!
On Workflow Automation and Retention
I think Workflow Automation. There are many tedious steps that could be handed off to AI tools. Especially as the chatbots and interview-bots improve and are more conversational to the user and recruiter. I don't think the bias starts with selection so I don't see where AI could really impact that. Bias is rooted in much deeper socioeconomic factors. Engagement and Retention comes when you hire the right people to lead people. Attitude, spirit, personality.... could be measured, but if AI could score that it might help select people leaders.
--Louis Williams, System Director of Talent Acquisition
Franciscan Missionaries of Our Lady Health System
I believe the area of TA most impacted by AI will be Workflow Automation because it requires humans to give up less in order to achieve it. What I mean is we are already used to interacting with machines and programs that do our work for us. Many humans interact with chatbots today when they go online to shop or resolve customer service issues. The concepts or Big Data and Machine Learning are part of our vocabulary, even if we can't explain what they are or how they work. We know there is some sort of program that tells us which movies to watch on Netflix or what books to buy on Amazon. We accept the results of these programs and interact with them knowing they are being generated by machines.
This acceptance will allow candidates and hiring managers to get comfortable with recruiting processes driven by AI automation in the next few years. We'll know we are interacting with a machine when we use a chatbot to go through the pre-screening process, but we'll be ok with that. As hiring managers, we'll know a machine learning algorithm generated the list of candidates we are reviewing based on our previous hires and job requirements, but we'll overlook the fact it was program that created the list because it gave us 10 highly qualified candidates in less than a day.
--Greg Roche, Senior Director of Compensation and Benefits
DaVita Medical Group
Yes AI is extremely helpful when reducing repetitive and mundane tasks that take recruiters time away from actively seeking qualified candidates and those passive candidates that may be looking for new opportunities!
--Karen Farmer, Director of Talent Management & Talent Acquisition HR Operations
Using AI to measure and assess behaviors like resilience, grit and tenacity at the onset will start to balance with technical and functional skill. Also, tracking this attribute in a organization to better predict outcomes throughout an employee's life cycle, like intent to stay, is something not far from reality.
--Angela R. Howard, Director, Talent Management & Culture
Kaiser Permanente Founder at ARH Clarity Consulting, LLC
Within #2, (workflow automation), lies the greatest set of opportunities for TA in my opinion… With the rise of data aggregators in the last couple years -- I’m thinking of firms like Entelo, Simply Hired, etc., searches are now carried out on much larger sets of data that span hundreds of public web sites. The algorithms also seem to be far more robust and more easily customized to the recruiter’s or the firm’s specific needs, consequently, the results are better. This in turn allows recruiters to target the right audience from the start, and then, leveraging those automated communications tools to engage with prospects becomes a more fruitful proposition (an example of one AI advance feeding into another).
--Alex Bacas, Talent Acquisition Sourcing Partner Company
T. Rowe Price
AI - Workflow Automation
This seems like an ideal state to save costs, reduce errors, and allow companies to better utilize humans for their human element... However, not everyone is wired for or interested in jobs that are technology-resistant. For example, we have seen a great trend in service-oriented jobs on the rise with manufacturing jobs declining. While it may be difficult to overcome the “will” aspect of transitioning into service roles, we also have not mastered overcoming the “skill” aspect.
I will not spend too much time on the soapbox on this aspect, but I also feel we have not yet evolved our educational approach to better prepare people for service-oriented, skilled labor-oriented, analytical thinking, and/or STEM roles. I love the advancements of AI, but we also need to find ways to help shape our future workforce to be successful in the roles that will be available to them.
--Maureen Hascher, Vice President
You have the top 3 I believe it will be most utilized in workflow automation. It has the quickest and most immediate tangible return in the form of cost reductions. It is also the easier to implement. Automating the candidate experience and on boarding is more scripted then true use of AI at this point, but there is tremendous value in pushing towards more AI in this area.
--Michael Duplessis, Vice President of Talent Acquisition
My personal take (not speaking for my employer) is that #2 is the first place that TA in general will be able to realize immediate results, if only because I think RPA is the logical place to focus energies out of the box. I've got concerns about the ability for AI to actually eliminate bias, at least in the immediate future. I'm in the camp that believes that we'll need to be very careful about what (and how) our robots learn to identify "best."
--Seth Kavanagh, Corporate Director HR Technology & Analytics
New York-Presbyterian Hospital
My answer is #2 is the "easy" choice because AI applications have shown promise in automating standardized, repetitive workflow tasks… TalentNeuron is innovating with an AI (via a Bot) to help recruiters and sourcers get labor market insights for specific role searches based on allowing users to type in their search criteria using normal language. However, it's not clear cut as simply deciding on "process" tasks to automate. Gartner analysis reveals the organizations getting value from AI (whether in HR or other facets of the enterprise) are deliberate about developing a rigorous business case.
--Jeremy Citro, Senior Customer Success Director, Talent Neuron Gartner
I would have to surmise that workflow automation will be the areas most impacted by Artificial intelligence by 2020. The use of Chatbots, will streamline the candidate and recruiter workflows. Eliminating the need for manual processes like Scheduling, Prescreening, onboarding and even providing the ability for companies to leverage for responding to questions about the culture, or company in general. Since this is fairly new, i see a potential influx in the upcoming years of companies migrating to leverage, deploy and implement Artificial Intelligence to reduce cost and administrative burden in Recruiting. In addition to examining ways in other areas like Employee Engagement and Communications.
--D'anthony Tillery, Vice President Talent Acquisition & Deployment Acosta
For AI, the wave of the future. I feel that #2, the workflow automation will be first to be automated across the whole lot TA, then elimination of bias...if they can only figure out how to take off names of resumes.
--Diane Zimmer, Talent Acquisition Professional
I believe all three will be critical but there is more and more evidence of the need to utilize predictive analytics to improve retention. The talent war is real and in my industry (healthcare) we have a shortage today with a much larger shortage predicted by 2021. We have to do everything possible to retain the best. Flexibility, transparency and technology are key drivers of the employee of the future. We must use art (creativity) and science (data) to retain top talent.
--Naomi Cramer, Vice President Talent Acquisition
As far as D&I and engagement and retention, I believe AI will help us in those areas in the future, but our acceptance of their results will take longer. In D&I, we are asking a machine to identify our own biases or to highlight decisions we have made that would be considered "wrong" if we were allowed to make the decisions ourselves. As humans, we don't like to be told we are wrong or that we have certain biases we don't control. For engagement and retention, we are beginning to understand all the reasons why people become disengaged and leave, but we can't yet identify all the signs that it is happening. I don't think we have enough ways to collect inputs for engagement on a daily basis in order to allows the machine to learn when our engagement is waning. In the future, we'll all likely sit down at work and our Siri or Alex-like work-friend will ask how we are feeling. Based on our response, including the words we use and the tone of our voice, it will know how we are doing and in time be able to identify when our sentiment toward work is turning negative. But for now, we aren't there in terms of entrusting our feelings and thoughts to machines.
--Greg Roche, Senior Director of Compensation and Benefits
DaVita Medical Group
Regarding Popular Area #3, about AI increasing employee engagement and retention—I would be extremely careful about making any connections/claims here. There’s already an abundance of Data about low levels of Engagement. So how exactly will AI solve that problem? The problem with low Engagement is rooted much more deeply in basic Job Design and Career Development issues. And the solutions require Leaders who understand that and are willing to think differently and develop unique Talent Strategies to increase Engagement. So I don’t think we need more or better data on low Engagement. We need more and better solutions. And since I see AI as a Diagnostic Tool, I think positioning it as being part of the solution to increasing Engagement/Retention is misleading. At the very least, I think it puts AI on a Slippery Slope.
--Barney Olson, Director, Talent Strategy & Organizational Development
AI has the opportunity to revolutionize the candidate experience! Organizations can use AI to stay connected with candidates in the talent forums and pipeline. AI could even manage simple communication tasks and check-ins on the prospective employer’s behalf.
--Ingrid Immanuel, Director, Talent Strategy
The challenge for all TA professionals will be to leverage AI correctly to ensure that we do not over utilize it. Human interactions, specifically in the selection process, are critical to maintain. Therefore, the challenge will be to leverage AI in the right place in the process so that the human interactions can become even more meaningful for the candidate and the company. Creating a great candidate experience is paramount for a company's success. Now more than ever we have a great opportunity to leverage technology to compliment the great work recruiters are doing to engage with candidates.
--Alyssia Fotenos, PMP, Vice President of Human Capital
At XOR, we believe in retaining employees and efficiently wielding automation to save money and time in recruiting. With the XOR chatbot, conversations with potential candidates are conducted by AI built to be indiscriminate and set with 100+ languages to accomodate any interaction. Currently 60% of applicants drop off from the hiring process when approached with traditional recruiting. Reclaim those applicants with XOR and schedule a demo now.