AI Resume Screening vs Recruiting Chatbots vs Conversational AI
Resume screening is the most time-consuming part of recruiting for high volume agency and internal recruiters. Data from LinkedIn shows that recruiters spend an average of 23 hours on screening resumes for a single hire, but AI resume screening can help reduce this time.
Considering that the average job opening receives at least 250 resumes, of which 75% can be unqualified, it’s no surprise that talent acquisition leaders report the hardest part of recruitment is screening candidates from large applicant pools. Using recruiting automation or AI resume screening is a potential solution to this problem.
There are many types of AI resume screening solutions available, but you can segment them into 3 categories, resume parsing, recruiting chatbots, and conversational AI.
In this article, I’ll cover:
- Why AI resume screening must go beyond resume parsing
- The most major flaw of even advanced resume parsing tools
- Recruiting chatbots and their ability to improve your post apply screening
- Similarities and differences between recruiting chatbots, enhanced chatbots, and conversational AI
- Why you need natural language processing for effective resume screening
AI Resume screening using only resume parsing is fraught with issues
Resume parsing automation extracts details from resumes and saves it in data fields. The methods it uses to extract data can vary from cumbersome repetitive forms that cause candidates to quit on applications to more subtle solutions that extract the data directly from the resume file itself.
The promise of resume parsers is to convert unstructured resume data into a structured format. Theoretically, recruiting teams should be able to use this structured data to find qualified candidates.
Most resume parsers are rule-based parsers. The problem with rule-based parsers is that there is a lot of ambiguity and variability in the language used in resumes that they are unable to account for. For example, a person’s last name “Duke” could be the same as the name of a university they attended.
In some cases, particularly in IT, the name of a skill could be confused with the name of a person and vice versa. Encountering a resume with “Apache Cassandra” on it would be enough to throw off a rule-based parser. The fact is, hiring teams can’t trust rule-based resume parsers to accurately structure resume data.
A new type of resume parser has been developed recently. This kind of resume parser uses AI technologies such as natural language processing (NLP) to create structured data from resumes. However, new resume parsers still have issues.
For example, the data sets that AI-powered resume parsers use to train are often too small, leading the parser to make errors in understanding the language it encounters. One AI-based resume parsing company used only 100 resumes to train their system to parse resumes in a new foreign language. With the nearly infinite amount of variability in language, AI based parsers need to be trained on millions of data points, not hundreds.
The key flaw of even the most advanced resume parsing tools
The critical issue with resume parsing tools is that their entire assessment of the candidate is based on data in the resume. Candidates may not have had time to carefully fine-tune their resume to meet the keywords resume parsing tools are looking for. Many times qualified candidates are overlooked by parsing tools.
If you’re looking for evidence of the issues caused by resume parsing software, just google “how to get your resume past the ATS.” If using parsers alone was effective, would so many recruiters and candidates be writing about methods for getting around them or overcoming them?
You’ll find hundreds of articles and discussions online from frustrated candidates sharing the challenges they’ve faced.
In fact, small industries of resume consultants and hiring coaches have even been created as a direct result of the issues caused by using resume parsing tools alone. These coaches and consultants work full time advising candidates on how to structure their resume and what keywords to add in to make it through ATS parsing screens.
Facing a resume parser is a poor experience for candidates, and it creates a weak pipeline for recruiting teams. Resume parsers have their place, but should not be used as the first tool for screening candidates.
The Conversational Medium of Recruiting Chatbots offers a potential solution than AI resume screening for post apply screening
Using a conversational medium as your first line of prescreening is superior to using a resume parsing tool. Using a conversational format addresses many of the issues caused by resume parsers. Regardless of whether the information is present on a resume, you can use a chatbot to get all the information you need to pre-screen your candidates like skills, location, and years of experience.
The additional benefit a conversational screening format offers is that you can automatically transition qualified candidates to phone screens and provide feedback to unqualified candidates in real-time.
Using a conversational format instead of resume parsing is the right choice for your time to hire, candidate experience, and data quality. However, there’s a lack of understanding in the marketplace about the differences between types of recruiting chatbots as well as the other effects they can have beyond improving your efficiency.
Consider this question, have you ever had a bad experience with a chatbot?
Most of us have.
Many recruiting chatbots available on the market today will miss the intention of candidate messages and even get stuck in never-ending loop cycles where they respond with “I didn’t understand, can you try rephrasing your question?”
Besides their tendency to create a frustrating candidate experience, recruiting chatbots can’t be relied on to reliably gather data from candidates. Recruiting chatbots and enhanced chatbots struggle to understand user intent resulting in them overlooking important data a candidate might share.
Finally, recruiting chatbot vendors don’t have documented AI Governance Processes and many chatbot vendors don’t staff Conversation Design teams which means they don’t know if they are infecting their customers hiring processes with unconscious bias.
Still recruiting chatbots are far more engaging, create a better experience, and introduce less potential for bias than AI resume parsers. So, using some sort of conversational recruiting automation to gather data from candidates is the right choice, but which one?
You have 3 options here for post apply conversational screening and engagement: recruiting chatbots, enhanced chatbots, or conversational AI.
Post Apply Screening Wars: Compare and Contrast Recruiting chatbots, Enhanced Chatbots, and Conversational AI
Here we’ll compare and contrast recruiting chatbots, enhanced chatbots, and conversational AI.
3 factors will be considered:
- What kind of candidate experience do they create? Will they Engage or Frustrate your applicants?
- How do they address unconscious bias in recruiting? Will they Protect you or Expose you?
- What kind of efficiency gains will they produce? Strong or Weak.
Recruiting Chatbots and Bias:
A recruiting chatbot offers the candidate a multiple-choice response to its query. “Are you licensed to work as a nurse in CA?” If the candidate needs clarification, maybe they are new to the country and don’t know what the acronym CA stands for, they’re out of luck.
A recruiting chatbot will Expose you to a lot of unconscious bias. Something as small as whether a recruiting AI uses an acronym or not can introduce unconscious bias to your hiring. Remember that the AI solution you choose initially will likely be the one you scale to all of your jobs. Without the Conversation Design that goes into making CAI, odds are a recruiting chatbot will create bias.
Recruiting Chatbots and Efficiency:
A recruiting chatbot is only able to rigidly follow its path and has limited NLP. If the candidate responds “No” the chatbot ends the conversation. What if the candidate was licensed to work in any of the other 51 states? You just lost a potentially qualified candidate.
A recruiting chatbot will create Weak improvements to efficiency.
Recruiting Chatbots and Candidate Experience:
If the candidate selects “Yes” the chatbot asks about years of experience. Here the candidate responds with extra information. A recruiting chatbot isn’t able to understand the candidate’s intent.
A recruiting chatbot will Frustrate many of your applicants.
It’s looking for a single number or a phrase similar to “# years”. When candidates feel like they aren’t understood, they get frustrated. This candidate may abandon your hiring process and form a negative perception of your company.
A recruiting chatbot is better than a resume parsing tool, but it’s not ideal.
Enhanced Recruiting Chatbots and Bias:
We’ve built the only conversational AI for recruiting available on the market today. Furthermore, we’re the first and only recruiting AI company to place such a huge emphasis on Conversation Design and AI Governance. I’ve noticed that recently, some enhanced recruiting chatbot vendors are starting to claim they’re conversational AI as well. They aren’t.
None of them have even started to talk about the importance of conversation design or AI governance. It’s just not built into the culture of their companies or the foundation of their product. Still, as public awareness has grown over 2020 around diversity and unconscious bias, it’s possible that enhanced recruiting chatbot companies may have started to consider the way their chatbots understand language, ask questions and respond.
But without conversation design teams, without spending years iterating and developing conversation templates, and without having carefully buildt their AIs from day 1 to protect diversity – enhanced recruiting chatbots are a toss up when it comes to how much they expose you to unconscious bias.
The degree of unconscious bias exposure enhanced recruiting chatbots expose you to will varies from a little to a lot from vendor to vendor. It’s unknown and unpredictable. Be wary when you purchase and ask smart questions to their sales reps.
Enhanced Recruiting Chatbots on Candidate Experience and Efficiency:
An enhanced recruiting chatbot is very similar to a recruiting chatbot. It’s just got some NLP capabilities. Like recruiting chatbots, enhanced chatbots will alternate between offering multiple-choice response selection to candidates and free form responses.
The difference is that enhanced chatbots are better able to understand the candidate.
Here when the candidate responds with “I’ve been working as a nurse for the last 8 years at Clark Medical” the enhanced chatbot is able to understand years of experience. It also creates a better experience for the candidate by confirming that they’ve met the minimum for the role.
This is good.
One of the issues with an enhanced chatbot is that it isn’t able to understand candidate intent. When it’s asking about years of experience it only cares about years of experience.
Enhanced Recruiting Chatbots make candidates repeat themselves and that can cause some to drop off and disengage. Still, an enhanced recruiting chatbot will product efficiency gains that you are happy with. That is, until you decide to scale your use of it beyond a single job or two. Enhanced Recruiting Chatbots produce weak efficiency gains but it’s not because their conversations are so horrible that candidates drop off – candidates don’t really mind engaging with an enhanced chatbot.
I’ve rated Enhanced Recruiting Chatbots as Weak for producing efficiency gains because they are hard to scale and deploy to additional jobs and locations. Enhanced Chatbots don’t come with a Conversation Cloud like a conversational AI platform does. That puts the onus on their customers to design every conversation themselves. As a result, their customers take longer to deploy enhanced chatbots to more jobs and create conversations that aren’t as engaging as they could be. The net result is an efficiency gain that gives their customers great improvement on paper and engagement metrics but doesn’t actually translate into time or money saved.
Anything additional that is shared by the candidate here is lost. Furthermore, an enhanced bot is rigid. It wants the candidate to follow the conversational order its on and doesn’t allow anything else.
Engaging with a recruiting chatbot or an enhanced chatbot is a lot like filling out a form one line at a time via a text message exchange. It’s rigid and the fact that it’s supposed to be a conversation means they still will Frustrate your candidates.
Final Verdict: Better conversational experience and efficiency than a basic chatbot. Lack of consistency in vendor approaches to building the AI powering them and in designing the understanding and use of language these AI-powered chatbots makes them risky on a bias front. Any conversation efficiency gains they produce are offset by unsolved challenges that fall to their customers to fix when deploying and scaling these types of chatbots.
A conversational AI is the most sophisticated form of a chatbot. A conversational AI employs advanced natural language processing (NLP) and machine learning (ML) techniques. These technologies provide a conversational AI with the skills it needs to communicate like a human and pick up on details in conversations.
In fact, candidates often mistake conversational AI(CAI) for humans. It’s not surprising, given that during a conversation CAI can understand context and intent, recognize ideas outside of context, and navigate back to the original topic.
In the nursing screening interaction happening above a CAI provides a strong positive candidate experience and is able to gather far more data about the candidate than a chatbot or enhanced chatbot.
The robustness of conversational AI means it allows the candidate to lead at times in the conversation just like a recruiter would. It also is more flexible than a chatbot or enhanced chatbot.
Because it doesn’t limit the candidate to a multiple-choice response to the first question, a CAI is able to uncover important candidate data.
Notice that the CAI is able to pick up on the extra information the candidate shared in response to “Are you licensed to work as a Nurse in CA?”
It was also able to associate the California location data point with its 3rd response. It confirmed that openings were available in California, shared a few cities from CA, and shared that it had openings in 28 other cities in CA.
With a CAI, you can offer more information to your candidates earlier in the process. This prevents qualified candidates from disqualifying themselves due to incomplete information.
Resume parsing tools, recruiting chatbots and enhanced chatbots simply can’t offer the strong candidate experience performance of conversational AI.
But what about the exposure to unconscious bias and efficiency? Read on in the next sections to learn how CAI gives you strong protection against bias and amazing efficiency gains from every angle.
Natural language processing is the keystone of effective AI resume screening
If you value your candidate experience, if you want to prevent unconscious bias from infecting your hiring process, and you need to create the biggest possible efficiency gain to do more less, you should use Conversational AI to manage your pre-screening instead of AI resume parsing or a recruiting chatbot.
Let me tell you a few things about Mya. Our company is called Mya. Mya is also the name of the most advanced conversational AI recruiting assistant on the market, which we built. Finally, you can also use Mya to refer to our conversational AI platform for recruiting. (It’s how we made it easy for our customers to try, deploy, and scale AI to solve their most pressing recruiting challenges across hundreds of roles, all of their locations, and in multiple languages.)
Introducing Safest, Most Efficient, and Most Engaging AI Post Apply Applicant Screening Solution – Mya Recruit
Mya Recruit is a product that’s part of our conversational AI platform. You can use RPA to deploy Mya, our conversational AI recruiting assistant, to improve the post-application candidate experience and efficiency of your recruiting process. RPA is more engaging, more efficient, and offers you significantly more protection against unconscious bias in recruiting than recruiting chatbots and resume parsers.
What can Mya Recruit Do?
Mya RPA will engage applicants in seconds after they apply, answer their questions, ask them questions, determine if a candidate is qualified, and create a shortlist of the best-fit applicants. If you’d like, you can also have Mya RPA schedule the best-fit applicants for interviews directly on your recruiters’ calendars. With RPA, Mya will even handle all cancelation and rescheduling too.
How does RPA create more and better engagement?
What we’ve found is that because Mya RPA deploys the most advanced conversational AI recruiting assistant on the market, we create extremely high engagement rates. RPA keeps candidates engaged post apply, the completion rate for RPA screening remains high, and best of all it even increases the completion rates of any other subsequent screening you might include in your application process.
How does Mya RPA give me the most comprehensive protection against unconscious bias in recruiting?
Unlike recruiting chatbots or AI resume screeners which would expose you to serious risk through unconscious bias, Mya RPA has been proven to improve the diversity of candidates considered and hires made. For one of our clients, a Fortune 500 global cosmetics company, Mya RPA improved the diversity of their hiring pool by 30%!
To reiterate, as you learned earlier in the article, AI Resume Screeners often have flawed AI algorithms. For example, did you know that Amazon built an AI resume screening solution? They discontinued it immediately because it showed a bias for white male engineer resumes. The effect of AI resume screening solutions for sale today have on diversity is largely unknown!
Unlike AI resume screening tools, we’ve established a strict, well documented, and intentional AI Governance Process here at Mya. Any type of AI or automation can increase efficiency. But we believe that recruiting AI performance should actually be defined by its impact on diversity, inclusion, and candidate experience. Our AI Governance Process ensures the data we use to train Mya, the way Mya understands intent & language, and the teams that build Mya protect our AI and our customers from the threat of unconscious bias.
How does Mya RPA give me the best support to scale post apply AI screening to more of my jobs?
Finally, unlike recruiting chatbots Mya RPA uses Conversation Design. Our Conversation Design team, Conversation Templates, and Conversation Cloud are some of the things we’re very proud of that make us different. Recruiting chatbot companies don’t have Conversation Design teams. We use professionally trained linguists, language annotators, and conversation reviewers to optimize every word of a Mya conversation. Next, one job at a time, we’ve created RPA Conversation Templates that cover hundreds of jobs our customers are hiring for. All of these RPA Conversation Templates live in the Mya Conversation Cloud.
When our RPA customers want to use Mya RPA to engage, screen, and schedule applicants for a job, we pull the appropriate Conversation Template from the Conversation Cloud. Our Conversation Design and Customer Success team customize the template for our customers and ensure its free from biasing and disengaging factors.
If you want AI that values diversity, inclusion, and candidate experience as much as you do. If you don’t want to be forced to compromise on recruiter experience, technology integration, efficiency, and price. If you want screening automation that also handles scheduling and improves the performance of your entire post apply recruiting funnel through strong engagement.
And if you want the best support, the most powerful set of complementary AI products and access to the best AI recruiting conversations in the industry.
What you truly want and need is our conversational AI recruiting assistant, our conversational AI platform, and Mya Recruit.
Resume parsing tools, recruiting chatbots and enhanced chatbots can’t even hold a candle against what you can accomplish with conversational AI. For a more diverse, more engaged, higher quality candidate pipeline and a faster time to hire – look no further than Mya RPA.