February 9, 2026
RogerUtting/Depositphotos.com
How Will Automated Hiring Change Frontline Retail?
In a conversation curated by Chain Store Age senior editor Dan Berthiaume, 7-Eleven’s Rachel Allen, head of talent acquisition for the c-store giant, outlined a case study as to what frontline hiring could look like in the retail and service industry moving forward.
Allen noted that the company currently uses a mixture of recruiting contractors, Workday Paradox Candidate Experience, and Paradox Conversational Applicant Tracking Software to streamline its hiring process, all leading up to the all-important in-person interview of applicants by store management figures.
“There are a few ways applicants can start to connect with us. We have QR codes at our stores and on our website that they can scan to start texting with our assistant named RITA, which stands for recruiting individuals through automation,” Allen said.
“RITA will then start the conversation with them to initially do things like share their name and what store they are interested in applying to. Then we need to collect some information specific to being authorized to work and having an application on file which RITA helps accomplish through text,” she added, noting that the next step was an automatically scheduled store-level interview. Store managers can switch RITA on and off at will, depending on staffing requirements at any given time.
Interesting factoids pulled from the remarks offered up by the 7-Eleven exec:
- The move to recruiters followed 7-Eleven’s 2021 acquisition of Speedway, which had hundreds of recruiters in the field: These recruiters helped to drum up applicant interest in staffing various 7-Eleven locations, whereas previously the hiring model relied solely on store-level management.
- Unified, automated hiring cuts speed-to-candidate and ghosting issues: Allen noted that previous to relying on automated solutions and contracted recruiters, it was taking 7-Eleven nearly two weeks to hire a new worker. Further, many hires were simply ghosting, never showing up. The new, unified hiring system has cut hiring times down to three days, retention has improved, and perhaps most importantly — quality of the hires has increased.
- Store leadership saves hours, and more: Allen underlined the massive boost that automating the vast bulk of the hiring practice had been for the company at all levels. “We have saved our store leaders about more than 40,000 hours a week, which is over 2 million hours a year, in time saved by automating 95% of the hiring process for them, which was a huge win. 7-Eleven is also now able to be more strategic in where we put our recruitment marketing dollars to the level of an individual store, as far as where we may need have some needs,” she stated.
Moving forward, 7-Eleven plans to double down on the automation aspect by shifting to agentic tech support — but before doing so “we want to make sure we have the foundation set for any agents coming into the picture, whether it’s HR or somewhere else in the business,” Allen said.
Perhaps anticipating criticism of this move toward AI-driven hiring, support, and other operational solutions, Allen was keen to highlight that (in her view), this approach was more of a supplementation of pre-existing human-driven capabilities. Agents are there to support person-to-person interactions within the 7-Eleven ecosystem, rather than outright replacements.
BrainTrust
Shep Hyken
Chief Amazement Officer, Shepard Presentations, LLC
Doug Garnett
President, Protonik
Cathy Hotka
Principal, Cathy Hotka & Associates
Recent Discussions
Discussion Questions
Given 7-Eleven’s example, how will automated hiring change frontline retail moving forward? Are there any obvious drawbacks, in your opinion?
Do you believe automated hiring practices will become commonplace in retail operations over the next five years? Why or why not?
What hiring processes should always remain in the hands of humans?
Poll
Loading …
It depends on what the automation is being used for. General filtering of candidates based on their knowledge and responses to basic questions is probably sensible. Basic admin like scheduling interviews, following up and so forth is also logical. Using AI to make qualitative judgements – like interpersonal skills – is not such a good idea!
Human in the Lead should be the foundation of designing automated hiring processes. Candidate lifecycles inherently have many bottle necks that benefit from implementing automations and centralized workflows. However at scale the bottlenecks will move further down the hiring process and it is critical a Human is making the hiring decision and dispositions of the candidates.
Efficiency is important. If automation can help speed up the application process, everyone (both the applicant and the company) wins. Keep in mind that “help speed up the application process” does not mean take it over from beginning to end. It can take over the beginning, but at some point, human-to-human interaction is important. Imagine the manager who can save hours a week by automating the early stages of the process. That manager can focus on more important tasks other than sifting through the applications to find someone to interview.
Will automated hiring practices become commonplace? For the reasons above, I’m surprised they aren’t already!
Final interviews cannot be replaced with automation. In retail, the personal connection (human-to-human skills) is important. The face-to-face interview provides the final piece of the process.
This feels like a strong use of AI for the parts of hiring that don’t require judgement, like collecting basic information or scheduling interviews. Where it gets harder is when the process isn’t straightforward. Reschedules, exceptions, or personal circumstances will still require human oversight. I also wonder how this will translate beyond entry-level roles, where more context is often needed upfront.
All automated hiring is a disaster. Before AI, companies had begun pulling back from their dependence on algorithmic sorting of applications because it is a miserable failure. Unfortunately, AI hype has led them to, once again, refuse their responsibility to customers and trust in the almighty algorithm. Partly, automated hiring ensures companies will NOT have the diversity of frontline employees needed to overcome misdirections of company policies to ensure customers value the company. In part, it is impossible for automated hiring to learn. While can learn which hires “didn’t work,” it cannot ever learn which hires were rejected but should have been hired. The only path of automated hiring, then, is to become ever more conservative — which ensures lower and lower diversity of hires making a company more and more unhealthy.
There are numerous things that automated hiring can do to streamline the process. First, I would like to see the name changed from “hiring” to ‘recruitment screening.’ Candidates are NOT automatically hired. AI can be used to understand more about a candidate’s likelihood to be successful and remain employed by identifying key traits or attitudes prior to engaging in a personal interview with store managers.
If the main component of hiring – or at least one of the main components – remains an interview – as is inferred here – I’m not sure AI makes much difference. But if we reach the point that the interview itself is with a chabot, let’s talk…pun intended.
Automation Isn’t about replacing human judgment, it’s a tool to help store managers find employees more easily, not directly choose who to hire.
Having hired many people over the years, I cannot ever see turning 100% of employee hiring over to AI. Building the right team is, and always will be, a people skill.
This has been a prominent topic at meetings of the Store Operations Council. Would-be candidates apply, then promptly seem to disappear. Candidates never get a status update. What a mess. Maybe it’s time for some human intervention.
How can you evaluate and grade a hiring process without evaluating and grading the post-hiring results? How about a little conversation about the quality and longevity of those hired? Strong performers with meaningful long term contributions, or weak performers that turned over in a month? Quick and efficient is only efficient if it did indeed serve up candidates that performed and had tenures as good or better than any analog processes. I’m reminded of the old adage that says if the 3 metrics are quality, cost and speed, you can only ever get 2 out of 3. Getting something of good quality, fast, is not going to be inexpensive. Getting something fast and inexpensive is not going to be high quality. So what kind of batting average does this process enjoy?
I really like the framework you laid out here Jeff on quality, cost, and speed. It’s clear AI can improve cost and speed, which leads us to debate quality. By addressing cost and speed, AI allows us to focus on quality. We can move and concentrate people resources more exclusively there. To your point, time will tell if/when AI can handle the quality part, but even if it cannot do so directly, by addressing the other 2 parts (cost/speed) it affords us the opportunity to. Now, of course, we just need to be sure we know how to successfully define what a “quality” hire is.
Perhaps, the framework you outlined is the test for gauging if and when AI truly comes of age in recruiting/hiring…if and when it can ever batt 1.000 and achieve 3 out of 3.
Great way to put it. Thank you. I am also reminded of the axiom that says something to the effect of “Hire for attitude, not skills. Skills can be taught far easier than attitude.” Can AI be taught to identify attitude, or is that late stage discovery for the humans to identify?
Agreed and good questions. What’s missing is the particularly critical question which cannot be answered: Who did we reject but should have hired? A well known reality of algorithmic screening is that it rejects people who should be hired, taken on as tenants, or any of many other roles — but we can never know who those people are.
Automation in hiring will likely become a practical tool for high-volume frontline recruiting, particularly in environments such as convenience, grocery, or big-box retail, where speed and scale are critical. Screening applications, scheduling interviews, and handling repetitive administrative tasks can reduce friction for both candidates and employers, helping retailers fill roles faster and keep stores adequately staffed. Used thoughtfully, automated hiring can also improve consistency by reducing human bias in early screening and allowing recruiters to focus on candidate experience rather than paperwork. The drawback, however, is that automation often evaluates candidates against rigid criteria — and that can unintentionally exclude strong prospects whose experiences don’t perfectly match a predefined checklist.
Looking ahead, I do believe automated hiring practices will become more commonplace over the next five years, but primarily as decision-support tools rather than full replacements for human judgment. Retailers operate in fast-moving labor markets, and AI-enabled recruiting can help manage volume and reduce time-to-hire. That said, overreliance on automation risks reducing hiring to a purely transactional process, thereby overlooking candidates with unconventional backgrounds who could bring creativity, resilience, or cultural leadership to a team. The challenge will be striking the right balance between efficiency and human insight.
Certain hiring decisions should remain firmly in human hands — especially for managerial and leadership roles. Automation today struggles to evaluate the nuanced value of diverse life experiences, adaptability, emotional intelligence, and leadership presence — qualities that often define effective retail leaders but may not align neatly with a job description or algorithmic scoring model. High-touch interviews, mentorship evaluations, and cultural fit discussions are areas in which human judgment remains essential. In my view, automation should handle the heavy lifting at the top of the funnel, while humans remain accountable for the final decisions that shape an organization’s culture and long-term success.
For an industry with the highest turnover rates in the market and seasonal temp hiring, automation is a fitting tool for the frontline. However, someone mentioned that this is just recruitment screening and effectively a background check rather than a real, automated hiring process. They are spot on. The solution works as an applicant tracking system, automated data/form collector, and perhaps a scheduling tool. However, the end result is efficiency, not quality of hire. More importantly, this won’t be a revolutionary change to hiring retail associates. It just brings retailers up to modern hiring practices.
Yet I would expect even automated screening will INCREASE retention problems leading to a spiral of ever shorter tenures.
Automation will make frontline hiring faster and more manageable, especially for high-turnover roles where speed matters. Removing manual steps like application screening and interview scheduling can take real pressure off store managers and reduce candidate drop-off. Most retailers have struggled with slow hiring cycles for years, so the efficiency gains here are meaningful.
Where retailers need to be careful is letting automation move beyond support and into decision-making. Frontline roles still depend heavily on reliability and how someone interacts with customers, and those qualities are best judged in person.
In my experience, automation works best when it handles the early steps and frees managers to spend more time with candidates, not less. Used that way, it can improve both hiring speed and quality without losing the human element that stores still depend on.
Today’s headline was an eye-opener. “Really?”, I thought. But after reading the discussion, it is not at all like that. It is automated recruiting and screening. The idea that automation would replace personal interviews is an overreach by people who don’t understand people.
I’m not sure where the automation begins and the human needs to be involved. I have heard for years how bad the hiring process is so does some level of AI automation help or hurt an already inefficient process?
More Discussions
Will a Hybrid Pharmacist Role Help Solve Labor Issues for Walgreens?
Will a Hybrid Pharmacist Role Help Solve Labor Issues for Walgreens?Should Burger King’s President Be Giving Out his Cell Phone Number?
Will this move by Burger King’s Tom Curtis drive meaningful results?How Much Of A Discount Drives New Grocery Trial?
How Much Of A Discount Drives New Grocery Trial?
It depends on what the automation is being used for. General filtering of candidates based on their knowledge and responses to basic questions is probably sensible. Basic admin like scheduling interviews, following up and so forth is also logical. Using AI to make qualitative judgements – like interpersonal skills – is not such a good idea!
Human in the Lead should be the foundation of designing automated hiring processes. Candidate lifecycles inherently have many bottle necks that benefit from implementing automations and centralized workflows. However at scale the bottlenecks will move further down the hiring process and it is critical a Human is making the hiring decision and dispositions of the candidates.
Efficiency is important. If automation can help speed up the application process, everyone (both the applicant and the company) wins. Keep in mind that “help speed up the application process” does not mean take it over from beginning to end. It can take over the beginning, but at some point, human-to-human interaction is important. Imagine the manager who can save hours a week by automating the early stages of the process. That manager can focus on more important tasks other than sifting through the applications to find someone to interview.
Will automated hiring practices become commonplace? For the reasons above, I’m surprised they aren’t already!
Final interviews cannot be replaced with automation. In retail, the personal connection (human-to-human skills) is important. The face-to-face interview provides the final piece of the process.
This feels like a strong use of AI for the parts of hiring that don’t require judgement, like collecting basic information or scheduling interviews. Where it gets harder is when the process isn’t straightforward. Reschedules, exceptions, or personal circumstances will still require human oversight. I also wonder how this will translate beyond entry-level roles, where more context is often needed upfront.
All automated hiring is a disaster. Before AI, companies had begun pulling back from their dependence on algorithmic sorting of applications because it is a miserable failure. Unfortunately, AI hype has led them to, once again, refuse their responsibility to customers and trust in the almighty algorithm. Partly, automated hiring ensures companies will NOT have the diversity of frontline employees needed to overcome misdirections of company policies to ensure customers value the company. In part, it is impossible for automated hiring to learn. While can learn which hires “didn’t work,” it cannot ever learn which hires were rejected but should have been hired. The only path of automated hiring, then, is to become ever more conservative — which ensures lower and lower diversity of hires making a company more and more unhealthy.
There are numerous things that automated hiring can do to streamline the process. First, I would like to see the name changed from “hiring” to ‘recruitment screening.’ Candidates are NOT automatically hired. AI can be used to understand more about a candidate’s likelihood to be successful and remain employed by identifying key traits or attitudes prior to engaging in a personal interview with store managers.
If the main component of hiring – or at least one of the main components – remains an interview – as is inferred here – I’m not sure AI makes much difference. But if we reach the point that the interview itself is with a chabot, let’s talk…pun intended.
Automation Isn’t about replacing human judgment, it’s a tool to help store managers find employees more easily, not directly choose who to hire.
Having hired many people over the years, I cannot ever see turning 100% of employee hiring over to AI. Building the right team is, and always will be, a people skill.
This has been a prominent topic at meetings of the Store Operations Council. Would-be candidates apply, then promptly seem to disappear. Candidates never get a status update. What a mess. Maybe it’s time for some human intervention.
How can you evaluate and grade a hiring process without evaluating and grading the post-hiring results? How about a little conversation about the quality and longevity of those hired? Strong performers with meaningful long term contributions, or weak performers that turned over in a month? Quick and efficient is only efficient if it did indeed serve up candidates that performed and had tenures as good or better than any analog processes. I’m reminded of the old adage that says if the 3 metrics are quality, cost and speed, you can only ever get 2 out of 3. Getting something of good quality, fast, is not going to be inexpensive. Getting something fast and inexpensive is not going to be high quality. So what kind of batting average does this process enjoy?
I really like the framework you laid out here Jeff on quality, cost, and speed. It’s clear AI can improve cost and speed, which leads us to debate quality. By addressing cost and speed, AI allows us to focus on quality. We can move and concentrate people resources more exclusively there. To your point, time will tell if/when AI can handle the quality part, but even if it cannot do so directly, by addressing the other 2 parts (cost/speed) it affords us the opportunity to. Now, of course, we just need to be sure we know how to successfully define what a “quality” hire is.
Perhaps, the framework you outlined is the test for gauging if and when AI truly comes of age in recruiting/hiring…if and when it can ever batt 1.000 and achieve 3 out of 3.
Great way to put it. Thank you. I am also reminded of the axiom that says something to the effect of “Hire for attitude, not skills. Skills can be taught far easier than attitude.” Can AI be taught to identify attitude, or is that late stage discovery for the humans to identify?
Agreed and good questions. What’s missing is the particularly critical question which cannot be answered: Who did we reject but should have hired? A well known reality of algorithmic screening is that it rejects people who should be hired, taken on as tenants, or any of many other roles — but we can never know who those people are.
Automation in hiring will likely become a practical tool for high-volume frontline recruiting, particularly in environments such as convenience, grocery, or big-box retail, where speed and scale are critical. Screening applications, scheduling interviews, and handling repetitive administrative tasks can reduce friction for both candidates and employers, helping retailers fill roles faster and keep stores adequately staffed. Used thoughtfully, automated hiring can also improve consistency by reducing human bias in early screening and allowing recruiters to focus on candidate experience rather than paperwork. The drawback, however, is that automation often evaluates candidates against rigid criteria — and that can unintentionally exclude strong prospects whose experiences don’t perfectly match a predefined checklist.
Looking ahead, I do believe automated hiring practices will become more commonplace over the next five years, but primarily as decision-support tools rather than full replacements for human judgment. Retailers operate in fast-moving labor markets, and AI-enabled recruiting can help manage volume and reduce time-to-hire. That said, overreliance on automation risks reducing hiring to a purely transactional process, thereby overlooking candidates with unconventional backgrounds who could bring creativity, resilience, or cultural leadership to a team. The challenge will be striking the right balance between efficiency and human insight.
Certain hiring decisions should remain firmly in human hands — especially for managerial and leadership roles. Automation today struggles to evaluate the nuanced value of diverse life experiences, adaptability, emotional intelligence, and leadership presence — qualities that often define effective retail leaders but may not align neatly with a job description or algorithmic scoring model. High-touch interviews, mentorship evaluations, and cultural fit discussions are areas in which human judgment remains essential. In my view, automation should handle the heavy lifting at the top of the funnel, while humans remain accountable for the final decisions that shape an organization’s culture and long-term success.
For an industry with the highest turnover rates in the market and seasonal temp hiring, automation is a fitting tool for the frontline. However, someone mentioned that this is just recruitment screening and effectively a background check rather than a real, automated hiring process. They are spot on. The solution works as an applicant tracking system, automated data/form collector, and perhaps a scheduling tool. However, the end result is efficiency, not quality of hire. More importantly, this won’t be a revolutionary change to hiring retail associates. It just brings retailers up to modern hiring practices.
Yet I would expect even automated screening will INCREASE retention problems leading to a spiral of ever shorter tenures.
Automation will make frontline hiring faster and more manageable, especially for high-turnover roles where speed matters. Removing manual steps like application screening and interview scheduling can take real pressure off store managers and reduce candidate drop-off. Most retailers have struggled with slow hiring cycles for years, so the efficiency gains here are meaningful.
Where retailers need to be careful is letting automation move beyond support and into decision-making. Frontline roles still depend heavily on reliability and how someone interacts with customers, and those qualities are best judged in person.
In my experience, automation works best when it handles the early steps and frees managers to spend more time with candidates, not less. Used that way, it can improve both hiring speed and quality without losing the human element that stores still depend on.
Today’s headline was an eye-opener. “Really?”, I thought. But after reading the discussion, it is not at all like that. It is automated recruiting and screening. The idea that automation would replace personal interviews is an overreach by people who don’t understand people.
I’m not sure where the automation begins and the human needs to be involved. I have heard for years how bad the hiring process is so does some level of AI automation help or hurt an already inefficient process?