Candidates Form First Impressions From Company Content Well Before The Job Posting
The application journey that candidates are on is very different today than it was a year ago, and certainly what it was three years ago. Recruitment marketing now needs to be part of everything else an organization is doing.
Steven Albert
K+ Director of Talent Acquisition
Spring Education Group
Candidates used to meet an employer through a job posting written by a recruiter. An employment search that begins on Google now routes through an AI assistant, which pulls from landing pages, forum threads, and whatever else the model judges relevant. By the time a candidate reaches the job description, it may be the third or fourth thing they’ve seen about the company. Much of what an AI model surfaces was written by someone at the employer, for a purpose that may have had little to nothing to do with hiring.
Steven Albert is K+ Director of Talent Acquisition at Spring Education Group, a network of more than 200 schools nationwide. He moved into the role in March 2025 after three years building the company’s talent function, following earlier stints at Fusion Academy and a Boston charter school. Albert holds a master’s in education with a specialization in urban education and leadership. His team is currently auditing content written for other audiences entirely, including parent-facing pages built to drive school enrollment.
“The application journey that candidates are on is very different today than it was a year ago, and certainly what it was three years ago. Recruitment marketing now needs to be part of everything else an organization is doing,” says Albert. Control over that first impression is now spread across the organization. A talent team that wants to gain influence has to work through the departments that own the content strategy.
A wider content footprint
An AI assistant building a response about a job doesn’t check who the source material was written for. In Albert’s case, enrollment marketing aimed at parents, operational announcements about new school openings, and coverage of problems at a particular location can all appear in the same answer. The candidate reads it as their overall perception of the employer.
Albert’s team began auditing content across the organization in response. They’re also working through landing pages and social accounts that sit outside talent acquisition entirely, asking what each one contributes to the picture a candidate assembles. “Organizations do need to be mindful of all of the content they have out there for recruitment marketing purposes,” Albert notes. “A few years ago, we had a very narrow lens of our recruitment marketing materials.”
The AI fluency gap
By Albert’s estimate, everyday users have been fluent in AI for only about eighteen months, and many have decided not to pick it up. Candidates in that group search the way they did a decade ago. A process tuned only for machine readability can leave this cohort unable to find the opening at all.
Albert’s team caps the application pathway at under seven clicks, counting every step from the listing to a submitted form. Whatever route a candidate took to the listing, the application itself stays the same short sequence of steps. “When we’re hiring a social studies teacher, we’re not hiring an expert in AI recruitment marketing,” he says. “They should not need to be, or even have an understanding of it, to find our job and apply for it.”
The candidate-side test
Albert tests candidate-facing automation by reading it as the candidate would. A job seeker who has sent thirty applications in two weeks is getting email from most of those employers. Confirmation that an application arrived gives that person a fact they didn’t have. A reminder every two days that the review continues repeats something they already know.
Messages built only to generate an open rate teach people to ignore the sender, and Albert has watched his own inbox fill with them. He applies a different standard on the recruiter side, where automation genuinely speeds up candidate review and his team uses it. A platform offering a candidate-facing feature is not a reason to switch it on. “If there isn’t a clear call to action, or there isn’t something that you receive that benefits you as the candidate, then to me it’s noise,” Albert says.
What automation gives back
The pitch for automating a task is that it frees people from work that distracts from priorities, and the returned time only counts for something if the organization spends it deliberately. Albert has watched the default answer become a reduction in headcount, which carries a risk of its own. “Organizations will shrink their teams, you’ll become leaner and leaner, and then if the tools stop working for you, you don’t have enough people to complete that work,” he says.
Albert’s alternative is to hold headcount and update the job duties. A team handed back hours could build a more human onboarding experience, rebuild a partnership with operations, or take initiatives away from leaders elsewhere in the business. “What’s really not being talked about is what do people actually do in talent acquisition and human resources,” Albert notes. “If we’re using AI to replace some functions, is there value that those individuals can add in a different capacity?”
The capacity Albert has in mind is human judgment on the decisions that affect people. He can’t control the journey a candidate takes to the application, so he’s deliberate about everything after it, from the length of the pathway to who reviews what comes back. “Let’s have the humans be the lower funnel activity, and ensure that the automation doing top of funnel is valuable,” Albert concludes. “The decision makers are still the decision makers, not the tools we put in place to help them.”
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TL;DR
Steven Albert
Spring Education Group
K+ Director of Talent Acquisition
K+ Director of Talent Acquisition
Candidates used to meet an employer through a job posting written by a recruiter. An employment search that begins on Google now routes through an AI assistant, which pulls from landing pages, forum threads, and whatever else the model judges relevant. By the time a candidate reaches the job description, it may be the third or fourth thing they’ve seen about the company. Much of what an AI model surfaces was written by someone at the employer, for a purpose that may have had little to nothing to do with hiring.
Steven Albert is K+ Director of Talent Acquisition at Spring Education Group, a network of more than 200 schools nationwide. He moved into the role in March 2025 after three years building the company’s talent function, following earlier stints at Fusion Academy and a Boston charter school. Albert holds a master’s in education with a specialization in urban education and leadership. His team is currently auditing content written for other audiences entirely, including parent-facing pages built to drive school enrollment.
“The application journey that candidates are on is very different today than it was a year ago, and certainly what it was three years ago. Recruitment marketing now needs to be part of everything else an organization is doing,” says Albert. Control over that first impression is now spread across the organization. A talent team that wants to gain influence has to work through the departments that own the content strategy.
A wider content footprint
An AI assistant building a response about a job doesn’t check who the source material was written for. In Albert’s case, enrollment marketing aimed at parents, operational announcements about new school openings, and coverage of problems at a particular location can all appear in the same answer. The candidate reads it as their overall perception of the employer.
Albert’s team began auditing content across the organization in response. They’re also working through landing pages and social accounts that sit outside talent acquisition entirely, asking what each one contributes to the picture a candidate assembles. “Organizations do need to be mindful of all of the content they have out there for recruitment marketing purposes,” Albert notes. “A few years ago, we had a very narrow lens of our recruitment marketing materials.”
The AI fluency gap
By Albert’s estimate, everyday users have been fluent in AI for only about eighteen months, and many have decided not to pick it up. Candidates in that group search the way they did a decade ago. A process tuned only for machine readability can leave this cohort unable to find the opening at all.
Albert’s team caps the application pathway at under seven clicks, counting every step from the listing to a submitted form. Whatever route a candidate took to the listing, the application itself stays the same short sequence of steps. “When we’re hiring a social studies teacher, we’re not hiring an expert in AI recruitment marketing,” he says. “They should not need to be, or even have an understanding of it, to find our job and apply for it.”
The candidate-side test
Albert tests candidate-facing automation by reading it as the candidate would. A job seeker who has sent thirty applications in two weeks is getting email from most of those employers. Confirmation that an application arrived gives that person a fact they didn’t have. A reminder every two days that the review continues repeats something they already know.
Messages built only to generate an open rate teach people to ignore the sender, and Albert has watched his own inbox fill with them. He applies a different standard on the recruiter side, where automation genuinely speeds up candidate review and his team uses it. A platform offering a candidate-facing feature is not a reason to switch it on. “If there isn’t a clear call to action, or there isn’t something that you receive that benefits you as the candidate, then to me it’s noise,” Albert says.
What automation gives back
The pitch for automating a task is that it frees people from work that distracts from priorities, and the returned time only counts for something if the organization spends it deliberately. Albert has watched the default answer become a reduction in headcount, which carries a risk of its own. “Organizations will shrink their teams, you’ll become leaner and leaner, and then if the tools stop working for you, you don’t have enough people to complete that work,” he says.
Albert’s alternative is to hold headcount and update the job duties. A team handed back hours could build a more human onboarding experience, rebuild a partnership with operations, or take initiatives away from leaders elsewhere in the business. “What’s really not being talked about is what do people actually do in talent acquisition and human resources,” Albert notes. “If we’re using AI to replace some functions, is there value that those individuals can add in a different capacity?”
The capacity Albert has in mind is human judgment on the decisions that affect people. He can’t control the journey a candidate takes to the application, so he’s deliberate about everything after it, from the length of the pathway to who reviews what comes back. “Let’s have the humans be the lower funnel activity, and ensure that the automation doing top of funnel is valuable,” Albert concludes. “The decision makers are still the decision makers, not the tools we put in place to help them.”