The staffing industry is at an important inflection point when it comes to the use of AI.
The 2024 State of Staffing report from Staffing Hub found that 48% of staffing firms currently use Al, and 48% of those who don’t, plan to adopt it this year.
Some staffing firms have more or less ignored the advances made possible by AI – either because they prefer to stick to business as usual or because they aren’t exactly sure how to implement AI into their existing processes.
Other firms are diving head-first into the AI universe, experimenting with public AI tools like ChatGPT, Gemini, and Claude.
While all of these tools offer exciting timesaving advantages over manual processes, the industry is just now coming to terms with some of the pitfalls and risks of using AI.
These risks range from shoddy outputs, generating copy misaligned with your firm’s standards, and security risks such as leaking proprietary or private information to public AI models.
Cutting-edge staffing firms are now investing in custom AI integrated into their ATS/CRM database. These firms are training AI models to reflect their specific values, tone, goals, and client needs so that AI-generated content can mimic the content generated by their A-team of recruiters, managers, and executives.
So let’s drill into some example manual recruiting tasks and break down the amount of time it takes to accomplish each using the 3 options here:
- The Manual Way
- The Public AI Way
- The Accelerate Way with Staffing EngineGPT
Task #1: Writing Candidate Submittals
The Manual Way: Up to 30-45 Mins
Manually writing submittals requires recruiters to comb through a job description and a candidate profile in order to get a candidate submitted to an account manager.
Historically, they would write the submittal into a blank Word document or manually adjust a template to meet their needs. Then copy and paste it into an email or into your CRM/ATS.
Depending on their seniority, staffing vertical, and skill level, doing this process manually could take up to 30-45 minutes for every single submittal. Some firms are still choosing not to automate this time-consuming process.
The Public AI Way: 10-15 Mins
Today, many firms are relying on public AI tools like ChatGPT, Bard, and Gemini to help their team craft submittals faster.
A workflow for this method might go like this:
- A recruiter will copy and paste information from the job description and the candidate profile into the public AI tool.
- They create a prompt, asking the AI to generate a submittal based on company standards, account manager needs, the intricacies of the position, and the skills of the paired candidate.
- If they’re doing their due diligence, recruiters will edit and revise the suggested submittal to guard against errors, overgeneralities, biases, and other liabilities.
- Public AI generates a candidate submittal, which the recruiter then copies and pastes into their ATS or CRM for the account manager to review.
This entire process, once becoming part of their routine, could take just 10-15 minutes. However, there are a few possible snags with this method.
First, it requires your team to enter sensitive information into a public AI model, potentially opening your firm up to security risks.
And second, recruiters need to know how to craft the right prompts to generate exactly the output that they need.
Public AI tools are notorious for taking vague prompts into strange places, so unless your team is well-versed in the complex nuances of crafting prompts, they may struggle to get usable results.
The Accelerated Way: 1-2 Mins
The accelerated way includes investing in a custom generative AI model like EngineGPT. This method is a game changer for speeding up your candidate submittals and keeping your private data safe. With a proprietary AI model directly connected to your firm’s database, your recruiters can use the following workflow:
- Enter the job ID
- Enter the candidate ID
- Click Generate.
Within 1 minute, your recruiter will have a completely formatted, standardized submission based on your firm’s preferred formatting. They can then review, edit, and with one click instantly submit the candidate into your ATS/CRM database.
Recruiters don’t need to know how to craft the precise prompt to generate a submittal because that’s all taken care of on the back end by an AI model that is trained on the specific needs of your firm.
Your recruiters can take care of the entire process on a single screen, without losing time and focus by copy and pasting between multiple windows and programs.
This integrated workflow with EngineGPT protects your firm’s privacy by keeping all sensitive information in-house in your database where it belongs.
Task #2: Creating Job Descriptions
The Manual Way: 30-45 Mins
Most likely, you still have a marketing team or account executive crafting job descriptions by hand, often based on the partial or insufficient information provided (perhaps in bulk) by your clients. Sound familiar?
Turning this information into an engaging, accurate job description is a time-consuming task.
One account manager said that doing it the manual way cost him 45 minutes per job description. With a single client dropping a batch of 100 jobs that needed descriptions, this could consume his entire job for 75 hours – nearly two weeks of full-time work.
The Public AI Way: 10-15 Mins
To cut down on this astronomical amount of time, it makes sense that many firms are relying on public AI tools. They can speed up the process and get job descriptions published for clients faster.
This workflow might look like this: an account executive might copy and paste all the information from the client into the public AI tool and craft a prompt to generate a job description.
But, in order to generate usable job descriptions that meet your firm’s standards, the account executive must know how to engineer the precise prompt.
All this information must be copy and pasted repeatedly, and as the executive moves back and forth from the CRM to the AI tool, they lose time and increase the opportunity for formatting issues and errors.
And finally, job descriptions require the kind of sensitive information- such as client’s names, salary offerings, and more- that could pose a security risk to your firm, and to your clients.
The Accelerated Way: 3-5 Mins
With Staffing EngineGPT, your sales and marketing teams can create job descriptions with the click of a button, directly from their existing workflow.
The job description prompts are customized based on your firm’s specific needs, formatted according to your requirements, and written in your preferred tone.
All sensitive information remains within your ATS/CRM database. Including review and edits, the entire process can be done in just a few minutes.
Remember the account manager we mentioned earlier that was generating job descriptions manually?
When he started using EngineGPT, what normally took him 45 minutes was completed in just 3 minutes. He could generate two weeks worth of orders for his clients in less than a day.
The operation manager of his firm reported: “He said, ‘I just spent 45 minutes on one job description and what Staffing Engine produced is better. You mean I can spend three minutes tweaking these job descriptions and just crank them out?’ His mind was blown.”
Task #3: Generating Boolean Searches
The Manual Way: 20-30 Mins
Generating boolean searches is like learning a language. Without a deep understanding of the syntax, grammar, and structure of your search, these searches often end up generating disconnects and errors, or yielding meaningless results.
To run boolean searches manually, recruiting managers need to be taught the ins and outs of the proper search language. This language also may be slightly different depending on your system, which makes it more complex to learn.
That’s why they have entire classes dedicated to learning boolean search for sourcers and recruiters. With such a steep learning curve, getting all of your recruiting managers up to speed can be time-consuming, and costly.
The Public AI Way: 10-15 Mins
Public AI tools can help shorten the amount of time it takes to create these boolean searches, but your recruiting managers still need to understand the basics of boolean language to implement these searches appropriately.
Without this basic understanding, the AI-generated boolean searches can yield unpredictable results because your team must be able to triage or troubleshoot the output.
Your team will also have to copy and paste search parameters or requirements from your CRM or ATS, upping the possibility of user error.
And, perhaps more importantly, to get a truly targeted boolean search, your recruiting managers will often have to input proprietary information into a public knowledge model, which leaves you and your clients liable and exposed.
The Accelerated Way: 1-2 Mins
With a custom Staffing EngineGPT AI model tied into your database, your recruiting managers can seamlessly generate boolean searches directly from job descriptions, all without any data leakage or even switching screens.
They can make adjustments to accommodate their needs and make their searches broader or narrower, all using the user interface they’re already familiar with.
Without having to take a course on boolean searches or waste time with inaccurate or incomplete results, your recruiting managers will save time and generate the best placements for your clients faster.
Task #4: Pre-Screening Candidates
The Manual Way: 10-15 Mins
Generating lists of pre-screening questions may at first seem like a straightforward task.
But, to do it manually, your recruiters must review candidates individually, carefully considering their job history, their search activity, client needs, skill requirements, and more to get that perfect blend of questions that ensure a good fit.
For every interview, it can take your recruiter 10-15 minutes to generate these questions. Multiply that by every candidate interviewed for every position you’re hiring for and pre-screening questions alone are taking up a lot of your team’s time.
The Public AI Way: 5-10 Mins
To generate pre-screening questions with public AI, your recruiters can copy and paste candidate data and job data into the tool and prompt it to generate questions that will help you get a good fit.
But this process has the same drawback as using public AI for other facets of your recruiting cycle. It requires a lot of clicks, which slows down your recruiting cycle, opens your team up to distractions and misdirected information.
By sharing candidate and job data with a public AI system, you can’t control where this information goes, how it is used, or how it might show up for competitors who are attempting to replicate the same process for their own firms.
Further, because pre-screening questions take a certain kind of finesse, the generalized nature of public AI, which is not built for your staffing firm, can lead your recruiters astray with pre-screening questions that don’t meet your needs, aren’t grounded in the values of your company, and don’t best serve clients or candidates.
The Accelerated Way: 1-2 Mins
With Staffing EngineGPT, generative AI is tied into your database. This means that your recruiters can compare candidates to the job order and compare individual skills to your clients’ needs.
They can also choose either the job description or the candidate and generate the best matches for each – automatically.
From there, recruiters can choose how many prescreening questions to generate to determine if candidates are a good fit for a specific position.
By now it’s clear – firms using fully manual processes will quickly be left behind as their competitors start leveraging the ever-evolving power of AI.
But firms that are relying too heavily on public AI may find that they are leading their teams down a losing path, too.
For more information on how Staffing Engine’s proprietary Recruiting Acceleration™ AI and custom generative AI can help your staffing firm, click here.
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