AI in Staffing: How to Move From Experimentation to Real Business Impact 

Artificial intelligence is already making its way into staffing firms. But AI in staffing creates little value simply because another tool has been added to the technology stack. 

The bigger opportunity is to determine where technology can eliminate repetitive work, remove bottlenecks, improve productivity, and give people more time to do the work where human relationships matter most. 

That was the challenge Lauren Jones, Founder and CEO of LEAP Advisory Partners, brought to staffing executives during REACH: A Staffing Executive Masterclass. 

After 28 years in the staffing industry and years spent helping agencies navigate technology and transformation, Jones believes staffing leaders need to move beyond AI curiosity and isolated experimentation. Instead, they need to start examining how work actually moves through their organizations. 

Her philosophy can be distilled into a deceptively simple idea: 

Multiply the human. Eliminate the repetitive. Keep the excellent. 

Doing that requires more than buying technology. It requires leaders to identify the right problems, integrate tools into real workflows, measure their impact, prepare their people for change, and remain deliberate about where humans belong in the process.

Staffing Firms Are Buying AI, but Are They Solving the Right Problems? 

Interest in artificial intelligence is not the problem. 

Jones said LEAP Advisory Partners’ data from clients it has worked with over the previous two years showed that 73% of agencies had active AI in their technology spend. Yet only one in four could identify the workflow the AI tool replaced. 

That disconnect gets to the heart of the challenge. 

A staffing company may purchase an AI sourcing tool, introduce an agent, add a new feature to its ATS, or experiment with generative AI. But if leadership cannot clearly articulate what problem the technology is solving, it becomes difficult to determine whether the investment is working. 

Jones compared the issue to hiring an employee without a job description. 

A staffing firm would not normally bring someone into the organization without defining what that person is expected to accomplish. AI should be treated with similar discipline. 

Before adding another tool, leaders should be able to answer questions such as: 

What task does this replace? 

What bottleneck does it remove? 

What financial or operational return should the organization expect? 

Without those answers, AI can quickly become another line item in the technology budget rather than a driver of better performance.

Start Your AI Strategy by Asking What Gets in the Way 

For staffing leaders wondering where to begin, Jones offered a surprisingly low-tech starting point: 

Ask your people. 

Specifically, ask them: 

What gets in your way every day? 

Jones described working with a 90-person organization whose employees were asked that single question. Their responses uncovered enough bottlenecks to help create an entire year’s AI roadmap. 

But the exercise also uncovered something much simpler. 

Three branches were experiencing Wi-Fi problems. 

The solution cost approximately $30 at each location. 

The story illustrates an important principle: not every operational problem requires an AI solution. 

Sometimes the answer is an AI agent. Sometimes it is automation. Sometimes it is a process change. And sometimes it’s just better Wi-Fi. 

Leaders cannot know which answer is appropriate until they understand the problem. 

Jones cautioned executives against becoming overly prescriptive from the top. Leadership may assume recruiters are being slowed down by resume formatting, sourcing, call notes, or another task. The people actually doing the work may identify an entirely different obstacle. 

An effective staffing AI strategy therefore starts with observation and questions, not software.

Interrogate the Work Before You Automate It 

Jones encouraged staffing leaders to “interrogate” every role in their organization. 

What does this employee do repeatedly? 

What continues to happen before the workday begins, throughout the day, after employees leave, or overnight? 

Those questions helped Jones rethink the operating model inside her own company. 

At the time of the REACH presentation, her 10-person firm was using 34 AI agents, with another 12 being tested. The agents handled activities ranging from reviewing AI newsletters and preparing discovery information to analyzing calls, supporting content production, and performing quality-control functions. 

The goal was not simply to accumulate agents. 

Jones wanted to understand what those agents were giving back to the organization. 

Her team evaluated how long comparable work would take a person and what that time might cost based on market compensation data. That gave the company a clearer way to quantify savings and understand the return on its AI investment. 

This is a fundamentally different approach from starting with a technology demo. 

Instead of asking, “What can this AI tool do?” 

Staffing leaders can ask, “What work should we be doing differently?” 

Automating a Broken Process Only Makes It Break Faster

One of Jones’ strongest warnings concerned a mistake that predates artificial intelligence: automating processes that do not work well in the first place. 

As she put it during REACH: 

“When we put AI on something that is broken, all it does is speed up the disaster.” 

Technology can accelerate a workflow. It does not necessarily make that workflow better. 

If recruiters follow an inefficient process, adding automation may simply allow the organization to perform that inefficient process more quickly and at greater scale. 

That is why process evaluation should precede automation. 

Jones used ATS implementations as an example. Her approach is generally to establish the ATS process first and introduce automation afterward. Employees need to understand the workflow and build the appropriate habits before additional technology is layered on top. 

This distinction matters as staffing companies face pressure to adopt AI quickly. 

Speed of adoption is not the same as quality of adoption. 

The better question is whether the process produces the right outcome manually. If it does not, leaders should fix the process before asking AI to replicate it. 

AI Can Give Recruiters More Time to Recruit 

The potential benefit becomes much clearer when AI is applied to work that genuinely should not consume valuable employee time. 

Jones offered the example of a six-figure recruiter who was spending approximately three hours each day reformatting resumes. 

The question for staffing leaders is not simply whether AI can reformat the resume. 

It is whether reformatting resumes is the best use of a high-performing recruiter’s time. 

Every hour consumed by repetitive administrative work is an hour that cannot be spent building candidate relationships, speaking with clients, developing expertise, or generating revenue. 

Jones’ operating philosophy is therefore not centered on removing humans from staffing. 

It is centered on putting humans where they create the greatest value: 

AI and automation on repetition. People on relationships. 

That distinction is particularly important in an industry built on trust. 

Candidates still need empathy. Clients still value judgment. Difficult conversations still require context. Relationships still need to be cultivated. 

Technology can help staffing professionals arrive at those conversations faster and better prepared. 

It should not automatically replace the conversations themselves. 

Better Search and Match Can Produce Measurable Results 

Jones also shared an example of a finance and accounting staffing client whose time to submit for highly specialized roles had reached approximately 21 days. 

Even considering the complexity of the positions, that timeline created a significant problem. 

By implementing vector search, which uses semantic and contextual relationships rather than relying only on traditional keyword matching, the organization reduced its time to submit from 21 days to seven days within 30 days, according to Jones. 

That is the kind of AI application staffing executives should be looking for. 

The value is not that the company adopted a sophisticated search technology. 

The value is that it identified a meaningful business problem, applied technology to that problem, and could measure the change in an operational metric. 

Faster search and matching can potentially improve the experience on both sides of the staffing relationship. Clients receive qualified candidates sooner, while candidates can be connected to relevant opportunities more efficiently. 

This is where AI stops being an abstract technology initiative and becomes an operating strategy. 

There Is No AI Transformation Without Integration 

Staffing firms frequently operate across multiple platforms, including ATS and CRM systems, job boards, communication tools, analytics platforms, automation products, sourcing technology, and increasingly AI applications. 

Adding another disconnected system can create more work instead of less. 

Jones’ view is straightforward: 

“There is no transformation without integration.” 

If an AI tool performs a useful function but its output remains isolated from the systems employees use every day, the organization may simply be creating another place employees have to visit, another login to remember, and another dataset to manage. 

Integration should therefore be part of the buying decision. 

Does the tool write information back to the ATS? 

What happens if the tool stops working? 

These questions may not be as exciting as watching an AI demonstration, but they determine whether technology becomes embedded in the business or remains an expensive experiment. 

Ask What Metric the Technology Will Move 

Jones uses a particularly clear test when evaluating technology for her own firm: 

Does it generate revenue or preserve revenue? 

If a technology investment cannot be placed into either category, she questions whether it deserves a place in the technology stack. 

That creates a useful filter for staffing executives. 

A tool might generate revenue by helping recruiters identify qualified candidates faster, improving salesperson productivity, or creating more opportunities for client engagement. 

Another technology might preserve revenue by improving compliance, identifying customer dissatisfaction earlier, reducing errors, or eliminating administrative bottlenecks. 

The exact metric will differ from tool to tool. 

What matters is that there is a metric. 

Jones’ warning to buyers was unequivocal: if a vendor cannot explain what metric its technology moves and how that improvement will be measured, staffing leaders should reconsider the investment. 

Audit Your Existing Tech Stack Before Buying More

Another AI tool is not always the answer. 

Jones noted that staffing companies can accumulate duplicative technology because leaders may not realize that an existing vendor has introduced new functionality. 

Before shopping for another point solution, staffing firms should inventory the tools they already own. 

Which features are actually being used? 

Could an existing platform perform the function the company is considering purchasing elsewhere? 

This scrutiny may become even more important as major technology platforms incorporate more AI functionality directly into their products. 

Jones expects the number of standalone point solutions to decline as broader platforms develop their own AI capabilities. 

For staffing executives, that makes technology discipline increasingly important. 

The goal should not be to assemble the largest tech stack. 

It should be to build the most useful one. 

Clean Data Is Still the Foundation of Effective AI

AI may be changing rapidly, but one decidedly unglamorous requirement remains: 

Good data. 

Jones described clean, tagged, structured data as foundational to strong AI execution. 

Poor data does not necessarily mean a staffing company must delay every AI initiative. In fact, AI itself may be able to assist with aspects of data cleanup. 

But organizations should understand that the quality and structure of the information available to an AI system can influence the quality of what comes back. 

This becomes especially important when firms want to use AI for search, matching, analytics, personalization, or other applications that depend heavily on existing information. 

Staffing firms have spent years accumulating enormous amounts of candidate, client, job, placement, communication, and performance data. 

The ability to organize and use that information intelligently may become an increasingly important competitive advantage. 

AI Agents Can Help Staffing Firms Scale Differently 

One of the most consequential ideas in Jones’ presentation involved the relationship between business growth and headcount. 

Traditionally, when staffing volume increases, companies often respond by adding employees to support the additional workload. 

Jones challenged leaders to reconsider that assumption. 

In the back office, for example, she sees emerging opportunities for digital workers and agents to support tasks involving ledgers, exceptions, timecards, credentialing, and other administrative functions. 

For healthcare staffing firms, she specifically highlighted opportunities around credentialing and compliance. 

The question becomes: 

If payroll increases, does back-office headcount have to increase at the same rate? 

Not necessarily. 

Jones was careful to distinguish this from simply eliminating jobs. Instead, she encouraged executives to examine where people can create greater value. 

If an agent can efficiently manage part of the credentialing workflow, perhaps experienced employees can focus more heavily on compliance, exceptions, customer service, or other areas where judgment is more important. 

The strategic opportunity is scalability. 

AI may allow staffing companies to increase output without automatically increasing administrative overhead at the same pace.

Human-in-the-Loop AI Matters in a People Business

For all her enthusiasm about AI, Jones repeatedly returned to one constraint: 

Human in the loop. 

Staffing remains fundamentally a people business. 

A chatbot may answer routine questions. An agent may analyze information. Automation may move data between systems. 

But there are moments when a candidate or client needs a person. 

Job searches can be stressful and deeply personal. Customer relationships can involve nuance. Compliance decisions can carry meaningful consequences. 

Jones argued that empathy is not something a bot can truly reproduce. 

That means staffing firms need to design escalation into their technology strategy. 

A chatbot should have a path to a human. 

An automated compliance process should have appropriate human review. 

An AI-generated interaction should not become an excuse to remove judgment from situations where judgment matters. 

The goal is not human or AI. 

It is determining where each belongs.

Adoption May Be the Hardest Part of AI Transformation 

Buying technology is relatively easy. 

Changing behavior is harder. 

Jones described many staffing firms as occupying an uncomfortable middle ground: they have several live AI tools, recruiter adoption is uneven, and ROI remains difficult to quantify. 

The technology exists. 

The transformation has not happened. 

This is why training cannot be treated as a single event. 

As AI evolves, Jones believes learning needs to become part of an organization’s DNA. Her own team dedicates regular time to learning because the tools and capabilities are changing too quickly for occasional training to keep pace. 

Build Change Champions Before Go-Live 

For organizations facing employee resistance, Jones recommends identifying change champions before a new technology launches. 

Interestingly, that group should not consist only of employees who already love technology. 

A respected skeptic can become a powerful advocate if leadership can successfully engage that person in the process. 

Change champions can receive early exposure to the technology, participate in training, help test workflows, and support colleagues after launch. 

Jones also recommends support around go-live, including accessible office hours where employees can ask questions in a low-pressure environment. 

The lesson is important: 

Implementation does not end when the software turns on. 

That is when adoption begins. 

AI Training Cannot Be a One-Time Event 

The pace of AI development creates another challenge for staffing leaders. 

A training session delivered six months ago may no longer reflect how a platform works today. 

New capabilities appear. Interfaces change. New risks emerge. Better methods develop. 

Jones therefore encouraged leaders to view AI education as an ongoing operating discipline rather than a project with an end date. 

This matters for both productivity and risk. 

Employees who understand the technology are better equipped to use it effectively, recognize its limitations, protect data, and identify opportunities for improvement. 

Continuous learning also helps demystify AI. 

Recruiters, Jones argued, may actually be particularly well suited to working with these systems because context engineering resembles something they already understand: writing a detailed job description. 

The clearer the instruction, the better the likelihood of receiving a useful result. 

AI literacy does not need to begin with technical expertise. 

It can begin with learning how to communicate a desired outcome clearly.

How Staffing Leaders Can Build an AI Roadmap 

The volume of AI products entering the market can make transformation feel overwhelming. 

Jones’ advice suggests a much more manageable path. 

Start with the work. 

Ask employees what gets in their way. 

Identify repetitive tasks and bottlenecks. 

Determine whether the existing process is worth preserving. 

Then decide whether to eliminate the task, automate it, or apply AI. 

Evaluate whether the proposed solution generates or preserves revenue. 

Define the metric that should move. 

Test the technology with a focused group. 

Integrate it into the workflow. 

Train employees consistently. 

Measure adoption and results. 

Then repeat the exercise. 

Jones described this as a flywheel: organizations should continually revisit their operations and ask where they can become more effective and efficient. 

AI transformation is not one massive technology purchase. 

It is a continuing discipline of improving how work gets done.

The Staffing Firms That Win Will Not Necessarily Buy the Most AI 

The speed of AI development can create an understandable sense of urgency. 

But urgency should not become indiscriminate spending. 

As Jones told the REACH audience: 

“The owners who win aren’t the ones that are gonna buy the most. They’re going to be the ones who are decisive, and then stick to the change.” 

That may be one of the most important lessons for staffing leaders. 

Experimentation is valuable. Jones’ own organization actively tests new tools and agents. But she recommends doing so within a controlled environment rather than exposing an entire workforce to every experiment. 

A small innovation team can test an idea, determine whether it works, and develop a thoughtful approach to implementation. 

That reduces change fatigue while preserving curiosity. 

Staffing firms do not need every new AI tool. 

They need the right technology, applied to the right problems, with the right people prepared to use it.

People, Processes, and Technology Must Work Together 

Lauren Jones’ session brought the core theme of REACH: A Staffing Executive Masterclass full circle. 

Technology does not operate independently of people and processes. 

AI cannot repair an organization simply because it is AI. 

A broken process may need to be redesigned before it is automated. 

Employees need training, leadership, and support if technology is going to become part of their daily work. 

Technology investments need measurable business objectives. 

And throughout that transformation, staffing firms need to protect what makes their industry valuable in the first place: relationships. 

For leaders, the opportunity is not simply to “implement AI.” 

It is to build a more productive, scalable, responsive organization where technology handles more of the repetitive work and people have more capacity to create value. 

Or, in Jones’ words: 

Multiply the human. Eliminate the repetitive. Keep the excellent. 

Frequently Asked Questions About AI in Staffing

How can staffing agencies use AI?

Staffing agencies can use AI to support sourcing and candidate matching, research, content creation, call analysis, administrative tasks, training, personalization, credentialing, back-office workflows, and other repetitive processes. The best use cases begin with a clearly defined business problem and a measurable outcome rather than adopting AI simply because the technology is available.

What should a staffing firm automate first? 

Before automating anything, leaders should identify the tasks and bottlenecks that consume employee time. Asking employees what gets in their way every day can uncover valuable opportunities. Leaders should then determine whether the task should be eliminated, improved, automated, or supported with AI.

How can staffing companies measure AI ROI? 

Staffing firms can connect AI investments to measurable business outcomes such as time to submit, recruiter productivity, hours saved, candidate volume, customer retention, compliance efficiency, or administrative costs. Lauren Jones recommends evaluating whether technology helps generate revenue or preserve revenue and identifying the metric it is expected to move.

Will AI replace recruiters in staffing? 

Jones’ perspective is that staffing companies should use AI and automation for repetitive work while keeping people focused on relationships. AI can help recruiters work faster and reduce administrative burdens, but empathy, judgment, trust, and relationship-building remain important human strengths in staffing.

Why is AI adoption difficult for staffing firms? 

Technology adoption requires more than purchasing software. Employees need ongoing training, leadership support, clear expectations, practical use cases, and opportunities to ask questions. Change champions and continued post-launch support can help staffing firms improve adoption.

Why does data quality matter for staffing AI?

AI systems often rely on existing candidate, client, job, and operational data. Clean, tagged, structured data can improve the organization’s ability to use AI for functions such as search, matching, analytics, and personalization. AI may also help firms clean and organize existing data. 

What should staffing firms ask an AI vendor?

Staffing leaders should understand what problem the technology solves, which task or workflow it replaces, what metric it improves, how ROI will be measured, who owns the data, how the product integrates with existing systems, what happens during downtime, and what implementation, training, and ongoing support the vendor provides. 

Turning Technology Investment Into Business Growth 

The promise of AI is enormous, but technology alone does not build a stronger staffing company. 

Leadership does. 

Staffing executives have an opportunity to rethink how work moves through their businesses, where valuable employee time is being lost, and where better systems could create capacity for growth. 

For 40 years, Access Capital has worked alongside staffing entrepreneurs as they navigate growth and change. Through tailored working capital financing, strategic insight, and term loan solutions, we help staffing firms access capital that can support expansion, acquisitions, technology investments, and other strategic initiatives. 

As an extension of Lauren Jones’ REACH session, Access Capital is pleased to connect readers with an additional resource from LEAP Advisory Partners. Staffing leaders who are ready to explore how AI and technology can be applied within their own organizations can schedule a complimentary consultation with LEAP by tapping here.  

Whether you’re planning for growth, considering an acquisition, navigating an ownership transition, or simply evaluating what comes next, we invite you to start a conversation with Access Capital. Connect directly with one of our experienced financing professionals to discuss your goals, explore your capital needs, and gain an informed perspective on the options available to support your business.