In their latest “State of AI” report, Deloitte researchers declare that artificial intelligence is gaining traction fast across a range of industries: “We see clear acceleration from organizations,” they report, “with wider workforce access to AI tools, early productivity gains, and growing confidence in AI’s potential.”
The staffing industry in the past has not been at the forefront of technological change. This time, industry leaders are stepping up. They are bringing AI use cases to the fore, with an eye toward improved productivity and elevated levels of service.
AI-enabled solutions are on the rise in support of both candidate engagements and back-office processes. Industry leaders are adopting agentic AI—machine-driven processes that can accelerate routine workflows. And they are looking to build up AI skills within their workforce.
Staffing Success takes a deep dive into the state of AI in the staffing industry at this pivotal moment.
INTEGRATION OF AI INTO STAFFING
Deloitte research shows companies across the boards broadening worker access to AI by 50% in just one year, with 60% of workers now equipped with AI tools. Staffing industry leaders are in step with this trend.
At National Recruiting Consultants, which provides flexible staffing solutions to school districts, AI drives automation in support of initial contacts. “If we’ve got an open position for a school psychologist in Dallas, we go through our [applicant tracking system] and set the filter criteria: Credentialed school psychologist within this area’s radius,” explains IT analyst Colin Dobbs.
Then the team will ask AI to generate an engaging text message to potential candidates, which goes out at a preset day and time. Recruiters are on standby to field responses and set up calls. “Through this automation workflow, we can reach hundreds [of candidates] almost simultaneously,” Dobbs says.
IT staffing firm Procom first started using AI to support compliance management—to verify whether the name on an individual’s driver’s license is the same as the name in the system. When that system came online, “our time to onboard actually decreased in some cases by five or six days because we weren’t spending as much time manually reviewing documents,” says chief operation officer Wendy Kennah.
Meanwhile, Kelly Services has taken a multilevel approach to AI adoption, says Hope Bradford, senior director, global shared applications. At the enterprise level, for example, the AI chatbot Kelly ACE “screens candidates against job requirements, gives them real-time feedback on their fit, and schedules interviews automatically,” she says. “That means candidates get a faster, more responsive experience—and our recruiters can focus their time on the candidates who are moving forward.”
At the user level, Bradford has seen firsthand the impacts of AI. “Microsoft Copilot embedded in my Outlook and Teams has reclaimed meaningful time I used to spend on scheduling, email triage, and meeting follow up,” she says. “The productivity shift is already very real.”
ADDRESSING THE RISKS
The proliferation of AI introduces new risk factors, and success demands a thoughtful strategy. As AI ramps up, strong governance will be essential, according to Deloitte, whose research finds that only 30% of companies are highly prepared to address risk and governance around AI.
AI can potentially introduce bias in candidate screening. It can leak personally identifiable information and potentially compromise security. Other risks include things like “credential drift, where AI validates a worker whose license lapsed,” says Chris Loope, founder and chief technology officer at Pedagogue Systems, an AI enablement, learning, and governance platform. There’s also “the gap between what AI recommended and what a human actually decided,” and the possibility that accountability could collapse under audit.
Staffing industry leaders recognize the need for a proactive approach here. “As AI moves from experimentation to deployment, governance is the difference between scaling successfully and stalling out,” says Amy Yackowski, founder and chief evolution officer at Painted Porch Strategies, which provides coaching, training, and advisory services to the staffing industry.
“If you don’t define where human judgment is required…and where AI autonomy is allowed, you aren’t freeing your teams from bureaucracy and administrative work,” Yackowski says. “You’re leaving them to figure out the boundaries of their own authority in real time.”
At Procom, Kennah looks to limit risk in part by standardizing tools. “Early on, people were going out and using whatever product they had. Some people have their own ChatGPT license or Claude license,” she says. “Over the past year, we’ve put a policy in place. You’re only allowed to use tools that are defined by the organization and that are secured in our own network.”
“As AI moves from experimentation to deployment, governance is the difference between scaling successfully and stalling out.”
—Amy Yackowski, founder and chief evolution officer,
Painted Porch Strategies
There’s also governance around how those tools are used. “We have a policy that tells people what’s okay and what’s not,” Kennah adds. “And we’ve tried to give them enough guidance to say: If you’re unsure, you should pause and consult with somebody to see if this is okay.”
At Kelly Services, governance is anchored in an AI Council, led by chief information officer Sean Perry, “which ensures AI initiatives align with measurable business outcomes and risk tolerances,” Bradford says.
“Within my own portfolio, governance starts at the project level,” she says. For any AI capability, “we require documented use cases, defined human-in-the-loop checkpoints, and clear escalation paths.” Bradford is a member of the ASA staffing technology taskforce, “where we’re actively developing industry guidance on responsible AI use in staffing—because this isn’t a problem any one company can solve alone.”
AGENTIC AI ON THE RISE
Where generative AI provides information, agentic AI can take action: AI agents can execute on predefined workflows. Deloitte found that 74% of companies plan to deploy agentic AI within two years. Staffing is keeping pace there, while working to minimize the risks.
At National Recruiting Consultants, Dobbs sees big potential here. “When you’re tailoring creation of an AI agent, you can apply the guardrails yourself: Look for this URL and pull from this list, apply this API connection,” he says. “You can define more of the parameters but still give it some autonomy as far as providing feedback and reports.”
With that in mind, “we’re working on agents to get external engagement,” Dobbs says. “For instance, if a certain industry has open job positions and maybe we’ve not historically worked with them, it feeds that data over to our sales managers to say: Hey, this is a possible opportunity. That’s a great example of agentic AI use, just to get market awareness.”
Procom likewise is putting AI agents to work. “In our technology team, we have agentic AI going on with our developers,” Kennah says. “Where they have code writing overnight, they have agents doing that work.”
AI agents in staffing are supporting “full-lifecycle autonomy: source to invoice, credential to placement, timecard to payroll,” Loope says. “Agents do the machine work; humans do the human work.”
“The industry is going to end up here,” Loope says, and strong guardrails will define success. “The firms that arrive with governance infrastructure [will be able to] run autonomously. The firms that don’t stay stuck at human-in-the-loop forever,” he says.
To that end, Kelly Services is approaching agentic AI “thoughtfully, and with a clear architectural blueprint,” Bradford says. The use cases she’s focused on for agentic AI include supplier onboarding (AI-driven document completeness checking), knowledge management (agent-proposed article generation from resolved cases), and service automation (incident or case triage and routing without human handoff for defined categories).
“The firms that will win are not the fastest adopters—they’re the most disciplined fast adopters. They deploy AI with clean data, train their people to use the outputs intelligently, and instrument the results so they can course-correct quickly.”
—Hope Bradford, senior director, global shared applications, Kelly Services
“In each case, we define the action boundary, the escalation trigger, and the audit trail before we deploy—because an agent that takes the wrong action at scale is a much larger problem than one that answers a question incorrectly,” Bradford explains.
She’s also watching developments in Microsoft Copilot Studio and ServiceNow’s Now Assist agent/Employee Works, as well as others. “The platforms are moving fast, and our job is to match that pace, without outrunning our governance,” says Bradford.
DRIVING SPEED-TO-MARKET
Speed matters in this industry, “both the speed to match talent to opportunity, and the speed to adapt to market shifts,” Bradford says. In staffing, the fastest often win. AI can play a key role here, “compressing timelines in ways that create genuine competitive advantage for firms that execute well.”
Kennah sees the potential here. “As a recruiter, if you can submit three people to the customer, before it would maybe take you three hours to format the résumés and then write detailed submission notes,” she says. “Now you can write pretty detailed submission notes speaking directly to the job with a formatted résumé in 15 minutes.”
She’s viewing speed through another lens as well: The time to ramp up new people within the staffing organization. “There’s a time and a cost to that, because they have to understand the job orders and how that creates a search string to go actually look for people,” Kennah says.
With AI helping, “you can put a job order in and we have something that says: Okay, create 10 questions for the pre-screen and give the appropriate answers. As a recruiter who’s on day two, they can run this prompt,” Kennah says. “Before, we would often take four to six months to get somebody with their first billable placements. Since we really integrated this into our organization, our time to first billing for our new hires is probably 45 days.”
“Staffing firms should be identifying and promoting the experimenters they already have, not hunting external AI specialists who don’t know the industry.”
—Chris Loope, founder and CTO, Pedagogue Systems
With speed in mind, “Kelly has demonstrated meaningful reductions in time-to-hire in targeted use cases through AI-assisted recruiting processes,” Bradford says. “When a client has a critical role to fill, that speed differential is often the deciding factor in whether they renew or look elsewhere.”
But fast without accurate is actually slower—“a poor match that results in early attrition means you’re starting over, with damaged client trust,” Bradford says. “The firms that will win are not the fastest adopters—they’re the most disciplined fast adopters. They deploy AI with clean data, train their people to use the outputs intelligently, and instrument the results so they can course-correct quickly.”
FINDING AI-CAPABLE TALENT
Staffing candidates increasingly are bringing AI skills to the table. In fact, a study from ASA and LinkedIn shows that staffing agency temporary and contract workers are adopting artificial intelligence skills at a faster rate than others on LinkedIn. Between 2023 and 2025, these workers added AI literacy skills at a higher rate than others—40% more in 2023, rising to 46% more by 2025.
So the AI-ready candidates are there. But staffing firms also need an AI-capable internal workforce to make the most of the emerging capabilities. “Insufficient worker skills are seen as the biggest barrier to integrating AI into the business,” the Deloitte report notes.
To ensure success, staffing executives say they aren’t necessarily looking for people who have AI skills today, but rather those who show the readiness to get there. “When we look at bringing on new internal talent, it’s really critical that they are willing to learn new systems,” Dobbs says. “If they’re not going to learn anything new, they’re not going to grow, and the company’s not going to grow.”
Kennah takes a similar stance. “What we’re looking for is people who have a high ability for change agility,” she says. “When you have that, you can train people. We’re looking for somebody who has high change agility and problem-solving skills, who is going to dive into these tools.”
Some of the younger employees on Kennah’s team use AI to put together their outfits, coordinating jewelry and makeup. “They’re not just using it for work. They’ve figured out how to make this work for life,” she says. “Those are the people who are going to really lean into it in the workplace.”
Even at Pedagogue Systems, where the work is all about AI, “we don’t look for AI backgrounds. We look for curiosity,” Loope says, and he encourages staffing firms to do the same. “Staffing firms should be identifying and promoting the experimenters they already have, not hunting external AI specialists who don’t know the industry.”
Bradford’s approach aligns exactly with this advice. She invests heavily in developing AI literacy within the existing team “because finding net-new talent is harder and more expensive than elevating the people who already understand our platforms, our data, and our business context,” she says
LOOKING AHEAD, SCALING UP
AAcross all industries, 42% of companies believe their strategy is highly prepared for AI adoption, Deloitte reports. It’s clear that many staffing firms can say the same. And with momentum building, staffing leaders are looking to scale up and expand their AI efforts.
At National Recruiting Consultants, Dobbs is seeking new opportunities to put AI to work.
“I’m going through and evaluating functionality of the team. What are you wasting time on? What can we build to remove labor hours?” he says. “Because if those labor hours are then available, they can do what they are really good at doing, which is selling.”
He’s also looking at external, candidate- and client-facing interfaces, in order to provide better services to employees in the field. “In the special education realm, a lot of what they do is hands-on with children, but there’s a certain amount of administrative work that can take anywhere from possibly five to 10 hours per week,” he says. “We are trying to reduce those, helping them to increase efficiency.”
At Procom, Kennah has seen rapid AI adoption among recruiters, and she’s planning to ramp up their uses even further. Instead of the recruiter using AI multiple times across a workflow, she’s looking to connect the dots “so that the AI is just doing these steps, without you prompting it to do those steps,” she says.
“That’s the next stage in terms of us being able to scale that, so that each recruiter doesn’t have to kick off these steps,” Kennah adds. “They’re able to just let those steps run.”
Budgeting will factor in here: Staffing needs to think about how it will pay for expanded AI usage going forward. The budget model “has to be consumption-based,” Loope says. “AI cost scales with tenant activity, so margin scales with revenue. A flat AI license does not survive contact with a staffing P&L running 3% to 5% net margins.”
Loope adds that a variable cost of goods sold model—expenses directly tied to production volume, increasing as production rises and decreasing as it falls—“is the only model that works.”
At Kelly Services, Bradford is tying AI scaling directly to measurable financial impacts. “Our roadmap is phased and tied explicitly to business outcomes,” she says. That helps guide the investment strategy.
“We’ve structured our AI expansion in waves, with each wave requiring a defined business case, an approval gate, and measurable ROI criteria,” Bradford says. “Architecturally, we made a deliberate decision to purchase technology in a way that supports reuse across multiple integration phases.”
That matters for budgeting “because it means we’re not re-architecting each time we onboard a new data source,” says Bradford. “We’re amortizing the infrastructure investment across the roadmap. It’s the philosophy I apply to all the platforms I manage: Build once, scale horizontally.”
Adam Stone, a freelance writer based in Annapolis, MD, is a regular contributor to Staffing Success. Send feedback on this article to s******@americanstaffing.net. Engage with ASA on social media—go to americanstaffing.net/social.
