The evolving art of talent acquisition: Keeping up with the pace of AI
Contributors:
Josh Bersin
Founder, The Bersin Company
Jo-Ann Feely
Chief Innovation Officer, AMS
Lewis Cohen
Managing Director of Service Development, AMS
Rebecca Wettemann
CEO, Valoir
Artificial intelligence (AI) is now part of the infrastructure of the talent process, reshaping how organizations attract, assess, and deploy talent at scale. What was once a productivity enhancer is rapidly becoming the operating system for hiring.
Across industries, CHROs and TA leaders are already using AI to sharpen decision-making, improve speed and quality of hire, reduce bias, and critically connect recruitment outcomes directly to business performance.
Yet as innovation accelerates, many leaders are struggling to separate meaningful transformation from technology noise. New tools are arriving faster than organizations can operationalize them.
The reality is AI is not a shortcut to instant results. Sustainable impact comes when AI takes on high-volume, task-intensive work, while human intelligence (HI) is elevated to focus on judgement, relationship-building, and strategic workforce decisions. The future of TA is not AI instead of people, but AI accelerating human decision making.
Research conducted by Wakefield Research Group in partnership with AMS underscores just how profound this shift will be. Nearly 60% of HR and TA leaders expect the CHRO role to become more focused on AI than people as automation expands across sourcing and hiring. Four in five believe CHROs, not IT, should lead AI investment decisions in TA. By the end of 2026, 72% expect at least half of TA processes to be completed by AI, with humans directing, governing, and refining outcomes.
This is the context in which next-generation talent acquisition must operate. In this article, we explore why the convergence of human intelligence (HI) and AI is the defining advantage for modern TA, and how Next Gen TA, powered by AMS One, brings this vision to life. By unifying the data behind permanent, contingent, early careers and campus hiring on a single intelligence layer, AMS One enables organizations to move beyond fragmented solutions toward confident, connected decision-making at scale.
The talent acquisition revolution
According to research analyst Josh Bersin of The Bersin Company, TA leaders must be ready to embrace this evolution. Using AI fuels a different way of thinking about TA’s role, whether we call it TA or not, he says.
If you look at AI as a way to incrementally add value to the 50 steps you're already doing, you'll achieve maybe a 10 or 15 percent improvement, but you won’t get much more out of the process. That's why we think of it as a revolution.
Josh Bersin
Founder, The Josh Bersin Company
“It's the way TA is budgeted, the way we measure cost and time to hire. It's a very revolutionary way to think about this,” he says, “If you look at AI as a way to incrementally add value to the 50 steps you're already doing, you'll achieve maybe a 10 or 15 percent improvement, but you won’t get much more out of the process.”
Bersin adds, “That's why we think of it as a revolution.”
Using AI in hiring is not a silver bullet, warns Jo-Ann Feely, Chief innovation officer for AMS. “It’s complex. It’s costly,” she says. “And it creates capacity, not instant efficiency.”
This AI-fueled TA revolution will help HR and TA leaders to rethink the traditional hiring process from start to finish. TA leaders say that they are trying to hire the best people in the fastest time frame and that could be an internal, external or contingent hire or a recent graduate. And yet, if TA leaders adopt new solutions for each of these steps, they’re not going to get the impact that AI could deliver.
“The organizations making real progress are the ones that are clear on why they’re using AI beyond implementing point solutions, what outcomes they’re trying to achieve, and how success is measured, rather than just proving they’ve adopted the latest technology,” says Feely.
The organizations making real progress are the ones that are clear on why they’re using AI beyond implementing point solutions, what outcomes they’re trying to achieve, and how success is measured, rather than just proving they’ve adopted the latest technology.
Jo-Ann Feely
Chief Innovation Officer, AMS
The need for a new solution
Bersin estimates that even strong TA teams achieve only a 50–80% success rate when hiring good employees. As a result, poor hires are inevitable - and their impact is significant. Beyond wasted recruiting effort, non-productive hires consume HR and TA resources and can negatively affect business performance.
“If we can improve the targeting and the decision making in a precise manner, adopting AI will pay for itself a 100 times over,” he says.
“The ultimate goal of AI in this domain is precision. Precision on who to hire, where to source, who does the interviewing, as well as precision on what skills are needed, their pay, and on who's the right internal hire,” adds Bersin.
“This is what prompted AMS to build their Next generation TA model that is powered by AMS One, says Feely. Today’s TA divisions are drowning in data but it often resides in silos that does not allow TA leaders to have a complete picture of how best to hire. Most TA departments will have an ATS for TA, a VMS for contingent hiring and a different one for hiring on campus as well as a different ATS for internal mobility - each with their own data and almost always cannot interact with one another because they hail from different vendors in a crowded marketplace.
AMS One powered by AI is able to extract the data from the various client systems and overlay it with the data from AMS’ wide range of clients. This allows TA leaders to be more predictive about the source of hire, the time to hire and whether a specialist role might be best filled with a contingent hire.”
Next Gen TA means that tech stacks are going to look very different in the future, and the service model and the people model needs to look different too.
Lewis Cohen
Managing Director, Service Development, AMS
“Perhaps a company, for example, has a promising internal candidate. With AMS One, TA can see a unified data picture that shows the talent available within the organization, explains Feely. It might be easier to move the internal candidate to their new role across and rehire for their former position.
We could look at the problem in a very different way and use data that exists within the organization today but is just not being leveraged, she says.
AMS One is the connective tissue because what it allows us to take data from the client’s existing systems into a single platform,” Feely adds.
The use of AI within the AMS One platform is just one small part of Next Generation TA, according to Lewis Cohen, Managing Director of Service Development for AMS.
“Next Gen TA is an optimization of the service model and the underpinning technology. Many organizations have bought technology that is implemented improperly, or they don't have the operational processes and the people model to make it deliver the return on investment they were expecting,” he says.
“Next Gen TA means that tech stacks are going to look very different in the future, and the service model and the people model needs to look different too,” adds Cohen.
AI will play a major part in this next gen change, says Rebecca Wettemann, CEO of HR market research firm Valoir. “The real potential transformational benefits from AI come from its ability to digest large volumes of data for automated building and maintenance of skills ontologies,” she says.
That said, Wettemann believes that companies must have their skills data in order, but few do. “As companies look to make hiring and workforce planning decisions with an eye for how AI will transform their operations, real skills data integration and visibility will be critical, and will also drive more intelligent workforce planning and hiring,” she says.
That thinking is exactly what has shaped Next Gen TA powered by AMS One: giving TA leaders access to AI in a way that’s practical, responsible, and grounded in real delivery, not hype.
How AI moves TA from efficiency to intelligence, ethically
AI’s impact on TA does not just mean more automation. Over the next two years, machine learning’s influence will be felt in four primary domains:
Predictive workforce planning: AI will enable real-time forecasting of skills demand by analyzing internal HR data, market trends, and external labor analytics. These models can identify emerging skill gaps months before they affect performance, helping leaders design upskilling or hiring programs in advance.
Candidate sourcing and engagement: Generative AI can write job ads optimized for inclusivity, search relevance, and a consistent employer brand voice. Meanwhile, intelligent sourcing engines can scour multiple databases to find passive candidates whose profiles align with skill-based needs and not just job titles. Conversational AI bots can engage with candidates 24/7, answer questions, and schedule interviews often after the candidate clicks the Apply button to create a consumer-grade experience at scale.
(Remember: the recruitment process is the very first interaction a candidate will have with an employer. A cold, complex and confounding experience could send prospective talent running.)
Assessment and selection: AI-driven assessments now analyze tone, response patterns, and cognitive indicators during interviews and provide structured, bias-mitigated insights. When used ethically, these tools can deliver consistent decision making and reduce human subjectivity in candidate scoring.
Continuous learning and mobility: The next wave of AI in TA focuses on internal talent orchestration matches current employees to open roles, projects, or learning pathways based on skills data. This supports retention and agility, ensuring that organizations can redeploy talent as business needs evolve.
While the benefits of AI in hiring are substantial, they must be balanced with responsibility. Bias, data privacy, and transparency are critical considerations for every TA leader. In fact, the U.S. Department of Labor reiterates that when hiring new workers with the use of AI tools, employers and their recruiters must abide by the current laws or face steep fines.
“AI should amplify human judgment, not replace it,” says Cohen.
Of course, using AI ethically, as with any other hiring technology, will require training. According to Wettemann, although HR leaders believe that recruiting is a top area where they can benefit from AI, they cite lack of AI skills and expertise as the top barrier to adoption.
“At the same time, policy progress is lacking, with only one-third of organizations having a policy on the use of generative AI. Training is an issue as well with less than a third of organizations having training for the effective use of AI,” she says.
She adds, “If skills are an issue and you don't have effective training, you're not going to make a lot of progress.”
Redefining the recruiter:
From processor to orchestrator
AI is not eliminating the recruiter, but it is evolving their role. In the next generation of TA, recruiters become Talent Architects and Data Translators. Their value lies in interpreting insights from AI systems, advising hiring managers, and ensuring the process reflects employer brand and candidate experience. Under the 4P operational model put forth by Everest Group research—Platform, People, Process, and Partnership—recruiters sit at the center of orchestration:
Platform
Recruiters operate within AI-fueled ecosystems that integrate all sources of recruitment data.
People
TA professionals act as trusted advisors to hiring leaders thanks to new AI-powered data analytics.
Process
Agile, AI-enabled workflows replace rigid linear steps in the hiring journey.
Partnership
Recruiters collaborate with IT and data partners to refine talent strategy on an ongoing basis.
This processor to orchestrator redefinition elevates the TA function from service provider to strategic business enabler, directly impacting revenue growth and innovation velocity.
The promise of Next Gen TA powered by AMS One
Next Gen Talent Acquisition, powered by AMS One, brings people, processes, and data together through a single intelligence layer that helps TA leaders respond to workforce needs with speed and confidence. It delivers more personalized candidate experiences, smarter data-driven decisions, and measurable improvements in hiring outcomes.
Crucially, Next Gen TA is not just another piece of technology. It combines human intelligence with AI across permanent, contingent, and early careers hiring. ensuring automation enhances judgment rather than replacing it.
As Rebecca Wettemann, CEO of Valoir, notes, TA leaders have shifted from experimentation to accountability. “We’ve moved from FOMO to FOMU—fear of messing up—when it comes to AI in recruiting,” she says. “Leaders are on the hook to ensure AI interactions are trusted, unbiased, and transparent, and they’re looking to vendors to help shoulder that responsibility.”
That responsibility is only growing as the AI vendor landscape becomes more complex. Consolidation is expected in 2026 as costs rise and fragmented point solutions become harder to justify. “All of these disparate technologies do excellent work,” says Josh Bersin, “but it’s incredibly difficult, and expensive, to stitch them together and extract real value, that’s why Next Gen TA powered by AMS One is going to be a game-changer.”
Leaders are on the hook to ensure AI interactions are trusted, unbiased, and transparent, and they’re looking to vendors to help shoulder that responsibility.
Rebecca Wettemann
CEO, Valoir
This fragmentation is exactly what AMS set out to solve. AMS One provides a unified TA workflow that connects hiring activities end to end, removing silos, reducing complexity, and enabling orchestration across the entire talent lifecycle.
The message for TA leaders is clear. “Don’t fight it,” says Jo-Ann Feely. “The best recruiters will be the ones who use AI well. AI won’t replace great recruiters—but a great recruiter, powered by AI, is an incredibly powerful combination.”
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