AI investment is rising. Hiring models aren’t keeping up.

87% increased talent acquisition tech investment, but most still struggle to scale hiring

Cielo's new Talent Benchmark research finds technology investment is accelerating, but organizations have yet to turn that investment into agile hiring models and broader business impact.

MILWAUKEE, WI – Cielo, the world’s leading Talent Solutions Partner, today released its new Talent Benchmark, a global research report on how enterprise organizations are evolving talent acquisition through technology investment, AI adoption, adaptive operating models, workforce agility and business-value measurement.

Based on a global survey of enterprise HR leaders, Cielo’s Talent Benchmark finds that organizations are investing heavily in AI and talent technology, but many have yet to translate that investment into a more agile hiring model.

Key findings from the Cielo Talent Benchmark reveal how enterprise hiring is evolving:

1. Tech investment is surging. Agility isn’t. Eighty-seven percent increased talent acquisition tech investment over the past 12 months, yet many organizations still struggle to translate that investment into greater hiring agility.

2. AI is expanding capacity. Recruiter headcount is still the constraint. Fifty-six percent say AI gives them some agility, but recruiter headcount still limits capacity; only 31% can scale sourcing and screening without adding recruiters.

3. AI moves faster. Human judgment still matters. Sixty-one percent report human-in-the-loop guardrails, while 45% track stakeholder experience and 43% audit automated workflows for bias, fairness and adverse impact.

4. Adaptive work remains the exception, not the norm. Only 29% have an enterprise-wide dynamic skills framework, while 45% are still transitioning from traditional job structures, limiting the flexibility organizations need to adapt work as hiring demand changes.

5. Measurement is expanding. Proof of business value isn’t. Just 23% track talent acquisition outcomes tied directly to enterprise value, business growth and the bottom line.

“Adding AI to the same hiring model is not transformation,” said Marissa Geist, CEO of Cielo. “In a business environment where hiring demand can shift quickly and unpredictably, organizations need a model that can respond just as fast. That requires rethinking the work itself, where AI can execute, where human judgment creates the most value and how the two come together to create greater agility.”

The Talent Benchmark findings show that shift is beginning to take shape as organizations work through how AI should be governed, where people need to stay involved and how work needs to be redesigned for greater agility.

Responsible AI adoption is moving from tool deployment to workflow design. As AI becomes more embedded in hiring workflows, legal, regulatory and trust expectations are raising the stakes onwhere organizations automate and where they preserve human judgment. The findings suggest organizations are beginning to define where AI can accelerate work and where people need to stay in control, especially in moments that affect fairness, experience and hiring decisions. That distinction is critical to turning investment into operating change rather than simply adding automation to the same model.

Enterprises are also beginning to move beyond static job structures, but most have not translated that ambition into greater agility. Twenty-nine percent have implemented a dynamic skills framework enterprise-wide, while 45% are still transitioning from traditional job structures. The broader opportunity is to move beyond skills frameworks and redesign work around capabilities, tasks, workflows and business priorities so organizations have more flexibility to adapt how work gets done as hiring demand and business needs change.

“These findings highlight a challenge many organizations are facing at an enterprise level,” added Geist. “More technology investment doesn't automatically create better outcomes. The organizations creating business advantage are the ones redesigning how work gets done, combining AI, human expertise and operating models that can adapt as needs change.”