IBM study shows human-led AI workflows cut risk 18%

A new global study from the IBM Institute for Business Value reveals a surprising disconnect between employer expectations and employee anxieties surrounding artificial intelligence, the company says. While 71% of Chief Human Resource Officers identify the ability to supervise and validate AI outputs as the most essential skill for the modern workforce, 60% of employees worry AI is eroding their skills, specifically citing critical thinking as the capability most at risk.

Organizations defining clear human-led, AI-assisted, or AI-executed workflows are seeing measurable benefits, reporting an 18% risk reduction and 20% quality improvement, yet nearly half do not include the CHRO in defining AI strategy. “AI is changing not only how work gets done, but where people can contribute the greatest value,” says Nickle LaMoreaux, Senior Vice President and Chief Human Resources Officer, IBM.

Cecilia McKenney, Senior Vice President & CHRO, Quest Diagnostics, states, “An AI-enabled culture that is grounded in the principle that humans are any company’s secret sauce will differentiate you versus competitors.” The study also finds that as AI takes on more routine and process-driven tasks, uniquely human capabilities become even more important.

Employee Concerns Reflect Declining Critical Thinking Skills

Sixty percent of employees express worry that artificial intelligence is eroding their skillsets, with critical thinking consistently identified as the most vulnerable capability, a concern that diverges from employer perspectives on necessary skills. This apprehension suggests a potential disconnect in how workers perceive the impact of AI on their professional value, and highlights a need for proactive skill development initiatives. The IBM Institute for Business Value study, encompassing 1,500 CHROs and 8,800 employees globally, reveals this disparity in perception is not merely anecdotal but a widespread sentiment.

Forty-six percent of organizations currently exclude their CHRO from the formulation of AI strategy, despite 71% of those same CHROs designating the supervision and validation of AI outputs as the single most crucial skill for the future workforce, according to the company. This omission appears counterintuitive, given the growing emphasis on human oversight in responsible AI implementation and the potential for errors or biases in AI-driven processes.

“CHROs have a critical role to play in redesigning the workplace of the future so people can focus on the areas where they can have the greatest impact.” Organizations that have clearly defined workflows, categorizing them as human-led, AI-assisted, or AI-executed, demonstrate an 18% reduction in risk and a 20% improvement in quality, indicating a measurable benefit to strategic role allocation.

AI is changing not only how work gets done, but where people can contribute the greatest value.

Nickle LaMoreaux, Senior Vice President and Chief Human Resources Officer, IBM

CHROs Prioritize AI Oversight and Human Judgment

Employee apprehension regarding skill erosion extends beyond general anxieties; 60% specifically cite a decline in critical thinking abilities as AI adoption increases, a concern not fully mirrored by employer perspectives. This disconnect highlights a potential gap in understanding how AI impacts workforce capabilities, even as 57% of CHROs identify critical thinking as a key skill for the AI era. The study reveals that organizations creating the greatest value from AI are redesigning work, decision-making and workforce capabilities around people and technology.

A significant organizational oversight appears to be the exclusion of CHROs from AI strategy formulation, with 46% of organizations currently operating without their input. Nickle LaMoreaux, as quoted in the study, emphasizes the evolving role of HR, stating, “We think of the CHRO and CTO as the power couple because they are bringing talent strategy and technology strategy into one conversation. Together, we’re co-architects of the work.” This collaborative approach, however, remains unrealized in nearly half of organizations.

Rather than simply measuring task completion, Kristin Oliver, Chief Human Resources Officer, Hyatt Hotels Corporation, suggests organizations should prioritize how AI impacts decision quality, employee experience, and overall business performance.

Rather than asking how much work was completed, we’re asking whether AI helped improve decision quality, speed, employee experience, guest satisfaction and business performance.

Human-Led Workflows Drive 18% Risk Reduction & Quality Gains

This benefit underscores the importance of intentional workflow design as AI integration expands, moving beyond simple task completion metrics to focus on detailed performance gains. Kristin Oliver, Chief Human Resources Officer at Hyatt Hotels Corporation, emphasizes this shift, stating, “Rather than asking how much work was completed, we’re asking whether AI helped improve decision quality, speed, employee experience, guest satisfaction and business performance.” Despite the potential benefits, a significant organizational gap exists in strategic oversight; 46% of organizations do not include their Chief Human Resources Officer when formulating AI strategy. When HR shares responsibility for determining which decisions remain human-led, employee confidence in questioning or overriding AI recommendations increases substantially, reaching 76% compared to only 43% in organizations where HR’s role is purely advisory.

The increasing reliance on AI is also creating new demands on the workforce, with 80% of CHROs acknowledging the emergence of “invisible” work, tasks like validating AI recommendations, correcting errors, and managing exceptions. This added burden is felt by employees, as 42% report that AI either increases their workload or leaves their contributions unrecognized. However, 42% of CHROs indicate that productivity gains from AI are being reinvested in innovation or employee reskilling, suggesting a potential pathway to address these challenges and cultivate an AI-enabled culture.

An AI-enabled culture that is grounded in the principle that humans are any company’s secret sauce will differentiate you versus competitors. AI is a tool for humans to perform their best work.

AI Adoption Creates “Invisible” Work & Accountability Gaps

Employee concerns about skill erosion accompany the increasing integration of artificial intelligence into workflows, with 60% fearing a decline in critical thinking abilities. This apprehension isn’t fully mirrored by leadership; while 49% of employees and 57% of CHROs both prioritize critical thinking and problem framing in the age of AI, the employee worry suggests a disconnect in perception regarding the pace and impact of these changes.

Where clear judgment is embedded in work processes, 62% of CHROs report increased employee confidence in AI-driven decisions, a figure that drops sharply to 57% reporting declining confidence when such judgment is absent. Accountability gaps are emerging as a significant challenge, with 43% of employees reporting they bear the blame when AI systems falter, while 41% of CHROs suspect employees may hesitate to challenge or override AI outputs.

This lack of clarity complicates AI deployment for 36% of CHROs, and only 28% report a collaborative roadmap with IT, operating with consistent coordination across executive leadership. Seventy-two percent of organizations currently make limited or no use of AI within the HR function itself, despite CHROs rating HR’s AI literacy (13%), performance measurement (16%), and change management (20%) as particularly weak areas.

We think of the CHRO and CTO as the power couple because they are bringing talent strategy and technology strategy into one conversation. Together, we’re co-architects of the work.

Stay current

See today’s quantum computing news on Quantum Zeitgeist for the latest breakthroughs in qubits, hardware, algorithms, and industry deals.

Avatar of Ivy Delaney

Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

Latest Posts by Ivy Delaney: