Worker Trust Gap in AI Reveals a Big Risk for Supply Chain Organizations
Employee skepticism about the deployment of artificial intelligence creates a significant, yet often overlooked, operational risk for supply chain organizations that invest heavily in automation and algorithmic decision-making. According to a survey of more than 1,000 working adults conducted by talent insight firm SHL and reported by HR Dive, only 27% of workers fully trust their employers to use AI responsibly, while 59% believe AI makes bias worse rather than better.
Key Takeaways
- Only 27% of workers fully trust employers to use AI responsibly, creating adoption risk for supply chain automation
- 74% say AI interviews change company perception, with workers preferring human involvement in career-affecting decisions
- 53% of workers worry AI erodes human touch, signaling resistance to operations automation without adequate consideration
- 48% are willing to upskill for AI workplaces, but 25% don't understand what "AI skills" means
- Transparency about AI usage and structured training programs address trust gaps more effectively than technical capability alone
The Perception Problem: Innovation Versus Impersonal
When workers encounter AI in high-stakes career decisions, their perceptions of employer organizations shift dramatically. The SHL survey found that 74% of workers said being interviewed by an AI agent would change their view of the company, with 37% describing the experience as "impersonal" and only 23% characterizing it as "innovative."
This perception gap extends beyond recruitment into operational contexts. More than half of surveyed workers prefer humans to algorithms for reviewing job applications, evaluating work performance, and making career-affecting decisions. For supply chain organizations deploying AI for performance monitoring, task assignment, or operational decision-making, this preference signals potential resistance that could undermine technology investments.
The Human Touch Concern in Automated Operations
Worker concerns about AI eroding human interaction create particular challenges for supply chain operations where automation delivers measurable efficiency gains. The survey revealed that 53% of workers worry that AI will eliminate human touch, while 21% would prefer to return to pre-AI workplace environments entirely.
These attitudes matter operationally when supply chain organizations implement warehouse automation, algorithmic scheduling systems, or AI-powered quality control. Employee resistance—driven by concerns about depersonalization rather than technical capability—can slow adoption, reduce effectiveness, and create friction between management and frontline workers who feel their roles are being diminished or eliminated without adequate consideration.
The Skills Gap and Training Imperative
Despite skepticism about AI deployment, workers recognize the importance of AI readiness for career success. Nearly half of surveyed employees said they're prepared to upskill for AI-enabled workplaces, with 48% willing to take online courses and 29% willing to use personal time to build AI fluency.
However, 25% of workers said they don't understand what "AI skills" means—representing a significant communication and training gap. For supply chain organizations, this suggests that technology implementation must include structured learning and development programs rather than assuming workers will adapt organically to new systems.
According to a LinkedIn report cited in the HR Dive coverage, most talent acquisition professionals say their CEOs expect them to solve AI skills gaps and build future-ready workforces, yet only one-third believe their teams can harness AI to meet strategic goals. This capability deficit creates competitive risks: organizations without effective upskilling programs risk lagging competitors, struggling to attract talent, and missing growth targets.
Strategic Implications for Supply Chain Leadership
The trust gap creates several strategic considerations for supply chain executives deploying AI systems. First, transparency about where and how AI operates in decision-making processes directly affects employee perceptions of organizational innovativeness versus impersonality. Workers value knowing when algorithms influence outcomes affecting their careers and operations.
Second, maintaining human oversight and accountability—even in heavily automated processes—addresses worker preferences for human involvement in consequential decisions. This doesn't necessarily mean eliminating AI, but rather structuring implementations so that humans supervise algorithmic outputs rather than ceding complete authority to automated systems.
Third, proactive investment in AI literacy training demonstrates organizational commitment to preparing workers for technology transitions rather than imposing changes without support. The 48% of workers willing to pursue upskilling represent an opportunity for organizations that provide structured, meaningful development programs.
By 2026, one in three companies expects AI to run hiring processes, according to Resume.org research cited in the HR Dive report. More than half already use AI in recruitment, yet similar proportions express concerns about algorithms screening out qualified candidates or introducing bias—concerns that mirror broader worker skepticism about the responsible deployment of AI.
Ready to implement AI in supply chain operations with employee trust and transparency? Connect with Trax Technologies to explore how human-centered technology deployment creates adoption success while delivering measurable operational improvements.