When Automation Backfires: How Rushed AI Implementation Can Hurt Employee Engagement

AI holds the potential to transform workplaces—but not always for the better. While artificial intelligence adoption can streamline processes and reduce employee workloads, automation without proper strategy and purposeful implementation creates significant challenges for organizations that can harm employee engagement. 

Pressure to innovate and stay competitive is significant. But organizations that rush to adopt AI without fully understanding the technology—or helping employees understand it—risk disrupting workflows and displacing workers. 

According to Accenture’s Work, Workforce, Workers Age of Generative AI report, 95% of workers don’t trust organizations to ensure positive AI outcomes for everyone. Employees struggling to grasp AI may experience a decrease in efficiency, compounded by fear and uncertainty about the future of their roles. These factors can cause confusion, uncertainty, and stress, negatively affecting job satisfaction and worker well-being. Missteps in AI implementation can also create operational challenges, such as integration difficulties and organizational liabilities, which, in turn, diminish productivity and foster frustration and distrust among employees. 

Forward-thinking organizations must recognize these risks and the importance of strategic AI rollout, a comprehensive training framework, and leadership involvement to preserve employee satisfaction and morale.

5 Ways Rushed AI Implementation Hurts Employee Engagement

SHRM’S 2024 AI in the Workplace report reveals that nearly half of U.S. workers (47%) feel unprepared for the widespread adoption of AI and automation models at their organizations. However, employee concerns extend past unpreparedness. Below are five ways AI adoption without proper strategy hurts employee engagement.

1. Lack of Understanding and Experience with AI

According to SHRM’s August 2024 Current Events Pulse survey, 4 in 5 workers (80%) classify their understanding of AI as only beginner or intermediate. In addition, 22% of workers have no experience with AI, while 63% rate their proficiency as beginner or intermediate. 

When employees are unfamiliar with AI and cannot leverage it fully, they miss opportunities to accelerate their productivity. Workers suddenly required to use AI in their roles may fall behind, leading to stress and frustration. Research by Upwork found that nearly half of employees (47%) are unsure how to achieve the productivity gains their employers expect. Additionally, new LinkedIn research uncovered that 64% of professionals feel overwhelmed by rapid workplace transformation—citing integrating AI into their daily work as a top challenge.

2. Uncertainty Weighs on Workers

Without proper communication and training, AI adoption can take a mental and emotional toll on workers. SHRM’s 2023 Workplace Automation Research found that 23% of U.S. workers are concerned that automation will replace their job in the next five years. “This is a people and psychological safety issue,” said Lei Comerford, executive coach at Lei Comerford Consulting, during her Main Stage speaker session at SHRM’s INCLUSION Marketplace 2024. “As most organizations are moving forward, they’re focusing on the tools and technology, and not about the people and how this is impacting them,” she said.

Recent union strikes underscore these fears. During the International Longshoremen’s Association strike in 2024—as well as the United Auto Workers, and Hollywood Writers Guild of America strikes in 2023—workers expressed concerns about the potential reduced need for human labor and how it could lead to them being displaced (or replaced) by automation. A lack of clear communication on how AI will be integrated into the workplace traps employees in a state of fear and uncertainty, eroding their job satisfaction and morale.

3. Human Intervention Increases Workloads

While AI can facilitate processes, it’s primarily a tool that requires human oversight to ensure results meet organizational standards. According to Deloitte’s State of Generative AI in the Enterprise Q2 2024 report, 33% of respondents lack confidence in results produced by AI tools, and 88% of HR leaders believe optimal functionality requires human intervention (AI in the Workplace, SHRM, 2024). While monitoring AI outputs is essential, it can increase employee workloads and detract from primary responsibilities. It may also overwhelm inexperienced AI users and lead to anxiety over potentially being blamed for errors.

Upwork found that while 96% of C-suite leaders expect AI to accelerate organizational productivity, 77% of employees believe AI tools have increased their workloads. In response to increased employer demands, 71% of employees say they are burned-out, and 1 in 3 say they are overworked and likely to quit their jobs in the next six months. 

4. Inoperability and Integration Errors

Deloitte’s State of Generative AI in the Enterprise Q1 2024 report reveals that most organizations use off-the-shelf AI solutions (71% use productivity applications with generative AI [GenAI], 61% use enterprise platforms, and 68% use standard GenAI applications). However, only 32% of respondents use private large language models (LLMs), and 25% use tailored open-source LLMs. 

An AI solution that is a poor fit for your business needs can drain resources, and inoperability with current systems can disrupt existing workflows. Without an integration strategy and sufficient data management, AI may not have a holistic view of a company’s data, and therefore produce skewed insights built on data silos. Consequently, AI initiatives may misalign with business objectives and ultimately fail, increasing stress, frustration, and disengagement among employees.

5. AI Liability Risks Disloyalty and Distrust 

Heedless implementation of AI can both exacerbate process flaws within an organization and create new troubles. The case of Zillow Offers serves as a cautionary tale: After relying heavily on AI algorithms to forecast home prices, Zillow mistakenly overpaid for homes it planned to resell, costing the company millions and resulting in a 25% workforce reduction. 

Disruption of business operations and financial setbacks due to the careless use of AI can significantly impact employee loyalty and morale. Workers may perceive a lack of trust in leadership and feel decreased loyalty to the organization—especially when errors could have been prevented by consulting employees for feedback during planning and rollout. “The people closest to the tasks are the ones who know what should be automated, augmented, or enhanced,” said Nichol Bradford, executive-in-residence for AI+HI at SHRM. “To me, the question is, do you want to be a market leader, or only incrementally better? If you want to be a market leader, you cannot do the implementation without your employees. And their engagement has everything to do with how you lead, inspire, and direct change.”

Change Management Takeaways for Leaders

Equipping employees to adapt to AI-related changes is essential for maintaining their engagement and productivity. However, only 36% of organizations measure worker trust and engagement as part of adapting talent strategies to GenAI (Deloitte State of Generative AI in the Enterprise Q2 2024 report) and 75% lack strategies or initiatives to ensure positive AI learning experiences for workers (Accenture Work, Workforce, Workers Age of Generative AI report).

While AI integration is complex, prioritizing employee communication and collaboration is critical. Transformative organizations should take the following steps to support employee engagement.

1. Purposeful Implementation: Develop a clear vision that aligns with company goals and processes. Identify areas where automation can genuinely benefit employees, rather than automating tasks simply for the sake of efficiency. 
2. Maintain a Human-Centered Approach: Ensure that AI is used to enhance human capabilities with proper oversight and that employees have the bandwidth to effectively oversee AI processes. It’s essential to clearly communicate the impact that AI will have on different roles, outline how those roles will evolve, and provide support to help employees adapt.
3. Establish a Process: Design a comprehensive rollout plan that includes data integration strategies. Seamless integration requires thoughtful planning and careful selection of AI solutions that align with business needs, rather than hasty adoption driven by competition.
4. Collect Employee Feedback: Implement pilot programs and gather feedback to address concerns and foster collaboration early. Proactively mitigating issues ensures they won’t negatively impact return on investment or business objectives.
5. Provide Training and Support: Collaborate with HR to develop training programs that equip employees with the knowledge and skills they need to work alongside AI. Empower employees to feel confident—not replaced—and provide resources for those who feel anxious or uncertain about their future roles.
6. Invest in Reskilling and Upskilling: In today’s AI-driven job market, 83% of HR leaders believe that upskilling will be essential for workers to stay competitive (AI in the Workplace, SHRM, 2024). Invest in career development programs to mitigate future uncertainty and foster an environment where employees can grow alongside technological advancements.

Organizations that prioritize collaboration, training, and upskilling can empower their employees to harness the full potential of AI. Doing so ensures a future where human and technological capabilities seamlessly complement each other, fostering greater workplace productivity and satisfaction.