The AI Reality Check: When Workplace Implementation Goes Wrong
All those wonderful things you hear about AI make it seem like a magical wand that you only need to bring into your workplace to transform it completely.
Well, although there’s no denying the powerful effects of a well-implemented AI strategy, there are also quite a few challenges that come along with it. Moreover, these hiccups sometimes give way to tragic outcomes too.
We checked in with the HR Spotlight community of HR leaders and business experts so we could go behind the scenes and bring to you a narrative you won’t always find among the AI headlines of the day—narratives where AI goes the other way, resulting in negative consequences.
Read on!
Overlooks Qualified Candidates
A company I worked with in the UAE had implemented an AI-driven hiring tool to streamline recruitment. The system used algorithms to filter candidates based on their resumes and preset criteria.
Initially, it seemed like a fantastic time saver but over time, the company noticed a troubling trend.
Highly qualified candidates were being overlooked, and there was an apparent lack of diversity in the new hires. Upon investigation, it became clear the AI system had been trained on historical hiring data that carried implicit biases, causing the tool to favor specific profiles while filtering out others unfairly.
This led to a skills gap in critical areas and tension within the HR team as they struggled to understand the discrepancies.
With my background in recruitment optimization and operational efficiency, I was brought in to address the issue.
Drawing on years of experience, I helped the company audit the AI system and retrain its algorithm with a more inclusive dataset. We implemented a dual-layered approach where human oversight complemented AI recommendations to ensure fairness.
Additionally, I coached their HR leaders on how to create unbiased hiring practices and monitor AI systems for unintended consequences. Within six months, the company saw a significant improvement in candidate quality and diversity while retaining the efficiency benefits of AI.
This experience underscores the importance of balancing technology with human judgment, something I always emphasize in my coaching practices.
Lowering Employee Morale
During my career, I’ve seen AI bring remarkable advances, but also some unintended issues, particularly in HR functions.
At a diagnostic imaging company I helped expand, we considered using AI for employee assessment. However, a similar AI tool used elsewhere in the industry unintentionally reduced employee morale.
By focusing too much on performance metrics extracted from work patterns, it failed to account for individual contributions that weren’t easily quantified, such as team collaboration and creativity.
This experience underscores the need for caution. AI can inadvertently neglect the human touch and nuanced judgment that are crucial in HR. Implementing AI requires more than just algorithmic precision; it needs a balanced approach that combines technology with human insights.
Ensuring constant oversight and human involvement helps preserve morale and align AI tools with broader company values.
Jeff Michael
Ecommerce Business Owner, Supplement Warehouse
Favors Keywords, Reduces Diversity
Being a small supplement and vitamin company with limited resources, we implemented an AI-driven recruitment tool to streamline the hiring process.
While it significantly reduced the time spent screening resumes, we noticed an unintended negative consequence: the AI’s algorithm unintentionally favored candidates with specific keywords, leading to a lack of diversity in the shortlisted applicants.
As a solution to this problem, we started doing regular audits of the AI’s selection criteria and combined its insights with manual review by HR staff.
This hybrid approach helped us maintain efficiency while ensuring we didn’t miss out on talented candidates due to algorithmic bias.
Creates Scheduling Conflicts
As the CEO of SuperDupr, I’ve seen AI’s potential to revolutionize various business functions, but it’s crucial to approach it with caution.
In our work changing businesses, we encountered an AI tool designed to automate routine HR tasks, such as sorting emails and managing candidate workflows.
However, the tool inadvertently created scheduling conflicts, impacting interview processes and frustrating both candidates and HR staff.
Implementing AI in such critical areas requires careful oversight.
At SuperDupr, we’ve learned that frequent testing and a strategic plan to integrate human oversight are vital. Providing team training to co-manage AI with human intuition can often prevent disruptions.
We’ve found that a balance between AI efficiency and human ethics is key to fairly enhancing HR operations.
Shows Bias in Recruitment
In the HR sector, AI has been used to streamline recruitment, but there have been instances where it created more problems than it solved.
For example, some companies implemented AI-powered recruitment tools to screen resumes, only to discover that the algorithm unintentionally exhibited bias. One well-known case involved an AI system favoring male candidates because it had been trained on historical data skewed toward male hires.
As a chatbot owner, I’ve learned that data quality and transparency are critical when implementing AI.
The bias in the AI tool wasn’t intentional, but it reflected the biases present in the training data.
This highlights the importance of auditing datasets and ensuring that the AI systems align with company values and fairness goals. HR teams must work closely with data scientists to avoid these pitfalls.
The takeaway is that AI systems are only as good as the data they are fed. Companies need to remain vigilant and regularly test their AI implementations for unintended outcomes.
In HR, the focus should not only be on efficiency but also on maintaining equity and inclusivity throughout the hiring process.
Rejects Freelance Applications
We decided to try to use AI to filter applications a little while ago.
However, we noticed that a large number of applications were being rejected and only a few were filtering through.
After adjusting, we noticed that the AI was eliminating those with freelance experience-but as a content agency, most of our collaborators are freelance. This was relatively minor and we wound up adjusting the AI and feeding the resumes through again.
However, I don’t know what would have happened had the rejection rate been just low enough that we didn’t notice anything wrong.
Alexander Anastasin
CEO and Co-Founder, Yung Sidekick
Cultural Bias in Performance Evaluation
We integrated AI to evaluate employee performance, aiming for objectivity and efficiency. The AI used communication style, task completion patterns, and language usage as metrics.
However, it inadvertently penalized employees from non-native English-speaking backgrounds and introverted individuals who preferred concise responses over elaborate ones.
This created friction within the team as those affected felt unfairly labeled as underperformers. It also overlooked high performers in roles where communication wasn’t critical.
The company faced backlash, leading to the suspension of the AI tool and temporary reinstatement of manual reviews.
The takeaway is that AI often amplifies cultural and contextual gaps if it isn’t trained with diverse datasets and clear ethical guidelines.
Before implementation, it’s crucial to assess how metrics might disadvantage subsets of employees and include cross-functional reviews to mitigate biases. Otherwise, you risk damaging morale and trust in workplace technology.
The HR Spotlight team thanks these industry leaders for offering their expertise and experience and sharing their insights.
Do you wish to contribute to the next HR Spotlight article? Or is there an insight or idea you’d like to share with readers across the globe?
Write to us at connect@HRSpotlight.com, and our team will help you share your insights.
Recent Posts
The Stay Interview Landscape: Implementation and Alternatives
On-the-Job Training Strategies: What Works and Why How are leading...
Read MoreCreating a Mindful Workplace: Perspectives from HR and Business Leaders
On-the-Job Training Strategies: What Works and Why How are leading...
Read MoreOn-the-Job Training Strategies: What Works and Why
On-the-Job Training Strategies: What Works and Why How are leading...
Read MoreBeyond the Breaking Point: Sharing Strategies to Combat Employee Burnout
Beyond the Breaking Point: Sharing Strategies to Combat Employee Burnout...
Read More
