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AI Recruitment Risks: Experts Uncover Biases and Share Fixes

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AI Recruitment Risks: Experts Uncover Biases and Share Fixes

Get ready for a deep dive into the future of hiring!

AI-driven recruitment tools are speeding up talent acquisition with incredible efficiency, but they’re also raising eyebrows over bias and fairness.

These systems can supercharge hiring, yet their potential to entrench inequities or miss diverse talent is a real concern.

To tackle this hot topic, the Techronicler team connected with HR gurus, AI experts, visionary thought leaders, and business trailblazers to answer a big question:

Despite concerns of potential bias, AI-driven hiring is gaining traction. In your opinion, what’s one serious adverse consequence of this practice in your industry, and how is your organization addressing it?

Their insights unpack real challenges—from amplifying biases to misreading candidate potential—while showcasing smart solutions like transparent algorithms, diverse data sets, and human oversight.

Join us as we uncover the risks of AI in hiring and the bold strategies organizations are using to champion fairness.

Discover how these leaders are striking a balance between cutting-edge tech and equity to pave the way for a more inclusive recruitment future!

Read on!

David Case
President, Advastar

David Case – Advastar

As a recruiting firm leader, I’ve seen firsthand how AI tools can improve the efficiency and accuracy of hiring. But I’ve also seen the risks they pose when used without proper oversight, especially in industries like construction and manufacturing, where our firm focuses most of its work.

One major concern is bias against candidates with non-linear career paths. These are common in both construction and manufacturing, which have also historically been male-dominated fields. AI hiring tools trained on historical data from such industries can end up favoring male candidates and overlooking others, and also tend to struggle with identifying transferable skills, meaning candidates with nontraditional backgrounds are often screened out unfairly.

Given the persistent talent shortages in the skilled trades and manufacturing sectors, employers simply can’t afford to lose strong candidates due to biased or incomplete algorithms. Overreliance on AI makes that more likely.

That’s why we pair AI tools with human oversight. For hard-to-fill roles, our recruiters manually review candidates who were initially screened out by AI. We also conduct regular audits of AI-driven decisions to spot and correct patterns of bias. I’d strongly encourage other employers using AI in hiring to do the same. Efficiency is important, but not at the cost of missing out on exceptional talent.

Justin Belmont
Founder & CEO, Prose

Justin Belmont – Prose

One major risk is automating bias at scale—if the AI’s trained on biased data, it’ll quietly filter out amazing candidates who don’t “look like” past hires.

In marketing, that can kill creativity and diversity fast.

We’re tackling it by keeping humans in the loop at key points and regularly auditing the tools for patterns that look off.

No set-it-and-forget-it.

If the AI’s making decisions, we’re making damn sure we know how and why.

George Fironov
Co-Founder & CEO, Talmatic

George Fironov – Talmatic

Despite the fact that AI has been with us for a long time, its use in different industries still raises many questions. And recruiting isn`t an exception.

A grave adverse effect of AI-powered hiring is the amplification of inherent biases in historical data, which can inadvertently exclude qualified candidates from underrepresented backgrounds.

To avoid this, Talmatic continuously audits our AI systems, employs training data sets that are diverse, and incorporates algorithmic recommendations into formal human review to guarantee fairness and accountability throughout the hiring process.

Vivek Mehta
Co-Founder & CEO, Weeve AI

Vivek Mehta – Weeve AI

A health system we advised saw applicant diversity drop sharply after deploying AI-powered hiring. The culprit? The model was trained on outdated job descriptions—rewarding familiar schools, linear resumes, and “no gaps.” It didn’t just miss out on great people—it reinforced the same old mold.

This wasn’t a tech glitch. It was a leadership miss.

AI doesn’t absolve us of judgment. It demands more.

Even the smartest systems drift without oversight. And in hiring, those drifts turn into quiet exclusions. That’s why high-impact leaders don’t just deploy AI—they guide it.

Here’s what they do:

Human-led, AI-augmented hiring: AI can flag patterns. People make the call. Always review for mission fit and lived context.

Bias audits beyond the checkbox: Track who advances—and who doesn’t. Patterns reveal what metrics alone can’t.

Transparency with teeth: Be clear with candidates about how AI is used. Offer opt-outs. Invite feedback. Build trust by design.

Design with lived voices: Involve ERGs, DEI leaders, frontline managers early. They see what the data misses.

There’s something more! What if the real breakthrough with AI in hiring isn’t speed at all—but finally seeing the people and potential we’ve always missed?

It’s not faster filtering. Not cheaper sourcing. Deeper understanding.

The best systems don’t just scan resumes—they talk to people.

Conversational AI engages applicants directly, surfacing what truly matters: how they think, connect, solve problems. You hear their values—the ones that already live in your organization, or the ones you wish did.

That’s the future—not automation for efficiency, but intelligence for alignment.

Great leaders use AI to spot brilliance others miss.

Not to filter people out—but to finally see them.

Eugene Mischenko
President, E-Commerce & Digital Marketing Association

Eugene Mischenko – E-Commerce & Digital Marketing Association

One of the most serious adverse consequences I see with AI-driven hiring is the risk of reinforcing legacy bias while creating the illusion of objectivity. In e-commerce and digital marketing, where growth depends on adaptable, creative teams, this is particularly dangerous. If a hiring algorithm is trained on historical data from a company that has favored a specific profile – consciously or not – it will perpetuate those patterns. This can quietly filter out unconventional talent, narrowing the team’s perspective and limiting innovation.

I have seen this first-hand in consulting engagements with multinational retailers and agencies. One client adopted an AI screening tool expecting it to broaden their talent pool. Instead, they noticed a subtle but consistent decline in candidate diversity – not only in demographics, but also in thought and experience. The system was favoring profiles that closely matched their legacy hires, even though the company’s strategy was shifting toward new markets and skills.

At the E-Commerce & Digital Marketing Association, we work with member companies to actively mitigate this risk. We treat AI as an efficiency tool, not a decision-maker. Every algorithm is audited by both HR and operational leaders before deployment. More importantly, we insist on regular outcome reviews, comparing AI-driven recommendations with business results and team performance. Where the data reveals patterns of exclusion, we adjust both the data inputs and the role definitions.

From a leadership perspective, it is critical to remember that hiring decisions shape the organization’s future capabilities. AI can streamline initial screening, but it cannot detect potential, adaptability, or cultural fit as a seasoned executive can. In my experience, the best results come when AI is paired with thoughtful human review, guided by a clear understanding of the shifting business context. This approach not only reduces bias, but ensures that teams stay dynamic and well equipped for rapid change.

Samantha Gregory
Self-Care Strategist & Culture Consultant, Workplace Alchemy

Samantha Gregory – Workplace Alchemy

One major consequence of AI-driven hiring is the exclusion of qualified, diverse candidates due to flawed training data. I’ve seen this firsthand as a SCORE business consultant supporting small business owners expanding their teams. These entrepreneurs often rely on AI tools to save time but unknowingly inherit biased algorithms trained on outdated, homogenous hiring patterns.

In my own work, I’ve built S.A.M.I., a digital well-being coach I trained on my original intellectual property, not general machine learning data. This personalized approach ensures culturally competent, context-aware support. Companies can adopt a similar model by customizing their AI tools, enhancing inputs, and incorporating values-aligned data to eliminate bias.

Diverse hiring isn’t just a checkbox; it’s a strategy. When AI is paired with inclusive design and human insight, it can surface well-rounded candidates who bring hard-won experience, education, and fresh perspectives that strengthen workplace culture.

Ulad Stsepuro
HR Director, ScienceSoft

Ulad Stepuro – ScienceSoft

I see two serious consequences here.

The first is discrimination. Since machine learning models are trained on historical hiring data, they may inherit past biases related to gender, ethnicity, or age, for example.

The second is an increase in conflicts within teams.

In my experience, human recruiters are still better at evaluating a candidate’s soft skills and their ability to integrate into a specific team. It’s not all just about technical skills — a poor team fit can quietly erode morale and productivity for months. It often takes a while to identify the source of the issue and even longer to reorganize the team or part ways with someone who is the wrong fit.

At ScienceSoft, we use a complex, multi-step hiring process managed by people, not AI.

Our recruiter initially selects candidates whose profiles best match the role, then forwards their resumes to technical specialists. This ensures that qualified candidates are not overlooked due to non-technical judgment.

Only those approved by the technical team proceed to the next step. Then, the selected candidates are invited for a behavioral and culture-fit interview with our HR team.

After that, the candidate undergoes a technical assessment. Depending on the role, that could be a technical test or a practical task relevant to the position. Those who pass the assessment are then interviewed by our technical team for a more in-depth evaluation.

A final interview with the department head ensures alignment with team goals and expectations. Successful applicants undergo thorough background checks, which include verification of their identity, employment history, education, and professional references.

Another important point is that the recruiter receives a bonus if the candidate they recommend is hired and proves to be a strong fit for the role. This way, the recruiter is highly motivated to remain objective and focus on finding the most qualified candidates.

James Francis
Founder, Artificial Integrity

James E. Francis – Artificial Integrity

When AI drives hiring, the hiring process is far more efficient, but it can also entrench bias in recruiting. If an AI model is trained on historical data that captures biased hiring decisions (for example, bias on the basis of gender, race, or age), it could replicate these biases in future decisions.

For example, an AI system may unintentionally reward candidates who are similar to past hires if it filters out equally competent brains. By weakening fairness, this also hampers organizational diversity, which, according to several studies, is essential for innovation and success.

At Artificial Integrity, we try to minimize this problem by ensuring that our AI tools are regularly audited for fairness and bias-free algorithms. By ensuring such biases are not a part of our training data and implementing checks for equity, we are creating systems that promote inclusion.

Eric Walczykowski
CEO, Bespoke Partners

Eric Walczykowski – Bespoke Partners

The old software principle, “garbage in, garbage out,” still applies in AI. Train your model using data only from your previous talent searches and hiring and you’ll repeat the same patterns.

Everyone using AI Chatbots for candidate discovery is likely affected by bias and recycling former candidates instead of finding new ones.

We take a completely different approach. AI’s real power is processing huge amounts of data, recognizing patterns, and forming logical connections.

Instead, our AI-driven talent market mapping platform, the Executive Index, maps every executive in the US software industry. It’s nearly 700,000 executive profiles, assembled from 53 million executive background data lines from 575,000 sources.

Our clients can see the entire talent market, filter it in real-time, and see who could solve their search.

There is no possibility of bias or narrow, repetitive thinking because you see the whole market, not a narrow slice based on past work.

The HR Spotlight team thanks these industry leaders for offering their expertise and experience and sharing these 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.

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Strengthening Remote Team Retention: Building a Connected and Loyal Global Workforce

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Strengthening Remote Team Retention: Building a Connected and Loyal Global Workforce

In 2025, remote and hybrid work models have become the cornerstone of the global workplace, driven by technological advancements and shifting employee expectations. 

A 2024 Gartner report indicates that 47% of organizations worldwide have adopted permanent hybrid or fully remote structures, with millions of employees working outside traditional office settings. 

While this shift offers flexibility, it presents a critical challenge: retaining top talent in a virtual environment where physical proximity and office culture no longer serve as unifying forces. With global employee turnover rates averaging 10-15% annually (Deloitte, 2024), effective retention strategies are essential to maintaining a motivated and loyal workforce.

Retaining remote teams requires more than digitizing office routines. It demands an intentional, empathetic, and purpose-driven framework to foster connection, engagement, and growth. Drawing from proven strategies and enriched with global insights and statistics, this article provides a robust blueprint for enhancing remote team retention.

Architecting a Robust Communication Ecosystem

Effective communication is the foundation of remote team cohesion, countering the isolation and disengagement that can erode morale. According to a 2023 Gallup study, 70% of remote workers feel disconnected without structured communication. To address this, organizations must prioritize deliberate, multi-layered communication strategies.

Establish a Predictable Rhythm: Consistency builds trust and alignment. Implement a structured cadence of interactions, including weekly team huddles to review goals, bi-weekly one-on-one check-ins to address individual needs, and monthly company-wide updates to reinforce the organization’s mission. 

Use a mix of synchronous tools like Zoom or Google Meet for real-time collaboration and asynchronous platforms like Slack, Trello, or Notion for flexible task management. 

Over-communication is key—assume clarity requires explicit reinforcement. A 2024 Microsoft Work Trend Index found that teams with regular check-ins report 25% higher engagement scores.

Engineer Informal Connections: The absence of impromptu office chats weakens team bonds. A 2024 LinkedIn survey revealed that 62% of remote workers miss casual workplace interactions. 

To recreate these “water cooler” moments, create dedicated channels on collaboration platforms for non-work discussions—think #CoffeeBreak, #PetPics, or #TravelStories, where employees share personal updates or hobbies. 

Virtual coffee chats, online trivia, or themed team events (e.g., global holiday celebrations) further nurture camaraderie. Tools like Donut, which randomly pairs employees for virtual meetups, have boosted team connection by 20% in some organizations (Donut, 2024).

Leverage Technology for Engagement: Platforms like Microsoft Viva or Culture Amp provide analytics to monitor employee sentiment, while tools like Miro enable collaborative brainstorming. 

With 78% of remote workers using collaboration tools daily (Statista, 2024), integrating these solutions bridges geographical gaps and fosters a sense of belonging.

Anchoring Talent with Purpose and Growth Opportunities

Remote employees often feel disconnected from the company’s vision or fear career stagnation. A 2024 SHRM study found that 55% of remote workers cite lack of growth opportunities as a key reason for leaving. To counter this, organizations must anchor talent with purpose and clear development pathways.

Create Transparent Career Pathways: Regular one-on-one discussions focused on career aspirations are essential. Leaders should align employees’ goals with projects or upskilling opportunities, such as certifications in high-demand fields like AI, cybersecurity, or project management. 

For example, global companies like Salesforce offer tailored learning through platforms like Trailhead, reporting a 15% reduction in turnover among participants (Salesforce, 2024). Providing access to online learning platforms like Coursera or LinkedIn Learning demonstrates commitment to professional growth.

Connect Work to the Mission: Employees stay engaged when they understand their role in the bigger picture. 

Regularly communicate how individual contributions drive organizational goals, using town halls, newsletters, or dashboards to share progress. Celebrate wins—both big and small—to reinforce impact. 

A 2023 Harvard Business Review study showed that employees who feel their work is purposeful are 30% less likely to leave.

Foster Internal Support Systems: Mentorship programs or “buddy systems” create stability and connection. 

Pairing new hires with experienced colleagues or encouraging cross-functional peer support mitigates isolation. 

A 2024 BambooHR survey found that 68% of remote employees with mentors report higher job satisfaction.

Building a Culture of Trust, Care, and Autonomy

A thriving remote culture recognizes employees as individuals with unique needs. A 2024 Mercer study revealed that 60% of employees prioritize workplace flexibility and mental health support when choosing employers. Retention hinges on empathy, trust, and inclusivity.

Lead with Empathy and Flexibility: Acknowledge diverse personal circumstances by offering flexible work hours and supporting work-life balance. Provide mental health resources, such as access to counseling platforms like BetterHelp or employee assistance programs (EAPs). 

Companies like Google have seen a 10% increase in retention after expanding wellness initiatives (Google, 2024). Simple gestures, like allowing time off for personal milestones, signal genuine care.

Grant Trust and Autonomy: Micromanagement erodes morale. Trust employees to manage their work, focusing on outcomes rather than hours logged. A 2023 Owl Labs study found that 74% of remote workers report higher job satisfaction when given autonomy. 

Tools like OKRs (Objectives and Key Results) help align expectations without stifling independence.

Ensure Inclusivity and Visibility: In virtual settings, quieter voices can be overlooked. Create an open culture where all ideas are valued, using tools like anonymous surveys or moderated discussions to encourage participation. 

Regular feedback loops and recognition programs ensure everyone feels seen. A 2024 Glassdoor study showed that employees who feel valued are 25% less likely to seek new opportunities.

Measuring and Sustaining Retention Efforts

Retention is an ongoing process requiring data-driven insights. Use pulse surveys, eNPS (employee Net Promoter Score), or exit interviews to gauge satisfaction and identify pain points. 

A 2024 Workhuman report found that organizations with regular feedback loops see 14% lower turnover. Invest in analytics platforms like Qualtrics or Glint to track engagement trends and adjust strategies proactively.

Additionally, benchmark against industry standards. For example, tech companies with strong remote cultures, like GitLab and Atlassian, maintain turnover rates below 10% by prioritizing asynchronous communication and employee autonomy (Slack, 2024). Regularly revisit training data and employee feedback to refine your approach.

Conclusion: A System for Lasting Connection

Retaining a remote workforce isn’t about constant oversight or endless meetings. It’s about building a system of connection, purpose, and trust so robust that physical distance becomes irrelevant. 

The formula is clear: communicate intentionally, align work with meaning, and empower with care. 

By implementing these strategies, organizations can create a resilient, engaged, and loyal remote team ready to thrive in the evolving global workplace.

Written by Grok and Gemini with inputs from the HR Spotlight team and information sourced from Gartner, Deloitte, LinkedIn, Statista, SHRM, Salesforce, Harvard Business Review, BambooHR, Mercer, Google, Owl Labs, Glassdoor, Workhuman, Slack, Donut, and Microsoft Work Trend Index.

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.

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From Blame to Ownership: Leaders Share Accountability Solutions

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From Blame to Ownership: Leaders Share Accountability Solutions

Nothing sinks a team’s potential faster than a culture of blame. While everyone agrees accountability is the foundation of high performance, the all-too-common instinct to point fingers instead of taking ownership can be a huge roadblock to success.

This isn’t just about hurt feelings; it has real costs. Blame-shifting, often born from a fear of failure, can crush morale and has been linked to a steep 20% drop in employee engagement (Gallup, 2024). In today’s tight 2025 talent market, with a low 3.5% unemployment rate (SHRM, 2025), no business can afford that kind of hit. Cultivating a culture of ownership isn’t just a nice-to-have; it’s a competitive necessity.

So, how can leaders effectively turn a tide of blame into a wave of personal ownership? The HR Spotlight team went directly to the source, asking seasoned HR and business leaders:

“When blame-shifting starts to undermine team morale and growth, what are your most effective, go-to strategies for building a stronger culture of accountability?”

From simple communication hacks to smart tech solutions, their responses provide a powerful playbook for creating a culture of trust and teamwork—empowering organizations not just to meet today’s challenges, but to truly thrive.

Read on!

Raymond Anto
Founder, Congruen

Raymond Anto – Congruen

Want to unlock accountability on your team? It’s not about complex theories; it’s about two game-changing habits: total clarity and leading by example!

Banish Ambiguity: Fuzzy instructions lead to zero results. That’s where accountability crumbles! So, ditch the vague, “Let’s hope this gets done,” and level up in a crystal-clear direction like, “Zui, you’re owning the proposal draft, and Friday is our launch day!” This isn’t about being bossy; it’s about setting your team up for a win. When everyone knows their exact play, the whole team scores.

Leaders Own It, First: If I drop the ball, I’m the first to raise my hand. I’ll tell my team, “I messed up here, here’s how I’m fixing it, and here’s my plan so it won’t happen again.” This one move is a culture-shifter. It instantly replaces the dreaded blame game with a “we’re-in-this-together” vibe. When leaders own their mistakes, it empowers everyone to do the same.

Ultimately, awesome accountability isn’t about calling people out. It’s about creating a high-trust space where everyone is excited to own their part and knows they’ll be supported when they stumble. That’s how you build an unstoppable team!

Justin Tardif-Francoeur
Co-Founder, Montreal Weights

Justin Tardif-Francoeur – Montreal Weights

I prioritize clear expectations and open communication.

I set specific, measurable goals for each team member and ensure they understand their role in achieving them. Regular check-ins help track progress, address roadblocks, and maintain alignment.

I also foster a culture of ownership by empowering employees to make decisions within their roles and providing constructive feedback when needed.

Lastly, recognizing achievements and holding individuals accountable for their responsibilities helps reinforce a sense of ownership.

This balanced approach creates an environment where accountability is built into daily operations and leadership.

Gregory Shein
CEO, Nomadic Soft

Gregory Shein – Nomadic Soft

To improve accountability, I implement clear role definitions, measurable KPIs, and consistent feedback loops. Establishing a culture of ownership through transparent communication and leading by example is essential. I also use project management tools to track responsibilities and outcomes visibly.

Regular retrospectives help teams reflect constructively without assigning blame. Training in emotional intelligence and conflict resolution further reinforces accountability. Recognizing accountability-driven behavior publicly strengthens its value. Ultimately, when expectations are explicit and support systems are in place, accountability becomes a shared standard rather than a forced obligation.

Kemi Chavez
Chief People Officer, Blue Federal Credit Union

Kemi Chavez – Blue Federal Credit Union

Shifting blame might feel easier in the moment, but it doesn’t move us—or our people—forward.

At Blue, we believe accountability is less about calling people out and more about calling them up. It’s about creating an environment where people feel trusted, supported, and clear on how their work contributes to something bigger.

We focus on setting expectations early, keeping communication open, and leading by example. And when mistakes happen, we use them as moments to grow—not setbacks to dwell on.

That mindset is a big part of why we’ve been recognized with several workplace excellence awards. But more importantly, it’s what keeps our teams connected and our culture strong.

We’re always learning, always improving—and always rooting for one another.

Mike Lyons
HR Consultant, Seasoned Advice

Mike Lyons – Seasoned Advice

To generate accountability, it’s important to first create trust through regular face to face conversations. When a manager combines this with curiosity, it can lead to deep conversations about the status of work, the obstacles, and the objectives of the team. With trust and curiosity, employees are much more likely to open up.

Doug Crawford
Founder, Best Trade School

Doug Crawford – Best Trade Schools

When it comes to improving accountability, I’ve learned over the years that setting clear expectations and leading by example make all the difference.

If you show your team that you’re willing to take responsibility for your actions, it encourages them to do the same.

I make sure to communicate expectations upfront so that everyone knows what they’re responsible for, and then I hold regular check-ins to see where things are going. I’ve found that these check-ins are less about pointing out mistakes and more about figuring out how to move forward.

If someone slips up, I want them to feel comfortable owning up to it without fearing judgment.

Encouraging this kind of environment helps build trust within the team, and it cuts down on the blame game because people realize that owning their mistakes is just part of the growth process.

Jonathan palley
CEO, QR Codes Unlimited

Jonathan Palley – QR Codes Unlimited

One of the things I’ve worked to make clear to our entire management team is that the successes and failures of their direct reports ultimately reflect on them–and that goes all the way up to me.

This doesn’t mean that we won’t identify individuals who are underperforming, or recognize people who have gone above and beyond, but ultimately, I believe in collective accountability.

Abraham Samuel
Outreach Strategist, BoostMyDomain

Abraham Samuel – BoostMyDomain

We made a simple but powerful switch on our team: we stopped viewing accountability as a dreaded disciplinary tool and started treating it as a core cultural value.

A game-changer for us was introducing “decision retros.” We don’t just review mistakes; we review every major call the team makes, walking through the context, choices, and outcomes. This isn’t optional, and the result was that scapegoating vanished almost overnight because the spotlight became shared, not targeted.

To bring ownership into the open, we also ditched vague job descriptions for dynamic “accountability maps.” Everyone’s name is publicly attached to specific outcomes. So, if a goal slips, the conversation immediately becomes about the structure, not the person. It’s about, “How can we fix the process?” instead of, “Who’s to blame?”

Let’s be clear: this isn’t micromanagement; it’s radical clarity. In today’s fast-paced, AI-driven world, vague accountability just doesn’t cut it. It’s often a fast track to a blame-shifting culture, which is usually a symptom of unclear boundaries.

The magic formula is pairing psychological safety with crystal-clear responsibility. When people know their fingerprints are on an outcome, they instinctively start thinking like owners. I’ve personally seen this shift turn passive employees into some of our most proactive, strategic thinkers.

You can’t build a resilient culture if ownership stays in the shadows. Our rhythm is simple: See it. Own it. Solve it. That’s how you build a team that thrives.

Danilo Coviello
Founding Partner, Espressotranslations

Danilo Coviello – Espresso Translations

I am all about creating a culture of accountability that feels natural, not forced. One key practice I have found effective is setting clear, specific expectations right from the start.

A few months ago, I launched a new project where we implemented a simple “daily goal tracker” that each team member filled out. It was not about micromanaging but about giving everyone visibility into where they stood, which built a sense of personal responsibility.

Since then, we’ve seen a 30% improvement in task completion rates within deadlines, all because each person had a clear sense of ownership. This has made a big difference in productivity and has helped everyone stay aligned.

I also believe in leading by example. When I slip up, I own it and turn it into a learning opportunity.

For instance, I missed a key deadline a while back, and instead of deflecting, I shared with the team how I would adjust my approach to avoid similar issues. This transparency set the tone for the rest of the group to do the same.

We have now incorporated a “learning moment” into every meeting, where we discuss what worked and what did not.

The changes in atmosphere have transformed accountability from a demanding duty into a necessary component of development.

The HR Spotlight team thanks these industry leaders for offering their expertise and experience and sharing these 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.

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Overtime Overhaul: New Rules, New Challenges

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Overtime Overhaul: New Rules, New Challenges

The U.S. Department of Labor’s new overtime rule represents one of the most significant compensation shifts in years. 

By dramatically raising the salary threshold for exempt status under the Fair Labor Standards Act (FLSA), the rule reclassifies millions of American workers, making them newly eligible for overtime pay.

For HR teams, this is far more than a simple compliance update; it’s a massive operational challenge with deep financial and cultural implications. 

The hurdles of implementation vary widely across industries—a tech startup with a flexible “always-on” culture faces a different set of problems than a retail chain with thousands of store employees whose duties must now be meticulously tracked.

Navigating this transition successfully requires foresight and a clear understanding of the potential pitfalls. 

To gain on-the-ground perspective, we turned to a panel of seasoned HR experts and business leaders from across industries with one critical question:

“As HR teams update overtime pay compensation in light of recent legislative updates, what is one implementation challenge they could potentially face in your industry?”

Their insights serve as an essential guide for any organization working to align with these new regulations, revealing the key challenges and strategic considerations for a smooth and compliant transition.

Read on!

Martin Weidemann
Owner, Weidemann.tech

Martin Weidemann

One of the biggest implementation challenges is adapting legacy payroll systems to handle nuanced, real-time rule changes across multiple jurisdictions—without disrupting operations.

In my own companies, which span across fintech and luxury services in Mexico, this became clear when managing a team with hybrid shifts, bonuses, and on-call structures. Many payroll platforms simply weren’t built for dynamic rules tied to hours worked, variable rates, or multi-role staff.

What made it even more complex was the communication gap between legal updates and HR tech—compliance would change, but systems lagged behind. We had to bridge that manually, often by updating spreadsheets or APIs on the fly. It’s not just a technical issue; it’s an operational one that impacts trust, accuracy, and morale. And for industries that move fast, like tech or aviation, lagging here can mean real legal risk.

Joe Spisak
CEO, Fulfill.com

Joe Spisak

One significant challenge HR teams in our industry face when implementing updated overtime pay regulations is managing the cost implications across a diverse workforce with varying seasonal demands.

In the 3PL world, we operate in an environment where peak seasons can require substantial overtime hours from warehouse staff. The recent increases in salary thresholds for exempt employees—moving from $684 to $844 weekly, and eventually to $1,128 weekly—create a complex reclassification puzzle that affects operational planning.

I’ve seen firsthand how this impacts our partners. A mid-sized 3PL we work with recently had to reclassify nearly 30% of their warehouse supervisors as non-exempt, dramatically changing their labor cost structure. Their HR team wasn’t just dealing with payroll adjustments—they were navigating employee morale issues as formerly salaried staff adjusted to punching time clocks.

The implementation challenge extends beyond paperwork. It requires recalibrating entire workforce management systems, especially when dealing with seasonal volume fluctuations. Many 3PLs have traditionally relied on flexible overtime arrangements during peak periods, and these regulatory changes force a fundamental rethinking of staffing models.

What makes this particularly challenging is the timing—these changes are hitting during a period when fulfillment operations already face margin pressure from rising carrier rates and warehouse space costs.

For HR teams, it’s not simply about compliance; it’s about implementing these changes while preserving operational efficiency and maintaining service levels for eCommerce clients who expect consistent performance regardless of regulatory shifts.

The most successful implementations I’ve witnessed involve HR partnering closely with operations to model different workforce scenarios, using data analytics to predict impact points, and creating clear communication channels to help employees understand how and why their compensation structures are changing.

Chris Brewer
Managing Director, Best Retreats

Chris Brewer

In the wellness retreat industry, one big challenge HR teams face updating overtime pay due to 2024 FLSA changes is reclassifying exempt employees to non-exempt. Many retreat staff, like facilitators, were salaried above the old $684 weekly threshold but fell below the new $844 (July 2024) or $1128 (January 2025).

Tracking hours for these roles, often involving irregular schedules at remote sites, is a nightmare. I saw a Peru retreat struggle with this—staff felt micromanaged when asked to log hours, tanking morale. Advice? Use simple time-tracking apps like Toggl and train managers to communicate the change as a fairness win, not a demotion.

Andy Danec
Owner, Ridgeline Recovery LLC

Andy Danec

One of the biggest implementation challenges we face in the addiction treatment industry when updating overtime pay policies is balancing compliance with continuity of care. At Ridgeline Recovery, our team operates 24/7. Clients don’t stop needing support just because the clock hits a certain hour. That means our counselors, support staff, and medical team often work odd hours, weekends, or get called in during emergencies.

With new overtime legislation, HR teams must rethink scheduling, payroll structures, and staffing without disrupting client care. The problem? You can’t always predict how long a crisis will last. Forcing strict cutoff times or limiting hours to control costs can create gaps in care or lead to burnout if team members feel like they’re being micromanaged around the clock.

We addressed this by investing in better workforce management software—real-time tracking, clear overtime alerts, and smart scheduling based on actual demand. But the real shift was cultural: making sure our staff understood their rights, our obligations, and that any changes in policy wouldn’t compromise the mission.

HR must walk a tightrope. You have to stay compliant, yes—but in healthcare and recovery, you also have to stay human. That’s the challenge.

Joel Miller
President, Miller Pest & Termite

Joe Miller

One big challenge I’ve seen firsthand is adjusting overtime policies for employees who split their time between roles that do and don’t qualify for overtime.
We encountered this issue at a field services company, where some team leads were hands-on in the field part of the week. The rest of the time, they handled scheduling and reporting.

When the new rules took effect, HR had a difficult time determining when those employees were eligible for overtime and when they weren’t. It was a tracking nightmare and led to some underpayments early on, which we had to correct.

We eventually moved to a time-tracking system that let employees categorize their hours by activity type, but even that took weeks of training and buy-in. The key learning was that compliance isn’t just about updating policy—it’s about making sure the tools and behaviors on the ground support it. You can’t rely on memory or assumptions when classifying labor anymore. To stay ahead of these changes, you must design your workflows to reflect the law, not the other way around.

Derek Emery
CEO, Cash For Cars Los Angeles

Derek Emery

Being the CEO of Cash for Cars Los Angeles since 1999 and having a 30-plus years of experience in the sphere of business and finance, I have noticed that the HR teams working in the sphere of automotive services have a peculiar problem with adjusting to the new policies of paying overtime: matching the inflexible legislative system with the anarchic pace of the industry.

Our industry is driven by uncertainty unlike the predictable office settings, seasonal peaks (e.g. holiday vehicle sales), post-disaster sudden rise requests, and inventory cycles that rise and fall.

As an example, customer traffic can repair suddenly and double because of one hailstorm, and technicians have to work long hours.

However, new overtime regulations offer tight limits on the number of hours as well as complicated payments calculations, which presents a paradox: limit overtime to meet the regulations, and lose income during busy periods; be flexible, and watch labor costs spiral.

The other potential obstacle that has been ignored is the fragmented workforce in our industry. The auto service positions, techs, sales people, detailers all have different pay structures (salespeople get commissions, mechanics get piece rates).

It is a minefield of compliance to design overtime policies that reasonably take such disparities into consideration.

A survey by the Automotive Service Association (2021) found that 38% of companies are having a hard time retaining skilled technicians; errors in pay transparency may help speed up the process.

Workers may leave in anticipation in case they dread earning less income in the event of new regulations, thus incurring fewer hiring expenses than the cost of conformity.

Finally, there is the integration of technology that makes it difficult. Automation increases efficiency, but watching over AI-generated diagnostics or answering customer portal requests after hours erases the distinction of a regular workday.

Defining overtime applicability to hybrid jobs (ex: a technician who manages robotic repairs) requires imaginative resolutions- something that HR departments seldom have to deal with in non-tech intensive sectors.

Workforce planning, flexible scheduling software, and honest communication are not negotiable when it comes to handling these legislative changes without compromising the quality of service and staff morale.

Mark Niemann
CEO & Co-Founder, MeinOffice

Mark Niemann

One key implementation challenge HR teams may face when updating overtime pay stems from the complexity of aligning compliance with operational agility, particularly in industries like ECommerce and tech-driven services:

Varying job roles: The rapid evolution of hybrid roles in marketing, content creation, and customer experience makes classification under new wage regulations harder.

System integration: Legacy HR and payroll systems often lack the flexibility to adapt quickly, leading to delays or inaccurate calculations.

Talent retention risk: Sudden compensation structure changes can affect morale or prompt dissatisfaction if not communicated transparently.

To mitigate these, it’s essential to:

  • Conduct job audits to clearly define exempt vs. non-exempt roles.
  • Upgrade digital tools for real-time compliance tracking.
  • Proactively communicate policy changes to build understanding and trust.

Andres Bernot
Founder, WOW! Shirts

Andres Bernot

HR departments in the clothing trade encounter a problem linking changes in overtime compensations with varying production patterns in the light of new laws.

We are selling shirts, we work with made-to-order, custom design, so we can rapidly increase workload, especially when there is a seasonal trend.

For example, when some new design is popular we usually have many orders that need overtime. Compensating in such peaks may be complicated.

Without a swift response and clear communication of changes by the HR teams, employees could develop a belief that the system is not fair, which can be dejecting.

To manage that, the HR needs to juggle between the legality and the effective communication so that the employees could feel appreciated and so that there would be no kinks in the working process at such crucial times.

Dr. Kirk Adams
Disability, Equity, & Inclusion Advisor, Innovative Impact LLC

Dr. Kirk Adams

When HR gets overtime policy wrong, it’s not just a payroll issue. It’s a people issue.

Employees with disabilities often work under modified schedules. Some share roles. Others use assistive tech.

These accommodations change how hours get tracked. But most systems weren’t built for that.

They miscount hours. They miss productivity. And they cause underpayment.

Not because of bad intent but because of bad design. That’s where trust breaks. That’s where legal risk grows.

HR leaders must act. Train your managers. Choose systems that flex. Bring in experts who understand disability inclusion.

Compliance is the floor. Equity is the goal. Leadership means knowing the difference and doing better.

Hayley Gillman
CEO, BOTI

Hayley Gillman

The main obstacle for HR teams extends beyond numerical challenges because it involves dealing with human aspects of organizational change.

The change from exempt to non-exempt employee status affects payroll operations while transforming employee perceptions about their work responsibilities. The shift in tracking work hours creates a sense of micromanaging for employees who previously enjoyed flexibility in their work. When communication about compliance updates is not handled properly the process transforms into a perceived demotion for employees.

The key? The solution requires organizations to modify both their policies and employee attitudes. The explanation should include both legal requirements and fair pay principles and employee protection aspects. Managers need training to conduct these conversations while showing understanding toward their team members. Organizations should spend money on tools that provide smooth time tracking experiences instead of creating overwhelming situations.

The actual expense of overtime updates exceeds monetary costs because it damages employee trust.

The HR Spotlight team thanks these industry leaders for offering their expertise and experience and sharing these 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.

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Powering Up AI Hiring: Solutions for a More Equitable Future

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Powering Up AI Hiring: Solutions for a More Equitable Future

As AI-driven hiring tools gain momentum, they promise efficiency and scale in talent acquisition, but they also spark concerns about bias and fairness.

While these systems can streamline recruitment, their potential to perpetuate inequities or overlook diverse talent is a pressing issue.

To dive into this complex topic, the HR Spotlight team reached out to HR experts, AI specialists, thought leaders, and business executives to address a critical question:

Despite concerns of potential bias, AI-driven hiring is gaining traction. In your opinion, what is one serious adverse consequence of this practice within your industry, and how is your organization mitigating this risk?

Their responses reveal real-world challenges, from reinforcing existing biases to misjudging candidate potential, alongside proactive strategies like transparent algorithms, diverse training data, and human oversight.

Join us as we explore the risks of AI in hiring and the innovative solutions organizations are deploying to ensure fairness.

Discover how these leaders are navigating the delicate balance between technology and equity to shape a more inclusive future for recruitment.

Read on!

Ger Perdisatt
CEO & Founder, Acuity AI Advisory

Ger Perdisatt – Acuity AI Advisory

When AI optimises for what worked before, it quietly filters out the people you actually need next.

The real risk in AI-driven hiring isn’t traditional bias — gender, race, or education. It’s corporate success bias: the tendency of AI systems to replicate what has historically worked in your organisation, even when that’s exactly what won’t move you forward.

Trained on past hiring data, these tools surface “safe” candidates who mirror your existing top performers. Familiar degrees. Recognisable companies. Predictable experience. It looks like consistency — but it’s actually stagnation.

          If you’re trying to evolve, these systems quietly optimise against change.

In industries that demand fresh thinking and strategic agility, this creates dangerous blind spots. AI won’t challenge your hiring assumptions — it validates them. At Acuity, we’ve seen how even well-intentioned systems can entrench sameness when they’re designed without forward-looking intent.

The mitigation playbook:

1. Define hiring success forward, not backward.

2. Audit inputs and outcomes, not just interfaces.

3. Use AI to assist, not decide.

4. And remember: culture makes the final call.

There’s justified focus on codified bias in AI systems. But here’s the uncomfortable truth:

      AI screens who you see.

      Culture decides who you pick.

Screening algorithms may be sophisticated — but they’re optimising for yesterday’s success criteria. In a period of transformation (which describes most organisations today), that’s the wrong objective function.

Until we acknowledge this, the risk isn’t just in our tech stack. It’s in our strategic blind spots.

Because real change means hiring for who you’re becoming — not who you’ve already been.

Margaret Buj
Principal Recruiter, Mixmax

Margaret Buj – Mixmax

One serious risk of AI in hiring is that it can reinforce existing biases. If an algorithm is trained on past hiring data-and that data has skewed toward certain backgrounds, schools, or demographics-then the AI will replicate those patterns.

At Mixmax, we don’t rely on automated decision-making. As a recruiter, I use AI tools to help draft outreach or summarize candidate feedback, but I still review every application manually. Our hiring is structured, but human.

In my coaching work, I advise clients to write resumes and LinkedIn profiles that are both ATS-friendly and human-readable. But ultimately, no algorithm should replace thoughtful hiring decisions grounded in context.

Tech should support fairness, not shortcut it.

Ydette Macaraeg
Marketing Coordinator, ERI Grants

Ydette Macaraeg – ERI Grants

In the nonprofit sector, one serious adverse consequence of AI-driven hiring is the perpetuation of systemic inequities that directly contradict our mission-driven values.

AI algorithms often reflect historical hiring biases, potentially screening out candidates from underrepresented communities who bring essential lived experiences to our work. This is particularly damaging in grant-funded organizations where diversity, equity, and inclusion aren’t just buzzwords—they’re often funding requirements and core to our effectiveness.

Our organization mitigates this risk through a hybrid approach: using AI for initial resume screening while ensuring human reviewers from diverse backgrounds evaluate all candidates who advance.

We’ve also implemented bias audits of our AI tools, partnering with local universities to analyze our hiring data for disparate impact. Additionally, we maintain structured interview processes with standardized questions and diverse interview panels to counteract algorithmic bias.

The key is treating AI as a tool to enhance, not replace, thoughtful human judgment in building teams that truly reflect the communities we serve. That’s how impactful grants fuel mission success.

Ishdeep Narang, MD
Child, Adolescent & Adult Psychiatrist, Founder, ACES Psychiatry

Ishdeep Narang, MD – ACES Psychiatry

Our work in psychiatry is built on a foundation of human connection. That’s why I see the biggest danger of AI in hiring as its inability to gauge a candidate’s therapeutic presence. An algorithm can screen a resume for keywords like ’empathy’ or ‘compassion,’ but it can’t detect the genuine warmth, clinical intuition, and unwavering stability a person projects in a room.

That felt sense of safety is the bedrock of a therapeutic relationship, whether you’re working with a child who’s too scared to speak or an adult who has lost all trust in others. It’s this intangible quality that allows a patient to feel seen and begin to heal.

To mitigate this risk, I’ve made our hiring process deliberately human. While technology can handle the initial application, its role ends there. I personally meet with every candidate we seriously consider, not just to review their experience, but to understand who they are as a person. I’m looking for the things an AI simply can’t quantify.

I’m reminded of a colleague I once worked with. An AI screening their resume would have likely passed them over for someone with more prestigious credentials. But I saw firsthand the incredible humility and deep care they showed when discussing a challenging past case. That’s the kind of genuine empathy you simply can’t program an algorithm to spot.

In a field built entirely on human connection, the ultimate hiring decision must be a human one. For me, that approach is non-negotiable.

Andrew Peluso
Founder, What Kind Of Bug Is This

Andrew Peluso – What Kind Of Bug Is This

One serious risk I see with AI-driven hiring is over-reliance on pattern recognition that unintentionally filters out qualified but non-traditional candidates.

In digital marketing, some of our best hires didn’t have agency backgrounds or traditional degrees—they came from journalism, teaching, even theater. However, many AI screening tools heavily weigh resume keywords, which tends to reward individuals who already know how to “speak the language” of the industry. That creates a feedback loop where the same types of profiles continue to rise to the top, and you miss out on diverse perspectives that often lead to stronger creative and strategic work.

To mitigate this, we made a conscious decision to keep our first-round screening partially manual, especially for content and strategy roles. We use tech for volume management—like filtering for basic writing skills or location—but we don’t let AI decide who moves forward. We also include blind writing assessments early in the process.

That levels the playing field and allows us to evaluate candidates based on output, not just their resume history. It takes more time, but it’s helped us build a team with a broader range of thinking—and in our industry, that’s a competitive edge.

Joe Spisak
CEO, Fulfill

Joe Spisak – Fulfill

One serious adverse consequence of AI-driven hiring is algorithmic bias that can perpetuate workforce homogeneity. When AI systems are trained on historical logistics industry data, they risk reinforcing existing workforce patterns rather than promoting diversity.

The logistics industry already faces challenges with representation across different demographics. If AI hiring tools learn from this historical data, they may inadvertently screen out qualified candidates from underrepresented groups who don’t fit the “typical” profile, limiting perspectives and innovation potential within our partner network.

At Fulfill, we’ve implemented a hybrid approach to mitigate this risk. Our AI tools assist with initial candidate screening for our network of 650+ fulfillment partners, but we never allow them to make final decisions. Our human experts review recommendations, applying contextual understanding that algorithms lack. We’ve also invested in diverse training datasets and regular algorithmic audits to detect potential bias patterns.

I’ve personally witnessed how diverse teams deliver superior results for our eCommerce clients. One of our most successful partners initially struggled with staffing challenges until they revamped their hiring practices to be more inclusive. They now maintain a culturally diverse workforce that brings unique perspectives to problem-solving, particularly valuable when handling fulfillment for clients with global customer bases.

The real value in matching eCommerce businesses with the right partners comes from understanding nuanced needs that pure algorithms might miss. That’s why we’ve built our platform to combine technological efficiency with human expertise – creating more opportunities while ensuring fairness in an industry that depends on diverse talent to solve complex logistics challenges.

Rae Francis
Counselor & Executive LifeCoach, Rae Francis Consulting

Rae Francis – Rae Francis Consulting

One of the most serious risks of AI-driven hiring isn’t just bias in data – it’s the erosion of human connection. While AI can be helpful in screening resumes, it can’t assess presence, empathy, or emotional intelligence – qualities that shape not just how someone performs, but how they connect, communicate, and contribute to a team.

Culture isn’t built through credentials alone. It’s built in the in-between – the way someone responds to pressure, the rhythm of conversation, the energy they bring into a room. Those things can’t be captured in data, but they’re often what determine whether someone strengthens or destabilizes a company’s culture.

And when it comes to bias, we need to be honest: if overcoming our own internal biases is hard, imagine the risk of an algorithm trained on decades of biased data – one that operates at scale, without reflection or accountability. Bias isn’t just maintained through AI, it’s multiplied.

Steve Ollington
ADHD Researcher, ADHDworking

Steve Ollington – ADHDworking

Back in 2022 the BBC ran a documentary called ‘Computer Says No’, which suggested the programming behind AI interviews was discriminatory towards neurodivergent people – for example, tracking eye content and facial expressions, which would be biased against people with Autism.

The program suggested AI interviews could be made more inclusive, if the companies and people behind the technology learned about neurodivergence so they could factor that in.

That was three years ago, but unfortunately the issue still doesn’t seem to be on the developers radars. That’s a shame, because it could be used to go the other way, removing some human biases and making recruitment fairer.

Hopefully some of the businesses using this AI will begin having neuroinclusion as part of their criteria for purchase soon – which will lead to the developers of the technology ensuring the (neuro)diversity of their training data.

Martin Weidemann
Owner, Mexico-City-Private-Driver.com

Martin Weidemann – Mexico-City-Private-Driver

One of the most serious risks I’ve seen with AI-driven hiring is how easily it can codify human bias under the illusion of objectivity.

Early on, we tested an AI-based screening tool to help preselect drivers. On paper, it seemed perfect—fast, data-driven, and consistent. But within a few weeks, we noticed a trend: local applicants from low-income neighborhoods in Mexico City were being filtered out disproportionately.

The algorithm had learned to prioritize “punctuality” using proxies like previous job addresses, but what it really did was penalize people who lived further from wealthier zones—where traffic is unpredictable and transit infrastructure lacking. The system had no context for the realities of commuting in Mexico City.

We immediately pulled the plug.

Since then, we’ve gone back to human-led screening, but with one key upgrade: we now use AI only as an assistive tool—not a gatekeeper. It flags applications for review, but final decisions always rest with a trained human who understands local nuance and context. And we track the demographic impact of every hiring round to ensure we’re not repeating mistakes behind the scenes.

For us, tech is there to scale human empathy—not replace it.

The HR Spotlight team thanks these industry leaders for offering their expertise and experience and sharing these 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.

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Hard-Won Wisdom: Early Career Lessons That Shaped Leaders’ Paths

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Hard-Won Wisdom: Early Career Lessons That Shaped Leaders' Paths

Think back to your first “real” job. 

The lessons you learned—whether from a supportive mentor, a challenging project, or a memorable mistake—likely still resonate with you today. 

These early experiences are more than just memories; they are the foundational principles that shape who we become as professionals.

With this in mind, we asked leaders from the HR Spotlight community:

What’s a lesson that you learned at a job early in your career that you still apply today?

From simple words of advice to career-altering learnings, their stories reveal the profound and lasting impact of our foundational years and offer invaluable guidance for anyone navigating their own journey.

Read on!

Robyn Davis Sekula
Vice President of Communications and Marketing, Presbyterian Foundation

Robyn Davis Sekula

In my mid-20s, I worked for someone who was fond of minimalistic notes, expecting us to do whatever it was he wanted that day by just a word or two in the note.

In one case, I didn’t know what he wanted, or when, so I ignored it because I didn’t want to look dumb and ask.

When it wasn’t complete by day’s end, he was not happy.

Once that note hit my desk, it was up to me to ask questions to ensure I knew what he wanted.

It’s not your fault the instructions weren’t clear – but it is your responsibility to make up for lack of clarity by asking clarifying questions.

Understanding the assignment is crucial.

Danny Ray
Founder, PinnacleQuote

Danny Ray

Early in my career, I worked in sales for a small insurance agency, and one lesson has stuck with me ever since, listening is more powerful than talking.

Above all, I learned that understanding a client’s needs is the foundation of building trust.

For example, instead of rushing to pitch a product, I focused on asking thoughtful questions and truly hearing the answers. In fact, this approach helped me not only close more sales but also build lasting relationships.

Furthermore, it taught me the value of patience and empathy, two traits that are essential in leadership.

Overall, this simple yet profound lesson has shaped how I connect with clients, lead teams, and grow my business today.

Listening isn’t just a skill; it’s a superpower.

Shane Skwarek
Founder & Chief Technologist, S-FX.com Small Business Solutions

Shane Skwarek

When I started my first job at the age of 14, my boss would often preach that “you never gyp a good worker.” 

He’d often go out of his way to make sure that everyone was appreciated for their hard work, even if it was only giving you an extra $5.  

At the time, it didn’t mean much – until I’d later start employing people myself. 

When someone works hard for you, reward them in any way they can. Whether it’s monetarily, a gift card, or just a note of appreciation – people respond well when they know they’re valued.  

More importantly, it’s a better investment to reward those who already work hard for you than it is to try and find someone to replace them.

Allison Jackson
Communication & Wellness Strategist, FractionX

Allison Jackson

My first job out of college was as a copywriter for a major insurance company. There were about 10 of us on the team.

As you might imagine, writing, proofreading, and editing was essential for the role.

We quickly learned the “Six Eyes Rule.” That meant in addition to your eyes, two other people needed to review your work for errors.

This rule has stuck with me for two decades — and has prevented many mistakes!

Genevieve Piturro
Founder, Genevieve Piturro

Genevieve Piturro

Early in my career in the TV syndication business in NYC, I worked for a very creative and bold man. 

I was reserved and hard-working and never wanted to make a mistake. 

We had an opportunity to market new TV movies, and I watched as his imagination fueled him with new promotional ideas. He wasn’t afraid to take a chance and I think he saw something in me that needed to wake up to that same attitude. 

He took me aside one day and said, “Genevieve, I know you’re holding back – GO FOR IT!”  

His words propelled me to dig deep for what I now call MOXIE. I picked up the phone and made a big ask. To my shock, the answer from the other side of the phone was, “I like it, YES let’s do it!” 

And I have been best friends with my Moxie ever since!

Simon Royston
Founder and Managing Director, The Recruitment Lab

Simon Royston

My first Managing Director preached to me that one should ignore the client! 

He argued that you should ignore the client, deliver on what was agreed and save a lot of procrastination and energy.  

In today’s world in certain circumstances, it really can help.  

Too often clients can be closely examining your methodologies and question your every move. Ultimately, the client came to you to solve a problem and that above all else is what matters. 

That is not to say the client journey is unimportant.  

One should always communicate and report progress or maybe seek further information in specific cases. Just be mindful that time is money, and you are paid to deliver on time and within budget.

Lisamarie Monaco
Co-Owner, InsuranceForBurial.com

Lisamarie Monaco

A lesson that I learned long ago and that is valuable to me still to this day is to approach a job by learning it from the back end forward. 

I learned it is important to understand the behind the scenes processes, systems and workflows first so you gain a deeper understanding of how everything works and functions. 

This allows you to have the tools you need independently in that role. And helps avoid relying on others to fill in any gaps or to even fix something when there is a bump in the road. 

This lesson has served me well in my career and in everything I have done since implementing this in my life!

Michael Puck
Founder, Global Dog Art Gallery

Michael Puck

A lesson that I learned early in my career is to challenge everything.  

After eight years in the German military, I moved into HR and transferred to the US. I had no experience with HR in the US, and when I learned how different the US healthcare system works from what I was accustomed to, I designed a model that would give employers more control over healthcare costs. 

In the beginning, I was told many times that this model could never work. Even the Chief Medical Officer of our health insurance carrier told me not to waste my energy. 

After considerable initial resistance (I even got laughed out of the boardroom by my peers on the leadership team), I got the green light to implement the program. 

Right from the start the program engaged over 92% of the employees and even 70% of the spouses. As a result, the company did not receive any healthcare premium increases for five consecutive years, and we reduced the average number of health risks from 2.8 to 1.5. The underwriter calculated our net cost avoidance at over $7 million. 

All of this only happened because I challenged the status quo. The skill of asking probing questions and challenging everything that doesn’t feel right or looks outdated has become the hallmark of my HR career. 

Today, I am working for an HCM think tank where we take on the most pressing challenges today’s business and HR, in particular, face. 

My professional focus these days is based on this early lesson in my career: Challenge Everything.

Karen Southall Watts
Author, The Solo Working Day

Karen Southall Watts

Early in my career I learned to prepare for inappropriate interview questions, because they will happen. 

As a young woman I was often asked about pregnancy, potential pregnancy, and my children. Shockingly, these questions usually came from female interviewers and were often prefaced with remarks like, “I know I’m not supposed to ask this” or “Just between us women” as ways for interviewers to excuse their inappropriate and illegal behavior. 

When the job market is tough, these types of questions increase, because employers know candidates are desperate and can be tricked or coerced into answering. 

Later in my career as an educator and coach I advised clients and students to prepare for questions to pop up on age, religion, family issues, or national origin. 

It’s important for candidates to know in advance how they will handle this—confront, deflect, or answer—and what these kinds of questions mean about an employer.

Craig Attiwill
Founder & CEO, Peloton Technologies

Craig Attiwill

A lesson I learned early in my career can be summed up in one quote: “Insanity is repeating the same mistakes and expecting different results.” 

It’s not a quote from anyone in particular (I don’t think!), let alone anyone famous for their quotes. It’s just a life lesson from the collective.  

It’s not just about learning quickly from your mistakes and moving on. It’s remembering that others have likely made these mistakes, and the result is not going to be any different for you. 

One way to avoid the expensive learning process is to spend more time reading, researching and learning from peers  – understand how others in your role or in your industry have tripped along the way, and then choose another path.

The HR Spotlight team thanks these industry leaders for offering their expertise and experience and sharing these 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.

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