Menu

FutureOfWork

Bridging Technology Gaps in Modern Talent Acquisition

by

Bridging Technology Gaps in Modern Talent Acquisition

By Michael Ang, CEO and Founder of JobElephant

In today’s talent acquisition landscape, HR professionals face a significant challenge that often gets overlooked: the fragmentation of recruitment technology. Job boards operate independently from applicant tracking systems (ATS), creating inefficiencies that cost organizations time, money, and top candidates. The critical need for integration between these platforms has never been more apparent as HR teams struggle to maintain data integrity across disconnected systems.

The current recruitment technology setup may feel like a bunch of islands rather than a connected continent. Job boards and ATS platforms operate in silos, each with its own interfaces, data structures, and communication protocols. This isolation is not accidental. Competing talent acquisition vendors often create barriers to protect their market share, even when it hurts the end users. The persistence of questions like “How did you hear about this job?” reveals this disconnect. Such questions became standard in the print advertising era but remain necessary today only because modern systems still can’t reliably track where candidates come from, a problem that proper integration would solve.

The real costs of these disconnected systems go beyond just being inconvenient. HR teams waste countless hours manually transferring data between platforms, increasing the likelihood of errors. Organizations lose money on ineffective advertising placements without comprehensive performance data. Most critically, qualified candidates fall through the cracks when their information fails to transfer properly between systems.

The Fragmentation Problem in Talent Acquisition

Data loss between recruitment systems creates ripple effects throughout the hiring process. When candidate information does not seamlessly flow between platforms, recruiters miss opportunities to engage with promising applicants. This fragmentation leads to inconsistent candidate experiences, as applicants encounter different interfaces and requirements across various touchpoints in the application journey.

Tracking candidates across multiple platforms becomes a logistical nightmare for HR teams. Without a unified view, recruiters struggle to determine where candidates are in the hiring process, leading to delays and miscommunications. The fragmentation also severely impacts reporting and analytics capabilities, making it nearly impossible to gain comprehensive insights into recruitment performance. With job seeker-provided information and without a standardized way to measure recruitment advertising success across all platforms, the Key Performance Indicators (KPIs) become meaningless. Organizations end up making critical hiring decisions based on incomplete or unreliable data.

Communication Breakdowns in the Hiring Process

Neutral intermediaries add significant value to the talent acquisition ecosystem by bridging communication gaps between competing vendors. Advertising agencies with specialized technology can serve as translators between job boards and ATS platforms, ensuring data flows smoothly throughout the recruitment process.

While technology plays a crucial role in bridging recruitment gaps, the human element remains essential. Expertise in navigating complex technology ecosystems helps organizations make the most of their recruitment tools. Strategic partnerships with third-party specialists provide access to this knowledge without requiring internal teams to become technology experts.

This independence allows for objective comparisons between different platforms and strategies, helping HR teams make informed decisions. Having an unbiased partner in recruitment technology ensures that recommendations are based on performance rather than platform preferences.

Customization through robust Application Programming Interface (API) capabilities allows organizations to tailor their recruitment technology to their specific needs. By leveraging data resources across platforms, these partnerships enable more informed decision-making and strategy development. Ultimately, third-party partners improve hiring outcomes by combining technological solutions with human insight and industry knowledge.

The Value of Strategic Partnerships and Independent Third Parties

Data protection has become a critical concern in recruitment processes, with candidates and organizations alike demanding greater security measures. Fragmented systems create security vulnerabilities as sensitive information passes through multiple platforms with varying levels of protection. Each transfer point represents a potential risk for data breaches or unauthorized access. Many HR professionals now question whether vendors might share their candidates with competitors, either directly or through third-party AI firms, adding another layer of concern to an already complex security landscape.

Building trust through transparent data handling practices requires a cohesive approach to information security. Organizations need consistent protocols that protect data regardless of which platforms are involved in the process. This unified approach to security helps build candidate trust and protects sensitive organizational information.

Information Security and Trust in Talent Acquisition

Integrated recruitment systems connect organizations to worldwide job distribution networks, expanding their reach beyond local or national boundaries. This global approach allows employers to tap into diverse talent pools and find specialized skills that may not be available in their immediate area. A growing cottage industry of middleware Human Resources Information System (HRIS) connectors has emerged to bridge these gaps, though these services come with a cost. Some providers offer more hands-on support than others, with many now bundling connections to background checkers, schedulers, payroll systems and other services to reduce the number of vendors organizations must manage.

Through a single interface, organizations can access niche platforms that cater to specific industries or skill sets. Performance tracking across all connected systems provides insights into which channels are most effective for different types of positions, enabling more strategic allocation of recruitment resources. Real-time monitoring of ad performance, clicks, and conversions helps organizations adjust their strategies quickly to maximize results.

Global Reach Through Integrated Systems

The future of talent acquisition depends on interconnectivity between previously isolated systems. Organizations that successfully bridge technology gaps gain significant advantages in efficiency, candidate quality, and hiring speed. As recruitment technology continues to evolve, the focus must shift from building individual platforms to creating ecosystems where different tools work together seamlessly.

The most successful recruitment strategies will leverage both technological innovation and human expertise. Data-driven insights from integrated systems empower recruiters to make better decisions, while strategic partnerships provide the guidance needed to maximize the value of these technological investments. Together, these elements create a recruitment ecosystem that is greater than the sum of its parts.

The Future of Connected Recruitment

About the Author

Michael Ang, CEO and Founder of JobElephant leverages over two decades of recruitment advertising expertise. Starting as a graphic designer in 1994, he established JobElephant in 2000, propelling it from his garage to national recognition. Michael’s visionary leadership emphasizes outstanding service, personally managing numerous client accounts. His focus on streamlining recruitment advertising processes has solidified JobElephant’s reputation for reliability and success. Michael’s insights and commitment to excellence distinguish JobElephant as an industry leader.

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

Discover the latest HR Tips and trends with our weekly newsletters!

What HR and Leaders Look for to Ensure Remote Teams Thrive

by

What HR and Leaders Look for to Ensure Remote Teams Thrive

By Stanley Anto, Chief Editor, HRSpotlight.com

The past few years have felt like one huge, involuntary experiment in remote work. The initial shock has faded, but here’s the question many of us are still figuring out: How do we, as leaders, truly know if our teams are not just getting by, but actually thriving?

For a long time, the instinct was to keep an eye on every move—video calls, chat activity, login hours. The thinking was simple: if you can’t see your team, are they working at all?

But as we’ve all gained experience, a new truth has emerged: the most effective remote teams aren’t built on surveillance. They’re built on trust, clear communication, and focusing on results, not hours logged. It isn’t about dashboards; it’s about a leadership mindset that believes professionals will do their work well.

So what does this new style of leadership actually look like? I spoke with leaders who have mastered it. Their key insight: focus on outcomes, not on activity, and watch for real signals of engagement rather than digital presence.

The old model was all about clock-watching. Were people logged in? Did they hit their eight hours? But anyone who’s worked remotely knows that hours don’t equal productivity. You could be “online” for eight hours but accomplish very little.

Top remote managers have moved on. They judge success by the final product, not by when or how it was made.

Edward Hones, an employment lawyer and founder of Hones Law PLLC, says it best: “We don’t rely on invasive monitoring to measure remote team effectiveness. We focus on outcome-based KPIs and the timely delivery of high-quality work.”

In Edward’s world, it’s the quality and timeliness of deliverables, whether drafting legal memos or managing cases, that count. This breaks through the noise of digital footprints and focuses on what actually moves the business forward.

But it’s not just about outputs. Edward also pointed out a vital human element: engagement. “A big part of success is responsiveness. Team members who quickly reply to internal questions or client needs tend to be more engaged. They raise red flags early, ask good questions, and take meaningful part in meetings.”

Engaged employees are proactive. They don’t wait to be told what to do. Their communication becomes a clear sign that they’re not just working, but truly invested.

From Hours Logged to Outcomes Delivered

Great teams share a common mission. When work is spread out, informal watercooler chats fade away. Some leaders find that a well-chosen business metric becomes their team’s rallying point.

Gunnar Blakeway-Walen, Marketing Manager at The Heron, Edgewater, explains: “Our conversion rate from marketing leads to signed leases became our key remote team KPI. I stopped tracking hours and started obsessing over this because it demanded perfect coordination between marketing, leasing, and operations.”

When conversion dips, the whole team feels it. They rally to find the issue—whether lead quality is down or follow-ups are slow.

That kind of shared accountability removes the need for micromanagement. The metric drives productivity and collaboration naturally.

Shared, Measurable Goals Unite Teams

Beyond KPIs, consistency matters. Gary Harutyunyan, CEO of SleepyBaby, who manages 28 remote employees across states, discovered that “consistent delivery timelines are the most reliable remote team indicator.”

If a team meets deadlines reliably, you know they’re productive. This isn’t about being wired to the clock 24/7. It’s about honoring commitments—and that means both quality and timeliness.

For teams that do more than just meet expectations, Dhawal Shah, Co-Founder of 2Stallions Digital Marketing, looks for continuous improvement.

He shared, “I track how fast work gets done and watch whether my team improves. Completing tasks quicker while maintaining or improving quality shows they’re gaining mastery and efficiency.”

This kind of progress tracking isn’t surveillance. It celebrates growth and pushes mastery, which fuels long-term success.

Productivity Shows in Consistency and Growth

If you want a roadmap for managing remote teams in 2025, here it is:

– Build a culture of trust. Treat your employees like professionals who can manage their time and workload.

– Set clear, outcome-driven goals and metrics that everyone understands and supports. This could be a shared business KPI or a simple weekly deliverable checklist.

– Keep an eye out for genuine engagement—how quickly your team responds, how proactive they are, and whether you see steady improvement.

By shifting away from surveillance and towards these principles, your remote teams will be more productive, innovative, and resilient.

In our evolving work world, leadership isn’t about watching every keystroke. It’s about empowering people. When you focus on trust, shared purpose, and continuous growth, you build teams that don’t just survive remotely—they thrive.

What Should Leaders Focus on Today?

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

Discover the latest HR Tips and trends with our weekly newsletters!

US Companies Fast-Track Green Card Sponsorships to Retain Global Talent

by

US Companies Fast-Track Green Card Sponsorships to Retain Global Talent

US companies are moving quickly to accelerate Green Card sponsorships for foreign professionals, as policy hurdles and tightening immigration laws reshape the global talent landscape. This shift is a strategic response to the pressing need to attract and retain top-tier talent from around the world amid heightened compliance checks, audits, and complex visa protocols in 2025.

According to a recent global corporate immigration trends survey, nearly 70% of US employers have started sponsorship procedures within three months of hiring a foreign employee—an enormous swing from previous norms, where it was common to wait a year or longer. Now, fewer than 3% of companies delay sponsorship beyond 12 months, and only about 4% refuse sponsorship entirely, down from 11% last year.

For companies, especially in sectors like technology, healthcare, and finance, offering early Green Card sponsorship isn’t just a benefit—it’s become essential for recruitment and retention in a fiercely competitive market. “Across many industries, companies are placing greater emphasis on permanent residence sponsorship as a strategic tool for recruitment and retention,” said Sherry Neal, Partner at Corporate Immigration Partners. “Timely progression to the I-140 stage is often a key factor in whether a candidate accepts an offer or stays with an employer,” she added.

The New Urgency in Green Card Sponsorship

This acceleration comes against a backdrop of stricter immigration enforcement and protectionist pressures under the current US administration. The government has implemented narrower definitions of specialty occupations, increased salary requirements, and greater scrutiny of visa petitions for programs like H-1B. These measures lengthen processing times, raise denial rates, and inject additional complexity into workforce planning for global companies.

Meanwhile, companies are wary of increased oversight of cost-recovery practices. While some employers tie sponsorship to “claw-back” clauses requiring cost repayment if the employee leaves early, government regulations restrict recouping certain expenses, such as attorney fees and certification process costs. State laws are fragmented, further complicating compliance.

Policy Headwinds and Compliance Pressures

Despite the surge in sponsorships, long-standing backlogs continue to impede smooth processing, particularly for Indian and Chinese professionals in EB-2 and EB-3 categories. Recent visa bulletins show these categories remain “retrogressed,” with substantial wait times for permanent residency—a bottleneck that US firms are desperately trying to outmaneuver by starting the sponsorship process as early as possible.

In response to persistent bottlenecks, some companies are educating employees on alternate pathways—like the EB-1 for extraordinary ability or EB-5 investment options—but these remain limited and highly competitive.

Green Card Backlogs: A Persistent Challenge

Early Green Card sponsorship is now seen as a “decisive advantage” in talent markets, where skilled workers have options globally. With many nations tightening immigration (including Canada, the UK, and parts of Europe), the US corporate sector cannot afford to delay. Surveys show employees are less likely to accept US offers or remain with a firm if pathways to permanent residence are uncertain.

To further support retention, more than half of the firms surveyed now cover all costs of the Green Card sponsorship, though some attach conditions. The percentage of companies that provide full financial backing with no strings attached has also sharply increased in the last twelve months.

Why the Rush? Retention, Morale, and Market Pressure

America’s urgent push for faster Green Card sponsorship reflects a broader shift in the global talent competition. As the US adapts to political and policy headwinds, corporate immigration teams are reshaping benefits packages and investing heavily in compliant, proactive immigration programs. The knock-on effect is clearer career certainty for top global talent, and a better shot for US companies to stay innovative amid worldwide labor shortages.

Yet, until Congress implements major reforms or visa backlogs shrink, both employers and employees will need to remain nimble, continually adapting strategies in an unpredictable policy climate. For now, the acceleration in Green Card sponsorship sends a clear message: companies determined to lead on the world stage are doing everything possible to win—and keep—the best talent, no matter where they come from.

The Macro View: Global Implications and Outlook

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

Discover the latest HR Tips and trends with our weekly newsletters!

Remote Team Effectiveness: How to Measure Performance Without Micromanaging

by

Remote Team Effectiveness: How to Measure Performance Without Micromanaging

In the evolving landscape of modern work, remote and hybrid models have fundamentally reshaped traditional notions of productivity and oversight.

The era of clocking in and out, or measuring “seat time,” is rapidly giving way to a more sophisticated understanding of performance, particularly for distributed teams.

For business leaders and HR professionals, a critical question emerges:

Beyond mere activity tracking or hours spent online, what are the most effective Key Performance Indicators (KPIs) that genuinely reveal a remote team’s productivity and success?

This HR Spotlight article compiles invaluable insights from those at the forefront of managing distributed workforces, revealing the metrics they prioritize to ensure accountability, foster autonomy, and ultimately drive tangible business results without resorting to invasive surveillance.

Read on!

Eugene Lebedev
Managing Director, Vidi Corp LTD

Eugene Lebedeve

One KPI that I look at is the number of sprint points completed by the team per week.

Every week we add tasks to our Clickup and assign a team member. We then assign a number of sprint points to each task based on how big the task is. The tasks that could be done within a couple of hours take 1 sprint point, tasks that can be done within a day are 3 points, tasks that take 2 days are 5 points, etc. Assigning sprint points helps to measure how big the tasks are.

We then measure how many sprint points were achieved by each team member. If we see that a number of sprint points dropped for someone in our team, we have a conversation and try to increase this number to where it was.

Raphael Larouche
Founder & SEO Specialist, SEO Montreal

Raphael Larouche

I often work with people in Bangladesh and other remote locations, and honestly, the best KPI for me is just seeing if projects get done on time and meet the quality I expect. If deadlines are consistently met and the work looks good, that’s the main signal I need.

I don’t track every minute or micromanage. If deliverables keep showing up and clients are happy, I know my remote team is working effectively.

Leigh Matthews
Founder & Clinical Director, Therapy in Barcelona

Leigh Matthews

Client outcome consistency is my go-to KPI after leading a 13-therapist remote team for 6 years. When therapists are truly engaged, their clients show measurable progress—regardless of where the session happens.

In 2024, we tracked 9,291 therapy sessions across our international team. The therapists who maintained consistent client improvement scores (measured through standardized assessments like PHQ-9 and GAD-7) were always the ones fully present and prepared. One therapist in Mexico consistently achieved 85% client improvement rates while working completely remotely—her dedication showed in results, not hours logged.

I’ve learned that micromanaging location or screen time kills the collaborative culture that makes remote therapy effective. When our Polish therapist moved time zones mid-year, her client outcomes stayed strong because she remained committed to the work itself.

The beauty of outcome-based measurement is it’s binary—either clients are getting better or they’re not. Our weekly team supervision focuses on these results, and it immediately reveals who’s thriving remotely versus who might need additional support.

Gunnar Blakeway-Walen
Marketing Manager, The Heron – Edgewater

Gunnar Blakeway-Walen

Conversion velocity is my go-to KPI for remote team effectiveness. In my role managing marketing across Chicago, San Diego, Minneapolis, and Vancouver, I track how quickly our distributed team moves prospects from initial contact to signed lease.

When we implemented UTM tracking across all channels, our remote team’s coordination improved dramatically—we saw a 25% increase in qualified leads and could immediately identify which team members were contributing most effectively to the funnel. The data showed that our Minneapolis team was converting prospects 40% faster than other markets, so we replicated their follow-up processes company-wide.

The beauty of conversion velocity is that it captures everything: communication speed, process efficiency, and collaborative problem-solving. When our Chicago team’s conversion rate dropped, we found they needed better CRM integration rather than more oversight. We fixed the workflow, and their numbers bounced back within two weeks.

This metric tells you if your remote team is actually working together effectively, not just staying busy. It’s outcome-focused and eliminates the need for invasive monitoring.

Jamilyn Trainor
Owner & SPM, Muller Expo

Jamilyn Trainor

For me, building a high-performance team has been about trusting them. As far as remote work is considered, what matters for me is consistent output over time. I’m not talking about hours logged in. I am speaking about the consistent reliability of meeting deadlines, shipping clean work, and not requiring hand-holding.

When a team member is routinely delivering good quality work without the chaos of a mad dash to the finish line, you can be assured that the person’s not just ‘present’, but they are actually ‘engaged’ in the task.

Bonus, they will have also likely been regularly communicating if they are engaged, asking insightful questions, and handling little problems before they become big ones. You do not need to be looking over their shoulder and spying on their screens if your people are taking ownership of the outcomes.

If you observe quality dropping, timing stretching, or they go quiet, that is your signal to check in,not so you may micro-manage, but so you may support them. Transparency and results, combined with trust, will beat surveillance every time.

Destiny Baker
Chief Operations Officer, CadenceSEO

Destiny Baker

Slack responsiveness is the primary way we monitor our fully remote team of 30.

Our team thrives on autonomy, so we’ve created transparent processes and guidelines about Cadence’s expectations during working hours. For example, we have a clear policy that an “away” message is set when an employee is away from their computer for more than a few minutes.

Additionally, we have several team channels where specific questions can be asked. It’s clear our team is active because they quickly respond.

Finally, we meet with team members often to discuss bandwidth, ensure they are working efficiently, and have the support they need.

Davide Pirola
CTO, Trep Digitalx

Davide Pirola

One reliable, non-invasive signal of remote team effectiveness is cycle time consistency.

At Trep DigitalX, we track how long it takes for a task—once assigned and clarified—to reach completion. This KPI reflects not just speed, but clarity, collaboration, and ownership.

If cycle times stay predictable across sprints or weeks, we know communication is flowing, blockers are being resolved, and priorities are clear—without the need to monitor every move. It’s outcome-focused, not activity-based, and helps build a culture of trust where performance is visible through results, not surveillance.

Vlad Vynohradov
Fleet Management Solutions Specialist, Logbook Solution LLC

Vlad Vynohradov

Data-driven task completion rates are my go-to KPI for remote team performance.

In our fleet management operations, I track project milestone completion against deadlines rather than hours logged. When our analytics team consistently hit 95% of their weekly data processing targets, I knew they were performing effectively regardless of when they worked.

The beauty of this approach lies in outcome measurement. During our fuel management software rollout, I monitored feature deployment rates and client onboarding completions rather than screen time. Teams that delivered 8-10 completed implementations per week were clearly engaged and productive.

I supplement this with voluntary participation metrics in team communications and knowledge sharing. Our most effective remote developers actively contributed to our technical discussions and documentation updates. High performers naturally engage with the work community without being forced.

Kevin Wasonga
Outreach & Growth Lead, PaystubHero

Kevin Wasonga

At PaystubHero, we’re fully remote and honestly, trying to monitor people all day just never felt right.

What has worked best for us is that each person picks 2–3 things they’ll own for the week, and we all check in on Friday to see what got done. No one’s counting hours or staring at dashboards.

We care if the important task is moving.

If someone’s stuck, we spot it early. If things are rolling, we stay out of the way. That one habit has told us more about performance than any tracker ever could.

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.

Recent Posts

New York Becomes First State to Mandate AI and Automation Disclosure in Layoffs

by

HR NEWS

New York Becomes First State to Mandate AI and Automation Disclosure in Layoffs

June 17, 2025 — In a pioneering move, New York has become the first U.S. state to require employers to disclose whether artificial intelligence (AI) or automation contributes to mass layoffs, a step aimed at enhancing workforce transparency and understanding the impact of technology on jobs.

The new requirement, which took effect in March 2025, is part of an amendment to the state’s Worker Adjustment and Retraining Notification (WARN) Act, announced by Governor Kathy Hochul during her January 2025 State of the State address.

New York Becomes First State to Mandate AI and Automation Disclosure in Layoffs

The New Rule: A Checkbox for Transparency

Under the updated NY WARN Act, employers with 50 or more employees must file a notice at least 90 days before a mass layoff or plant closure affecting at least 25 workers or one-third of the workforce at a single site. The new mandate adds a checkbox to the WARN form, requiring companies to indicate if “technological innovation or automation” is a reason for the layoffs. If checked, employers must specify the technology involved, such as AI or robotics.

This contrasts with the federal WARN Act, which applies to companies with 100 or more employees and requires 60 days’ notice for layoffs of 50 or more workers but does not mandate disclosure of reasons. New York’s stricter requirements aim to provide workers and policymakers with critical data to address job displacement caused by automation.

Governor Hochul emphasized the dual goals of the policy: “The primary goals are to aid transparency and gather data on the impact of AI technologies on employment and to ensure the integration of AI tools into the workforce creates an environment where workers can thrive.” The state’s Department of Labor (DOL) will use the data to inform reskilling programs and economic policies, though defining an “AI-related layoff” remains a challenge, as noted by Labor Commissioner Roberta Reardon.

Why It Matters: AI’s Growing Impact on Jobs

The rise of AI has sparked widespread concern about job displacement across industries. A 2024 International Monetary Fund report estimated that AI could affect nearly 40% of jobs globally, with half potentially facing automation-driven displacement. In the U.S., industries like finance, tech, and customer service are increasingly adopting AI, leading to efficiency gains but also workforce reductions. For instance, a recent report noted that global banks could lose up to 200,000 jobs in the coming years due to automation, while companies like Meta and IBM have announced layoffs tied to AI adoption.

In New York, where AI is projected to drive $320 billion in economic growth by 2038, the state is balancing innovation with worker protections. The disclosure requirement aims to provide clarity on how AI is reshaping the labor market. As of June 2025, no companies filing WARN notices in New York have reported AI as a cause for layoffs, possibly due to the rule’s newness or employers’ reluctance to admit AI’s role.

Experts see this as a critical step. Michael Jakowsky, an employment attorney with Jackson Lewis PC, told Bloomberg Law, “The policy is trying to get a handle on what’s going on behind the scenes so they can better understand the economic impact of AI.” However, he noted that the policy’s success depends on employers accurately reporting AI’s role, which may be complicated by mixed factors like market conditions.

Implications for Employers and Workers

For employers, the mandate introduces new compliance obligations. Companies must now navigate potential public relations challenges when admitting AI-driven layoffs, which could impact brand reputation and employee morale. However, transparency could foster trust with workers and the public.

Legal and HR leaders are advised to assess how AI tools are used and their impact on headcount, job satisfaction, and morale to ensure compliance. Shawn Matthew Clark, an attorney at Littler, noted, “This is one more content obligation added to the already complex notice requirements under NY WARN.”

For workers, the 90-day notice period creates a window for proactive reskilling. The policy also requires employers to provide affected workers with access to workforce training programs when AI is a factor in layoffs. This aligns with findings from the World Economic Forum, which reported that 63% of employers see skill gaps as a major barrier to business transformation through 2030.

Broader Context: AI Regulation in the Workplace

New York’s move is part of a growing trend to regulate AI in employment. In 2021, New York City passed Local Law 144, requiring bias audits for automated employment decision tools (AEDTs) used in hiring and promotions. Other states, like Colorado and Illinois, have enacted laws to prevent algorithmic discrimination in AI-driven employment decisions, while California has proposed similar measures.

At the federal level, the Equal Employment Opportunity Commission (EEOC) issued guidance in 2023 on AI’s potential for adverse impact in workplace decisions, though recent rollbacks under the Trump administration have shifted focus to state-level regulations. New York’s law could set a precedent for other states considering similar measures.

Challenges and Criticisms

The policy has potential shortcomings. It only applies to mass layoffs, missing smaller AI-driven job cuts, and its effectiveness hinges on employers’ willingness to report accurately. 

Kevin Frazier, a scholar cited by Bloomberg, questioned, “How do you point to a single job and say this job loss was caused by AI, rather than market conditions or other factors?” 

Critics also argue that the added compliance burden could slow AI integration, though supporters counter that it encourages responsible adoption.

Looking Ahead

New York’s AI disclosure mandate marks a bold step toward addressing the human cost of automation. 

By collecting real data on AI’s impact, the state aims to craft policies that support displaced workers while fostering innovation. 

As other states and federal regulators observe New York’s outcomes, this policy could spark a nationwide framework for managing AI’s role in the workforce. 

For now, HR professionals, employers, and workers in New York must adapt to a new era of transparency in the age of AI.

Written by Grok with inputs from the HR Spotlight team and information sourced from Bloomberg Law, New York State Government, New York State Department of Labor (DOL), International Monetary Fund (IMF), World Economic Forum (WEF), Equal Employment Opportunity Commission (EEOC), New York City Local Law 144, General Web Sources.

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

Resistance to Readiness: How Leaders Can Upskill Teams in AI and Analytics

by

Resistance to Readiness: How Leaders Can Upskill Teams in AI and Analytics

The rise of AI and analytics is transforming industries, pushing organizations to urgently upskill their teams to stay competitive in a data-centric world.

Yet, preparing employees for this shift comes with significant challenges.

From addressing resistance to new technologies to managing limited budgets and diverse skill levels, HR and business leaders face a multifaceted journey to drive effective upskilling.

The HR Spotlight team posed a critical question to leading HR and business experts:
What practical challenges should leaders anticipate when helping their workforce advance in AI and analytics skills?

Their responses highlight key barriers—such as cultivating a culture of continuous learning, securing resources for robust training, and designing inclusive programs that meet varied employee needs—while providing practical solutions to navigate them.

As AI expertise becomes essential for organizational success, these leaders stress strategic foresight, transparent communication, and tailored approaches to empower teams.

Discover their insights below to learn how to overcome these obstacles and build a workforce ready for the demands of 2025.

Read on!

Chris Hunter
Director of Customer Relations, ServiceTitan

Personalized Development Paths Ease AI Transition Fears

Leaders have to take into consideration different levels of competence across teams, which means personalized development paths are required.

In addition, obstacles exist when people do not want to change or fear that machines will take jobs away from them. Thus, access to top-level training materials is essential, as is the ability to develop a culture of consistent improvement.

Finally, the integration of new AI software should not disrupt old workflows, which means stressed leaders have to take part in detailed planning and communication to ease employees into the transition.

Chris Brewer
Managing Director, Best Retreats

Lead by Example: Curiosity Drives AI Adoption

Expect resistance and uneven learning curves. Not everyone will be tech-savvy or excited.

Budget for ongoing training, not just one-off sessions.

Be clear about the “why” behind the upskilling so it feels relevant, not forced.

Create space for experimentation without fear of failure.

Most importantly, lead by example because curiosity is contagious.

Joel Miller
President, Miller Pest & Termite

Tailor AI Training to Roles for Faster Adoption

Leaders should prepare for resistance to change and varying skill levels across their workforce when introducing AI and analytics training.

Many employees may feel intimidated or unsure about how these tools fit into their daily work. It’s essential to address these concerns through clear communication and tailored training.

Another challenge is integrating new AI tools without disrupting current workflows.

Leaders need to plan for time and resources to support learning while maintaining productivity. Practical training must focus on real-world applications relevant to employees’ roles to build confidence and drive adoption.

Amir Husen
Content Writer, SEO Specialist & Associate, ICS Legal

Map Individual Gaps Before Building AI Skills

When upskilling teams on AI and analytics, leaders must prepare for several hurdles.

Uneven skill baselines: A one-size-fits-all bootcamp won’t work—map individual strengths and gaps, then offer tiered learning paths.

Tool proliferation: Bombarding learners with every new library or platform breeds confusion. Start with one core stack (e.g., Python + pandas + a BI tool), then expand.

Data quality & access: Without clean, well-governed datasets and clear ownership, analytics projects stall. Audit your pipelines before training begins.

Time constraints: Carve out protected “learning sprints” or micro-learning slots—don’t expect people to upskill on top of full workloads.

Change fatigue: Promote quick wins, celebrate early successes, and keep leadership visibly invested to maintain momentum.

Anticipating these challenges turns training initiatives from checkbox exercises into lasting capability builders.

Louis Costello, MD
Founding Physician, Dynatech Lifestyle Mind Body Care

Address Biology First for Effective AI Training

The dominant narrative frames AI literacy as a content issue, solved with more courses and longer modules.

That misses the actual bottleneck: cognitive fatigue and information rejection.

Most employees can handle 60 minutes of high-intensity abstract learning before the prefrontal cortex disengages and starts defaulting to rote behavior. Stretch that to two hours with no breaks and retention drops below 40%. Instead of expanding access to AI resources, more companies should be reducing training blocks to 45-minute intervals, followed by physical reset tasks that spike dopamine and improve memory encoding.

Without structured rhythm, upskilling becomes an intellectual treadmill.

Any AI training rollout that skips lifestyle recalibration will collapse under mental dropout.

Sleep compression reduces data absorption by 25% in 48 hours. Multitasking through Slack or email during training destroys analytical engagement. Movement, fuel timing, and environment temperature under 72degF all impact neuroplasticity.

These variables do not show up on a curriculum checklist, but they determine whether the content lands or bounces.

Every executive designing AI training must address biology first. Otherwise, the content is brilliant but the brain is unavailable.

Yoad Bet Yosef
Owner, Nature Sparkle

Gradual Learning Process Builds AI Confidence

When I started helping my team get better at AI and analytics, one of the biggest challenges was getting people comfortable with the new tools.

Many of our employees, especially those in customer service and marketing, were used to more traditional methods of working. Transitioning them to data-driven decisions required patience and clear, simple explanations of how AI could make their jobs easier.

One thing that worked was offering bite-sized training sessions that focused on real-world applications, like how AI could help with predicting customer preferences.

After implementing this approach, we saw a 22% increase in marketing team productivity, as they became more confident in using analytics to create personalized campaigns.

The key takeaway is: Make the learning process gradual, show the direct benefits to daily tasks, and celebrate small wins along the way. This way, your team can embrace the changes rather than resist them.

Marcus Denning
Principal & Senior Lawyer, MK Law

Align AI Tools with Daily Legal Practice

Often, lawyers struggle with using statistics because they perceive them as separate from the legal process. I helped a company explain the basics of data analytics by using daily examples and easy-to-understand legal terms for probabilities and trends. Presenting legal ideas as simple data allows people to learn them more quickly and retain them for a longer period.

I tried an AI tool for litigation and found it impressive at the start, but it was not fully aware of the details used in Victoria’s courts. They quickly rejected it because it did not fit with what they dealt with every day. It demonstrated to me that any software that does not align with the law or lawyers’ thought processes will not find use.

Furthermore, I have suggested that companies reconsider their expectations as people adapt to new ways of doing things. In some cases, junior lawyers did not use AI tools since their time was only recorded by billable hours. We changed the benchmarks for a brief period to encourage students to try different activities, and very soon students became excited about working together.

Mary Rizutti
HR Advisory & Compensation Resources group, EisnerAmper

Skill Analysis, Identifying Application, and More

While AI is changing so many aspects of business, with change comes challenges. There is clearly and expectedly a learning curve in this space. Companies are facing the challenge of a workforce that has had limited to no exposure and/or training in AI.

To work effectively with AI, a combination of technical and soft skills is needed. Technical skills such as knowledge of programming languages like Python, Java, R and C++ are commonly used in AI development. Individuals with backgrounds in computer science, data science, artificial intelligence, robotics, mathematics and statistics and software engineering may possess skills upon which they may rely to begin to understand large language and algorithm model development, as well as prompt engineering (the ability to optimize prompts for AI tools), as an example. may be acquired through self-study.

It’s important for companies to assess the current workforce to help them understand which employees might be suited to support an AI integration process.

One initiative many companies are undertaking is to perform a skills analysis on its workforce to identify those in-house who possess the capability to engage in identifying areas where AI may be appropriate.

Companies should also be prepared to deal with the challenge of identifying the application for AI within their companies. Some questions they should consider include: How far down the road should we go with AI? Are there controls in place to test and trust AI’s output? Do we have policies in place to monitor and provide guardrails for individual usage?

These challenges call upon leaders to not only possess, but to also instill and encourage keen problem-solving skills among their teams, to create ethical awareness around AI biases, privacy concerns and the responsible use of AI.

Fostering an environment of continuous learning, adaptability, curiosity, communication and collaboration needs to be a deliberate focus for leaders to enable their companies to travel the AI journey that is ahead.

Rebecca Trotsky
Chief People Officer, HR Acuity

Allow Employees to Shape AI Use

As HR leaders, one of our biggest priorities is helping our people leaders reskill and upskill their team members.

Many are excited by AI’s potential; yet, some challenges and concerns remain.

Fear of job displacement, lack of understanding, concerns about privacy and bias. Knowing these sensitivities, organizations that are adopting AI have to remember that trust and transparency are just as critical as training.

That means involving your employees from the start, allowing them to help shape how AI is used.

Making sure that they understand how AI is an enhancement not a replacement. And setting clear policies on how tools are used and what data is collected.

Danielle Pickens
Chief Program Officer, Urban Schools Human Capital Academy

Support Not a Substitute for Human Judgment

One key challenge for education leaders is preparing their workforce to effectively adopt AI and analytics. This goes beyond technical training as it requires a mindset shift toward data-informed decision making.

Educators are the heart of schools, yet many lack exposure to AI tools and face time constraints, making targeted professional development critical. Leaders must ensure equitable access to technology to prevent deepening disparities, while addressing ethical concerns like data privacy and bias.

AI should be seen as a support, not a substitute, for human judgment. It all starts with a strategic, empowered Human Resource team ready to lay the foundation for continuous learning.

By prioritizing upskilling and fostering an open culture, schools can begin to leverage AI to improve efficiency, accessibility, and ultimately, student outcomes.

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.

Recent Posts