“If HR can’t clearly connect the dots between engagement, retention and contribution to EBITDA, it’s not a business case,” says Wettemann, CEO of Valoir, an analyst firm experienced with the business impact of HR technology. “Its big feelings expressed in a bar chart.”

Where HR isn’t connecting the dots

Wettemann argues HR has largely brought this scrutiny on itself by failing to build a solid business case for investing in employee engagement. “Until HR does this,” Wettemann says, “CFOs will keep treating employee engagement as the soft stuff that gets cut first when belts need tightening.”

Most engagement data is self-reported through employee surveys, which isn’t credible with finance leaders, says Wettemann. She says CFOs are trained to be skeptical of metrics that are generated and interpreted by the same function.

Wettemann identifies another problem when HR tends to sell correlation as causation. “Survey scores don’t connect to business outcomes in any way that finance leaders find credible,” she says.

The fix isn’t another, better survey. “CFOs also understand variance analysis,” says Wettemann. “They track forecasted versus actual and explain the gaps. HR needs to do more post-mortems on what engagement initiatives cost and what they actually delivered, and where they moved the needle, to be credible with the CFO.”

Employee engagement as a business case

HR leaders are familiar with the engagement-as-business-case argument when analyzing turnover. Replacing an employee is expensive. Recruiting fees, manager time, onboarding and lost productivity add up quickly. The tally sheet fattens with specialized or senior roles where institutional knowledge resides with the departing employee.

“Engaged employees quit less, and the cost of replacing them is real and calculable,” she says. But she pushes HR leaders to see beyond recruiting cost savings, because the CFO is thinking about risks HR often isn’t putting a number on.

The risks of disengagement

The first is disengaged employees who haven’t left yet. Wettemann points out that these workers are going through the motions or calling in sick more often. “Companies are paying full price for partial output,” she says. That gap between what an engaged employee delivers and what a disengaged one delivers is real and can show up in output in roles that are measurable.

The second risk category is legal and insurance exposure. Engaged employees are less likely to escalate workplace conflicts into formal complaints, says Wettemann. In industries with physical risk, engaged employees have lower accident rates and fewer workers’ compensation claims. HR rarely connects engagement investment to liability exposure.

Wettemann says HR leaders don’t need to poll workers to get a taste of employee engagement. Instead, they should check the operational data the department already holds. “This is not about another survey,” Wettemann says. “It’s about thinking about business benefits beyond the walls of HR and connecting them to outcomes CFOs already care about.”

Rebecca Wettemann will speak at HR Tech Europe, April 22-23 in Amsterdam. Catch her sessions: Building the Business Case for HR Technology Investments and The Real ROI of Becoming a Skills-Based Organization. Register now.

The post When employee engagement gets cut, who’s to blame? appeared first on HR Executive.

See also: State AI regulation ban nixed. What it means for employers, tech firms

Recent state AI regulation activity

Several states—including California, Colorado, Illinois and Texas—have recently enacted legislation seeking to place parameters on AI-driven compensation and employment decisions. These include the following:

• The Colorado Artificial Intelligence Act (“CAIA”)—Effective Feb. 1 (with an enforcement date of June 30, 2026), the CAIA requires employers to exercise “reasonable care” when deploying AI systems in “high-risk” areas—including compensation, promotion, hiring and other employment decisions—to avoid “algorithmic discrimination.” To satisfy this duty of care, employers using AI systems to make employment decisions must implement risk-management policies and programs, conduct annual and other periodic impact assessments to identify potential bias, and notify employees if AI is used to make employment decisions.
• Illinois’ Amendments to the Illinois Human Rights Act (“IHRA”)—Effective as of Jan. 1, 2026, the IHRA amendment prohibits employers from using AI tools in connection with employment decisions, including those related to wage setting, unless they (1) notify employees when using AI for these purposes and (2) ensure the tools are not used in a manner that results in discrimination based on protected classes.
• The Texas Responsible Artificial Intelligence Governance Act (“TRAIGA”)—Effective as of Jan. 1, TRAIGA prohibits employers from using AI tools in employment decisions with the intent to discriminate against protected classes. Unlike other states, this law does not allow for liability based solely on disparate impact or unintentional discrimination.
• California Privacy Protection Agency (“CCPA”) Regulations—Effective Jan. 1, 2027, the updated CCPA regulations restrict employers’ use of automated decision-making technology in employment decisions, including compensation and other terms and conditions of employment. The regulations require employers to conduct risk assessments, provide employees with pre-use notices and allow employees to opt out of automated decision-making processes under certain circumstances.

Various state lawmakers have continued the trend in 2026, introducing bills containing similar restrictions. For example, California Senate Bill 947, also known as the “No Robo Bosses Act,” was introduced in February and could significantly restrict how employers use artificial intelligence to make employment decisions. If enacted, the bill would prohibit employers from using automated decision-making systems to process worker data as inputs or outputs to inform employee compensation—unless the employer can clearly demonstrate that any differences in compensation for substantially similar or comparable work assignments are based upon cost differentials in performing the task involved, or that the data was directly related to the tasks that the worker was hired to perform. Notably, this is a revised version of California Senate Bill 7, the original “No Robo Bosses Act,” which was vetoed by California Gov. Gavin Newsom on Oct. 13, 2025.

While the various proposed and enacted state laws are not all identical, they share common features. First, they generally define “automated decision systems” to include systems, software or processes—including those which rely on machine learning or AI techniques—that are used to assist or replace human decision-making. In the employment context, these definitions encompass automated human resources tools and software systems that use predefined rules to process data through algorithms and assist with the performance of human resources functions. These tools could include everything from basic rule-based systems to sophisticated technologies powered by generative AI.

Additionally, the proposed and enacted state laws provide guidance for conduct that would not constitute unlawful use of algorithmic wage setting. These exclusions include, for example, when employers (1) offer individualized wages based on data related to services workers perform; (2) disclose in plain language their use of automated decision systems, including the data considered by the systems and how the systems consider such data, to employees and applicants whose compensation is influenced or determined by these methods; and (3) develop and implement procedures to ensure the accuracy of the data considered by automated decision systems in setting wages.

Legal risks associated with AI-driven compensation decisions

The lawmakers advocating for these proposed state laws have emphasized that the unregulated use of AI by employers in compensation decisions may result in discriminatory compensation results. Indeed, employers’ AI-driven compensation decisions may be covered by and actionable under a variety of employment laws, including Title VII of the Civil Rights Act, the Americans with Disabilities Act, the Age Discrimination in Employment Act, the Equal Pay Act and/or applicable state and local laws.

The nature of automated decision systems already creates unique legal risk for employers, particularly in the context of relying on these systems to render employee compensation determinations. A key challenge employers face when using AI-driven tools in general is the lack of transparency in how the tools arrive at their conclusions or recommendations. While human decision-makers can explain the reasoning motivating compensation decisions, it is difficult—and in some instances may be impossible—to discern the reasoning underlying decisions made by certain AI tools. This leaves employers vulnerable to legal challenges regarding compensation decisions rendered by AI tools or software. The scope of potential liability may be amplified if the processes are used to set or influence the compensation of a large number of employees or applicants.

Takeaways for employers

For now, employers should ensure compliance with applicable federal and state laws that have been enacted or are scheduled to take effect in the near future. This includes, at a minimum, identifying each AI tool currently used in employment decision-making and assessing whether those tools are subject to regulation by any state or local laws. Employers also should establish and implement a comprehensive AI policy that outlines internal procedures for using AI, provides required notice to employees and applicants about AI use and mandates human oversight of AI-driven recommendations.

Looking forward, employers should actively monitor developments in federal, state and local legislation and agency regulations aimed at governing the use of AI in decisions related to employee compensation and other employment terms. As states move rapidly to establish boundaries for AI’s role in workplace decision-making, employers that proactively audit their AI-related practices and prioritize transparent human involvement in decision-making processes, including compensation decisions, will be better positioned to minimize legal risks and adapt to evolving regulatory requirements.

The post State lawmakers seek to regulate employer use of AI for wage decisions appeared first on HR Executive.

Research from the UC Berkeley Labor Center inventory of union contracts shows that collective bargaining is already being used as a tool to give workers a voice over how automated management systems improve jobs rather than degrade them.

Workers in several sectors have already won contracts that constrain how monitoring data can be used for attendance, performance evaluation, discipline or interference with protected activity, according to the UC Berkeley Labor Center’s inventory of union contracts.

The policy signal

In April, OpenAI published an industrial policy blueprint calling for formal worker co-governance of automation deployment across U.S. employers. “Give workers a voice in the AI transition to make work better and safer, including a formal way to collaborate with management to make sure AI improves job quality, enhances safety and respects labor rights,” as documented in the blueprint.

While OpenAI is a tech vendor and a business, it’s notable that the organization building some of the most powerful automation tools in the world calls for worker governance as a policy baseline.

OpenAI’s call for worker co‑governance parallels a still‑pending legislative effort in Congress, according to a brief from law firm Fisher Phillips. In 2023, the Senate introduced the No Robot Bosses Act. This aims to bar employers from relying solely on automated decision systems for hiring, scheduling, pay and termination decisions and would require human review and bias‑testing of those tools.

Read more: That AI notetaker could be your next compliance problem

The employee signal

About two‑thirds of U.S. workers cite risk associated with emerging technology as a top macro concern, according to MetLife’s 24th Annual Employee Benefit Trends Study, released earlier this year. That ranks alongside mental health and geopolitical instability as a present-tense pressure workers are navigating now.

As companies move faster on automation, the MetLife study finds that feeling connected at work and using human-centered skills remain the strongest drivers of workforce performance. Employees who feel connected are 25% more productive and show 15% stronger retention.

Findings from the research and grantmaking organization Washington Center for Equitable Growth document the forms of automated management that workers are pushing back against. These include algorithmic scheduling, pace‑setting software and continuous performance monitoring. These were identified as worker pain points across sectors, including logistics, healthcare, retail and financial services.

According to the Washington Center for Equitable Growth, many union contracts now include advance notice requirements when employers use automated management and surveillance tools, and some agreements include limits on how these tools affect workers’ job conditions. These provisions often emerged from workplace conflicts and grievances over the introduction of algorithmic tools.

Read more: AI’s $130M lobbying blitz hands HR the real AI compliance burden

What HR leaders should do now

For organizations interested in following the suggestions from OpenAI, there are a few areas for HR leaders to consider.

First, map what’s already deployed. Many organizations have more algorithmic management tools in place than HR leaders realize. These are often adopted at the department level without central visibility or policy.

Second, build a formal input process before the next deployment. This requires a defined protocol addressing who gets consulted, at what stage and what criteria determine whether a tool meets the bar for job quality.

Third, set explicit limits on harmful uses. The OpenAI industrial‑policy framework names workload intensification, narrowed autonomy and undermined scheduling and pay as areas that HR leaders can operationalize through written policies, vendor contracts and manager guidance.

“There is also a risk that the economic gains concentrate within a small number of firms like OpenAI, even as the technology itself becomes more powerful and widely used,” according to the blueprint. “Workers using AI might well agree that it’s increasing their productivity without believing they’re seeing the benefits.”

The post Increasingly, the next labor negotiation isn’t about wages. It’s about who controls the bots appeared first on HR Executive.

Anthony Salcito, senior vice-president and general manager of enterprise at Coursera, views this momentum as more than a technical surge. He suggests that the true driver of success in the modern enterprise lies in the human elements that technology cannot replicate. While Singapore leads the Asia-Pacific region in technical AI upskilling with over 169,000 enrolments, this interest is mirrored by a 185% year-over-year increase in enrolments for critical thinking. This parallel growth indicates that the workforce recognizes a critical truth: Technical proficiency is only half of the equation.

See also: AI training revolution: Upskilling for a new era

The shift towards human-centric transformation

Many organizations prioritize the mechanics of AI, focusing on prompt engineering or technical workflows. However, the most resilient enterprises recognize that the current shift is less about the tools and more about the people using them. Salcito observes that while a great deal of attention is placed on technical upskilling, the primary challenge for chief learning officers is harnessing organizational focus to drive tangible business outcomes.

“Many organizations are trying to transform,” Salcito says. “This is a human-based transformation, less of a technology-based transformation.”

This perspective suggests that leadership in the new era requires a fundamental change in mindset. When technology can provide rapid answers and automate complex tasks, the value of a leader shifts toward the ability to ask the right questions and make high-level decisions. Salcito emphasizes the critical connection between human skills and the digital landscape. Most leaders recognize that they need their talent connected to what AI is and how to use it to maximize their work. He argues that thinking differently and coming to different conclusions by bringing human-based skills to the world of technology is what really unleashes organizational potential.

Redefining professional seniority and the skills currency

The rise of augmented workflows has sparked a necessary debate regarding the traditional markers of professional competence. For decades, years of experience served as a reliable proxy for seniority. Today, a junior employee utilizing advanced tools can often produce output that rivals a senior lead in speed and technical accuracy. This dynamic raises the question of whether the concept of seniority is losing its relevance in a market that prioritizes immediate output.

Salcito argues that seniority remains essential, provided it is coupled with an openness to new organizational capabilities. He points to a shifting skills lifecycle in which the previous model of education has been replaced by a more kinetic one. In the past, an individual might have attended school for four years and carried that skill set through 40 years of work. In the current landscape, the requirement is more akin to acquiring 40% of a new skill set every four or five years.

“A skills-based foundation is only enhanced by seniority,” Salcito explains. However, he warns that seniority without the corresponding capabilities can become a liability. If an organization sets a mandate to be an “AI-first” organization and employees resist that move, it limits the organization’s success. The goal for HR leaders is to harness experienced talent and encourage them to bring decades of industry insight into this new technological paradigm.

Cultivating a culture of curiosity over mandates

For adoption to remain sustainable, it cannot rely on top-down directives. Instead, organizations must cultivate a culture where employees are inherently motivated to build new capabilities. Mandated learning rarely fuels the level of engagement necessary for a successful enterprise-wide transformation. Salcito remarks that in the best-case scenario, an organization creates a culture in which employees are hungry and curious to learn. He maintains that learning should not be mandated at any point, as that approach does not foster the engagement required for innovation.

Coursera has responded to this need by evolving towards a concept of “skills currency,” where learning is hyper-personalized and practice-based. This provides a verification foundation that offers a clear blueprint for hiring managers. By moving from broad course libraries to a verified skills path, organizations can assess talent based on demonstrated capabilities rather than just a university degree or a previous employer. This shift is particularly relevant as Singapore doubles down on AI as a national priority, requiring organizations to become beacons of transformation.

The North Star of organizational purpose

Looking ahead, the integration of AI is likely to be followed by further disruptions from robotics and quantum computing. Salcito remains optimistic about the future of the industry, especially as organizations shift towards a model in which verified skills serve as a universal language for talent management.

Ultimately, the most successful organizations will be those that maintain a consistent sense of purpose. While technology waves such as the cloud, mobile platforms and now intelligent agents seem to change the landscape, the fundamental principle of believing in and upskilling talent remains unchanged.

“All those technology waves have felt like the catalyst that was going to change everything,” Salcito concludes. “The heart that comes into this is the best organizations in the world will recognize those technology trends and accelerate their core mission, but they will have a fundamental North Star, a purpose and a meaning that extends far beyond the technology.”

The post Human intelligence: The key to navigating the rapid acceleration of AI appeared first on HR Executive.

Yet, AI strategy that is guided only by a pursuit of productivity will miss the mark, says Nickle LaMoreaux, IBM’s CHRO. In remarks at The Wall Street Journal’s recent inaugural CPO Council Summit in Palo Alto, Calif., LaMoreaux, the 2024 HR Executive of the Year, says many organizations are thinking of AI transformation at the individual process level: How can the tech help employees write emails, gather insights, generate ideas—ultimately, how can AI drive productivity in employees’ daily tasks?

However, she advocates for HR taking a broader view. “Where we as CPOs can get the biggest bang for the buck is figuring out how we can put AI, technology and automation into enterprise workflows,” she says. The ways employees access customer support, how managers run promotions process, how HRBPs answer questions, “these are the workflows we should be focused on,” LaMoreaux says.

Transforming such processes through AI will indeed increase productivity, but it can also move the organization toward measurable enterprise growth, which LaMoreaux says needs to be the real aim of AI integration.

Reimagining for reinvestment

As AI and automation make their way into the workplace, the impact on productivity is undoubtedly transforming conversations on workforce planning, as evidenced by the ongoing waves of mass layoffs.

LaMoreaux, however, challenges HR to think differently about AI’s potential. What if, in three years, AI could power 50% of the work currently done by humans in your company, but you had to keep your headcount flat, or even double it? What new products could you build? Which new clients could you go after with that freed-up manpower?

AI certainly drives efficiencies, leading to productivity and cost savings—LaMoreaux points to the $4.5 billion in free cash flow from IBM’s own AI journey over the last three years—but it’s not just a shot straight to the bottom line. To capture the full savings and promote real growth, HR has to also focus on how human talent will be reinvested.

“What growth can AI drive? What can we do differently?” LaMoreaux asks. Those are ideas she says many orgs aren’t focused on, which puts them at risk of “missing the moment.”

AI-driven growth in focus: entry-level hiring

IBM’s push to view AI as a catalyst for growth—not just productivity—is a driving factor in its pledge to triple entry-level hiring in the next three years. This comes at a time when so many other companies are shaving or significantly pulling back hiring in this area.

On one hand, these moves make sense, LaMoreaux acknowledges. After all, AI can handle a lot of the work that junior analysts, call center and customer support professionals did at IBM just a couple years ago. But while cutting entry-level hiring may be a “logical decision in the short-term,” these moves often come as a result of viewing AI simply from a productivity mindset.

Instead, think about long-term growth and strategically redeploying talent. What if entry-level hires could be redeployed to capture small and medium-sized businesses an organization hasn’t previously had the ability to pursue? What if, instead of maintaining products, software developers had the capability to focus on new products and features?

“It’s a growth mentality,” LaMoreaux says. And it’s one that’s working at IBM.

Software developers used to spend 80% or 90% of their time coding. Now that AI can handle much of the low-code work, entry-level developers have more time to invest in debugging automated code, and supporting customers and clients with customized configurations.

HR has been another area where AI-powered transformation is opening opportunities for new talent to drive growth. Early-in-career HR professionals used to be sent to Center of Excellence call centers and asked to tackle employee inquiries. Much of that work is now being handled by the firm’s Ask HR chatbot, with entry-level human talent layered on top.

For instance, employees are asked to rate their experience with Ask HR, and when they provide a negative rating, entry-level professionals follow up via phone to garner feedback and then take that information back, which she says can help the function train the AI while arming new entrants to HR with customer service and problem-solving skills. The redeployment is also having a meaningful impact on employee perspectives on HR. Now that the function is freed up to respond directly to employee feedback, it helps employees feel like they have more of a voice.

“We have to get comfortable constantly reengineering jobs to the value,” LaMoreaux says, “and that value is always going to be shifting.”

It will be up to HR to sell the potential of AI-powered growth to leadership and employees. For both, it will be about shifting the conversation from AI’s influence on employee productivity to its potential for employee experience. For instance, LaMoreaux says AI has freed up $4.5 billion at IBM, but it has also saved 22 million people hours, shrinking the amount of time the workforce is spending on administrative processes to single-digit percentages.

“We don’t want to just say AI is taking away the drudgery,” she says. “OK, to do what? We have to get people excited about the ‘to do what’.”

The post IBM CHRO: Focus on AI productivity at your own risk appeared first on HR Executive.

The ISG report finds HR performance is generally falling short of business expectations. Four in 10 organizations rate the efficiency of HR and their data for HR insights and decision-making “far below” to “somewhat below” expectations. HR leaders are looking to AI programs to help address these shortcomings by improving business efficiency, delivering new insights for improved organizational decision-making and boosting productivity and cost savings for the HR function, but so far, AI-driven productivity gains have been modest at best, with the average cost savings at 9 percent—well shy of the 30 to 60 percent returns cited by many providers in the market.

The capability of the technology is not what is holding organizations back. When asked about the main challenges impeding results, leaders will often point to gaps in data or governance, or the need to document and harmonize processes across the business. To truly capitalize on AI, data must be cleaned and integrated across various organizational platforms and the right AI governance model must be in place to ensure a safe, transparent and compliant approach.

These do represent real, foundational roadblocks to achieving results. However, there is an even larger missed opportunity in how organizations are approaching AI. Most organizations are evaluating AI on a process-by-process basis, identifying potential tasks for automation, compiling individual use cases, and selecting projects with the most straightforward ROI or that present the least risk to implement. And while this approach reduces risk and allows organizations to absorb smaller amounts of change within the organization, it limits results.

Getting results from AI investment is more human than technological

The solution to achieving AI results turns out to be more human than technological. AI should completely redesign the way we work—the roles and responsibilities of humans versus AI, interactions and processes. It requires us to change the way we think about work and our role in it. This should be HR’s home turf.

One might be tempted to blame HR for the function playing small—but this isn’t just an HR miss. After all, HR rarely drives the decision. Beamery data shows only 12% of CHROs influence AI choices, and just 30% are brought in early, compared with 60% of other C-suite leaders. If strategy, budget, timeliness and risk tolerance are set by executive leadership, IT and finance, key people-first considerations like talent and capability building get overlooked, and even the most promising technology will struggle to deliver ROI.

When AI is limited to acting as a job description builder, a resume screener or a chatbot, it isn’t because HR leaders lack imagination, but because leadership funds pilots instead of programs, and tools instead of capabilities. Yet, HR is not off the hook. If HR accepts AI as just another tool to implement rather than a force that reshapes work design, skills and decision-making, it reinforces the very transactional mindset HR claims to resist.

Few organizations step back and take the opportunity to reinvent how work can be delivered with AI. Rather than tweaking at the edges, the process of incorporating AI should start with a blank slate. When redesigning for speed and growth, starting with an “AI + human” mindset might deliver results that are two, five or even ten times the impact of limited, bespoke projects. When HR steps into strategy, HR can architect the future of work.

Over the next two years, we expect to see a more prevalent shift to HR models that incorporate a fully enabled digital AI layer. AI-led HR operating model transformation requires embedding AI across the entire lifecycle, redesigning roles and workflows, simplifying processes and shifting transactional work to technology and self-service. Rethinking how work can be done for AI is where more significant potential for savings and improved business results exists beyond discrete AI use cases.

The leaders of AI will put HR at the center of their strategy. Isolated examples have emerged of organizations combining HR and IT into a single “People and Digital Technology” function. Whether the functions ultimately converge or simply enjoy an enhanced partnership, putting HR at the center of the AI strategy from the start can turn it from simply deploying impressive AI technology into a catalyst for stronger team performance, better employee experiences and improved business impact. The organizations that recognize this—and empower HR accordingly—will be the ones that move fastest and compete strongest in the years ahead.

The post HR investment in AI is booming, but most companies aren’t seeing meaningful results appeared first on HR Executive.

Date & Time: Thursday, June 4, 2026 at 3:00 pm ET

Speakers:

Tom Gordon, Co-Founder and CEO, Slim Chickens

Description:

Starting a business isn’t easy. But quickly scaling up into a worldwide operation while staying true to your original values? That’s a major achievement, and that’s exactly what Tom Gordon has done as the co-founder and CEO of fast-casual restaurant chain Slim Chickens.

Gordon joins us for an exclusive webinar where we discuss how Slim Chickens built a fast-casual powerhouse by using the traditional brigade system in its kitchen paired with modern tech that automated payroll and streamlined HR processes. From hiring to development and all the way to succession planning, you’ll learn how Slim Chickens expanded from a single location in Arkansas to almost 300 locations worldwide.

Join Gordon as he discusses:

• identifying and developing future leaders
• using tech and full-solution automation to scale your business
• achieving rapid growth while staying true to your core identity

Register here!

The post The Recipe for Growth: Slim Chickens CEO Tom Gordon on Scalability and Succession Planning appeared first on HR Executive.

Date & Time: Thursday, May 28, 2026 at 3:00 pm ET

Speakers:

Lisa Bodell, CEO, FutureThink

Trinity Thomas, SHRM-CP, Workforce Marketing Partner, Paycom

Description:

When we have goals we want to achieve, complexity keeps us from making the most of our time. But what if it was possible to simplify our most tedious tasks and overcome the obstacles that constantly set us back?

Whether in our personal or professional lives, automation makes it possible. By pulling ourselves out of complex processes and eliminating needless work, we have the power to focus on the aspects of our jobs that really matter.

In this webinar, Lisa Bodell, CEO of FutureThink and bestselling author of Kill the Company and Why Simple Wins will explain how simplifying is easier than you think. Join her as she discusses:

• how unnecessary complexity keeps organizations from maximizing their output
• tips for focusing on the priorities that matter most and eliminating the “work of work”
• why simplifying complex tasks optimizes our work and lives

Register here!

The post Keep It Simple: How to Reduce Unnecessary Workplace Complexity appeared first on HR Executive.

Date & Time: Tuesday, May 19, 2026 at 3:00 pm ET

Speakers:

Steve Boese, President and Co-founder, H3 HR Advisors

Trish Steed, CEO and Principal Analyst, H3 HR Advisors

Description:

What HR topics should be your focus in 2026?

In a July 2025 survey,* we asked 1,250 HR and finance professionals about the technology trends, strategies and goals occupying their focus. Their eye-opening responses give us powerful insight into HR’s ever-changing landscape.

In this webinar, we’ll discuss how to leverage the top HR trends and priorities of 2026 to:

• give your organization a strategic advantage
• prepare your staff for significant changes coming in the HR world
• improve productivity with upgraded HR tech

Join us as hosts Steve Boese and Trish Steed of H3 HR Advisors discuss the trends and priorities impacting HR’s expanding role. Register today and make sure you’re prepared to meet the HR challenges of 2026 and beyond!

*2025 survey conducted by PSB Insights and commissioned by Paycom.

—

This Program has been pre-approved for 1.0 (HR (General)) recertification credit toward aPHR®, aPHRi, PHR®, PHRca®, SPHR®, GPHR®, PHRi and SPHRi recertification through HR Certification Institute® (HRCI®).

Paycom is recognized by SHRM to offer Professional Development Credits (PDC) for SHRM-CP® or SHRM-SCP® recertification activities. This program is valid for 1.0 PDC. For more information about certification or recertification, please visit shrmcertification.org.

Replay here!

The post Top HR Trends and Priorities for 2026 appeared first on HR Executive.

Date & Time: Tuesday, May 12, 2026 at 3:00 pm ET

Speakers:

Dr. Michelle Weise, Author of “Long Life Learning: Preparing for Jobs that Don’t Even Exist Yet”

Trinity Thomas, SHRM-CP, Workforce Marketing Partner, Paycom

Description:

Is your organization ready for the next era of work?

As the forward movement of automation and AI makes once-essential skills obsolete, career advancement is a major concern. Organizations that upskill and reskill employees have a strategic advantage by maintaining a competitive workforce and increasing productivity while reducing turnover.

Upskilling and reskilling also empowers employees to address skill gaps and prepare for future roles within your company. A May 2024 Paycom survey of 2,200 full-time U.S. employees revealed that 61% of respondents agree they’ll need to learn new skills within the next year to stay current in their job role or advance to a new one.

In this webinar, we’ll discuss how to:

• create a professional development program
• identify skill gaps and measure employee development
• build upskilling and reskilling into your retention strategy

Replay here!

The post Upskill, Reskill and Retain: How to Future-Proof Your Workforce appeared first on HR Executive.