In this episode of Spilling the Tea on HR Tech, Cliff Stevenson and Tammy Smith, Sapient’s senior manager of data science, mark the public launch of the 29th Annual HR Systems Survey, the most expansive and longest-running survey of its kind. Almost 10,000 professionals representing 4,670 organizations worldwide participated in last year’s survey.  In response to participant feedback, this year’s survey includes two entirely new sections covering finance systems and compliance and risk management.  Cliff and Tammy walk through how the survey works, why organizational-level data matters, and what participants receive when they submit their responses.

Key points covered include:

↪️ The survey now includes dedicated sections covering solutions for core finance, travel and expense, and financial planning.  Finance professionals, C-suite leaders, and business managers are invited to complete this new section.  

↪️ The survey platform saves responses so participants can complete the survey in multiple sessions if needed.  Sapient encourages distribution of the survey across departments and subject matter experts.   

↪️ Participants will receive an unabridged copy of the survey results, expected to be published in October 2026. As an additional bonus, after completing the survey, participants have the option to receive a benchmark report based on their answers and last year’s survey data for either their industry or a geographic region. IHRM also awards 10 continuing education credits to those completing the survey.  

↪️Over the last 29 years, the data set has grown exponentially.  For instance, in 2021participants represented 2,177 unique organizations compared to 4,670 in 2025. The annual research report has also expanded, growing from 150 pages to 380 pages over that same period.

The 29th Annual HR Systems Survey is now open through June 24th. Use the link below to add your organization's voice.

LINK TO SURVEY

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In this episode of The Pivot Effect, Teri Zipper and Susan Richards are launching something new. The Pivot Effect is a podcast built around the individual, where you are in your career, where you want to go, and what it takes to get there in a world of work that keeps shifting underneath you. In this first episode, Teri and Susan introduce the show's focus: the skills, mindset, and self-direction that matter now, whether you're navigating AI, rethinking your role, or just ready to stop following and start leading. Think of this as the conversation the organizational lens has been missing.

Key points covered include:

↪️ Why AI adoption is moving faster at the individual level than the enterprise level, and what that tells us about who's really driving change at work.

↪️ How early adopters are already offloading routine work to AI tools so they can focus on what actually moves the needle.

↪️ Why reinventing yourself every three to five years used to be the rule, and why that window is shrinking fast.

↪️ What Teri and Susan are planning to cover on the show, including career pivots, personal journeys, and the data behind where you work and why it matters.

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Teri Zipper

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Susan Richards 

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In this episode of Spilling the Tea on HR Tech, Stacey Harris and Cliff Stevenson dig into a news week in which the same question keeps surfacing: how much should you trust the data in front of you? Oracle laid off 30,000 employees, and the financial story behind that decision is more complicated than the AI narrative being used to explain it. Meanwhile, a meta-analysis of six major consulting firms working from the same data produced conclusions so different they barely resemble each other, which is its own argument for never acting on a single source.

They also tackle the real cost of removing humans from decision-making chains, using Laszlo Bock's post on AI-assisted military targeting as a case study for what happens when speed becomes the only goal. 

Key points covered include:

↪️ The official narrative on Oracle's layoffs is AI replacing unnecessary roles, but the numbers behind $58 billion in borrowing and $156 billion in data center commitments tell a more complicated story about cash flow needs.

↪️ Six consulting firms analyzing the same AI data produced an array of starkly different conclusions.  For instance, one firm concluded that AI had "zero economic impact" while another cited quadrupling productivity rates. According to the hosts, this shows why industry benchmarks and recommendations are not a reliable basis for your organization's AI decisions.

↪️ "Human in the loop" is not enough if that human is only doing a final sign-off without visibility into how the AI reached its recommendation

↪️ AI pricing is moving away from flat subscription models toward usage-based and connector-based charges, and buyers who treat AI as an unlimited resource right now are going to face a reckoning as that infrastructure debt comes due.

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Stacey Harris

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Cliff Stevenson

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In this episode of HR, We Have a Problem, Cliff Stevenson debuts as host alongside guest Aly Baxter, Director of Product Management at Indeed, to dig into what's actually happening on both sides of the hiring process as AI use accelerates. They look at why more AI adoption hasn't translated into faster hiring, what recruiters really need from these tools, and how Indeed's Smart Screening is trying to fix the dynamic between job seekers and employers. Whether you're trying to fill roles or land one, this conversation cuts through the noise and gets to what actually works.

Key points covered include:

↪️ AI adoption in recruiting is at 49%, the highest of any HR function, yet time to hire is still going up, which tells you adoption alone is not the answer.

↪️ Before adding any AI to your hiring process, map every step and how long it takes. That's the only way to know where it will actually help and how to measure whether it does.

↪️ For job seekers, validating your experience, certifications, licenses, work history, matters more than a polished resume in a world where employers can't tell what's real.

↪️ The goal on both sides is the same: get to a real human conversation as fast as possible, and the best AI tools are the ones that clear the path to that moment instead of replacing it.

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Aly Baxter

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In this episode of Spilling the Tea on HR Tech, Stacey Harris and Cliff Stevenson recap two of the biggest HR tech events of the spring season and break down what they actually heard from participating CHROs, mid-market HR leaders, and vendors. The conversation moves through a packed week of news, covering acquisitions, funding rounds, platform expansions, and many rebrands.

They dig into the growing debate around the use of synthetic data panels, the liability ruling against Meta and Google, and new research showing C-suite leaders still expect AI to yield productivity gains despite seeing little impact over the past three years. 

Key points covered include:

↪️ Organizations across mid-market and enterprise are still trying to get their existing HR systems working together, and many are frustrated that AI conversations keep taking priority over fixing that foundation first.

↪️ Proprietary data is what separates defensible companies from ones that can be replicated - that theme runs through the Findem/Glider acquisition, Payscale's Compass tool, and Origin's $50M raise.

↪️ The liability verdict against Meta and Google opens real questions for HR vendors incorporating AI into their solutions. In particular, vendors selling AI-supported coaching, performance management, learning, and recruiting tools could be held accountable for what their AI agents do.

↪️ Research from the National Bureau of Economic Research showed that CEOs and CFOs reported minimal productivity improvement from AI use over the last three years, and yet still predict nearly 1% productivity gains annually going forward. At the same time, data center capacity is dropping.  The data disconnect indicates that despite the ongoing AI hype, companies are in a wait-and-see mode when it comes to AI’s business and ROI value.   

The hosts get into the pros and cons of synthetic data panels – AI-generated, simulated groups that are supposed to mimic the behaviors, preferences, and survey responses of real people. They discuss the challenges of using synthetic panels for decision making and the questions customers should have when reviewing results. 

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Stacey Harris

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Cliff Stevenson

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In this fan-favorite episode of HR, We Have a Problem, Teri Zipper and guest Chris Taylor, Founder and CEO of Actionable.co, discuss why most training programs fail to drive lasting behavior change and what actually works. Drawing from data across 9,000 learning programs and over 100,000 participants, Chris shares the proven methodology behind turning workplace learning into measurable results. 

The conversation explores the gap between knowing what to do and actually doing it, revealing that most organizations spend 80% of training time on content when they should be spending 75% on context and application. Chris introduces practical strategies including the 3:1 context-to-content ratio, accountability partnerships that triple success rates, and cohort structures that dramatically increase commitment when groups stay under 10 participants.

Key points covered include:

↪️ Training programs achieve far greater success with a 3:1 ratio of context to content, allowing participants to find their personal "why" in addition to understanding organizational objectives.

↪️ Accountability partners increase the likelihood of sustaining behavior change by three times when participants check in at least twice after the initial session, yet this free and simple tool remains underused.

↪️ Cohort learning becomes significantly more effective when groups stay below 10 participants, with daily practice expectations and regular progress reviews at the start of each session.

↪️ AI will commoditize the "how" of change through accessible content, but human facilitation remains critical for helping individuals discover why they care enough to actually change their behavior.

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Chris Taylor

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Actionable.co

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In this episode of Spilling the Tea on HR Tech, Stacey Harris and Cliff Stevenson discuss Perceptyx's acquisition of Lyceum AI; the general availability of Insperity HRScale; and the just-announced Sana from Workday. The wide-ranging conversation also gets into Canva’s new Magic Layers for managing the design and content of legacy learning; Grammarly’s controversial Expert Review; people news at Employ, UKG, and Adobe; ICIM’s rebranding and Coalesce AI;  and filtered's SCORM Intelligence. 

The duo also calls out a potential pricing disrupter brought about by AI agents. Pricing models built around AI usage and API access are starting to hit real cost barriers for larger organizations

Key points covered include:

↪️ With the promise of bringing “superintelligence to work,” Workday has launched Sana for Workday, which includes: Sana for Workday, a new AI interface for Workday; Sana Self-Service Agent, which automates HR and finance workflows; and Sana Enterprise, designed to automate work across the enterprise systems and applications employees use everyday.

↪️ Insperity HRScale, created from Insperity’s partnership with Workday, is now generally available, giving small businesses access to enterprise-grade HR technology while creating a potential pipeline for Workday as those companies grow.

↪️ With the recent acquisition of Lyceum AI, Perceptyx seeks to translate employee signals into personalized capability and skills building in the flow of work. Or, as stated in the news release, to close the gap between employee insights into actual business impact.  

↪️ Grammarly disabled its Expert Review AI agent after backlash over its use of named writers' voices; the controversy, which has spawned a class action lawsuit, raises broader questions about the boundary between AI-assisted writing and unauthorized use of an individual's identity and creative IP.

↪️ Research facts about use of benefit brokers: Sapient’s 2025-2026 data shows that 65% of companies with under 2,500 employees say their brokers have significant influence on how they run HR.  A corollary: organizations using brokers or other third-party HR support are 90% more likely to be viewed as contributing strategic value to their companies.

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In this special episode* of HR, We Have a Problem, Teri Zipper and guest Zach Keep, Manager, Compliance Risk at Paychex, break down the compliance and regulatory shifts that HR professionals, finance teams, and business owners need to track in 2026. They dig into the One Big Beautiful Bill Act and what the "no tax on tips and overtime" provision actually means for employees. The conversation moves through AI legislation at the state level, where new laws are multiplying faster than federal guidance can keep up, and into retirement plan incentives that are making 401(k) adoption more accessible for small businesses than ever before. 

Key points covered include:

↪️ The "no tax on tips and overtime" provision in the One Big Beautiful Bill is a refundable tax credit, not a true exemption, and employees should weigh the tradeoffs before adjusting their withholding.

↪️ Federal tax credits under Secure 2.0, including credits for plan establishment and employer matching, have lowered the cost barrier enough that small businesses can now offer 401(k) plans without significant financial risk.

↪️ AI regulation is moving faster at the state level than the federal level, with most legislation focused on deepfakes, privacy protections, and automated decision-making, but that picture will likely shift through 2026.

↪️ Worker classification rules are still in flux, with litigation pending on the 2024 independent contractor rule, and state and local employment laws are filling gaps that federal rollbacks leave behind.

For up-to-date compliance resources for your business, visit: paychex.com/state-resources 

*This podcast episode is sponsored by Paychex.

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Zach Keep

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Paychex

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In this episode of Spilling the Tea on HR Tech, Stacey Harris and Cliff Stevenson cover a packed week of HR tech news ranging from SD Workx’s expanded European payroll reach to Canva’s acquisition of two AI companies that are quietly becoming relevant to HR practitioners. They dig into Workday’s Agent System of Record, now generally available; the DOL's new AI literacy framework; and Matt Shumer’s controversial essay on AI’s future that garnered more than 80 million views on X.  

Key points covered include:

↪️ Canva is aggressively expanding its design ecosystem with the acquisitions of MangoAI, which sells AI video ad optimization tools, and Cavalry, a U.K. based 2D animation design company.  These acquisitions aim to transform Canva from a simple template tool into a comprehensive creative ecosystem for both casual and professional users.

↪️ PayScale's 2026 Best Practices Compensation Report finds 61% of organizations now list AI skills as part of existing roles, but only 45% are adjusting compensation to reflect those skills.

↪️ Two legal cases involving AI use - one tied to a criminal investigation, another around attorney-client privilege - offer practical reminders that legally one must have full knowledge of the work to be done before relying on AI output.  Nor is AI output protected under attorney-client privilege.  

↪️ The U.S. Department of Labor released an AI literacy framework for guiding the development of training programs to equip American workers with foundational, non-technical AI skills.

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Cliff Stevenson

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In this episode of HR, We Have a Problem, Teri Zipper and guest Kate O'Neill, Founder and CEO of KO Insights, examine what it actually takes to lead through a period of rapid technological change. The conversation moves beyond AI adoption tactics and into the harder questions around how people make decisions, resist change, and find meaning in their work when automation is reshaping the ground beneath them. Kate draws from her background in tech humanism to explain why the fears employees have about AI are worth listening to, not just managing, and how organizations that skip those conversations tend to pay for it later. 

Key points covered include:

↪️ When employees resist new technology, they may be sensing real trade-offs the organization has not acknowledged, such as loss of institutional knowledge or cultural continuity. HR leaders are well-positioned to surface those concerns rather than manage around them.

↪️ AI tools work best as scaffolding beneath human judgment, not as a replacement for it. Organizations that focus on structuring unstructured data and building clear rules and thresholds will move faster than those chasing full automation.

↪️ "Bankable foresight" is Kate's term for signals you are not ready to act on yet but track over time so your decisions are calibrated to something beyond the current moment's anxiety.

↪️ Prompt skilling is the minimum viable entry point for AI adoption. Teaching people to write better prompts also develops clearer thinking and stronger delegation skills, making it useful well beyond AI contexts.

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Teri Zipper

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Kate O'Neill

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