Digital currency is coming for payroll. Bitcoin and stablecoins are fighting for that future.
Andy Maren — May 1, 2026
I want to talk about money.
Specifically, about the fact that the way we move money to workers is going through its most significant structural shift since direct deposit. And most HR and payroll teams are watching it happen from the sidelines.
Full disclosure before we go further: I hold Bitcoin. Have for a few years. I'm not going to pretend that doesn't color how I see this space — it does. What I'm going to try to do is be honest about what I think is happening and why I think HR and pay leaders need to be paying attention, regardless of where they land personally on crypto.
November 2025: the moment I started paying closer attention
On November 7, 2025, Paystand — a B2B payments platform that has processed over $20 billion in volume — acquired Bitwage, the company that built the first Bitcoin payroll infrastructure back in 2014.
If you're not familiar with Bitwage: they spent over a decade building the compliance infrastructure, international corridors, and payout rails to let workers receive wages in Bitcoin, stablecoins, or local fiat in nearly 200 countries. They served over 90,000 workers and 4,500 businesses. They were, for a long time, mostly a product for crypto-native companies and international freelancers.
When a B2B enterprise payments company with SoftBank backing acquires that infrastructure, something has shifted.
Paystand's CEO put it plainly: "Stablecoins just crossed from crypto curiosity to regulated money movement." What Paystand saw in Bitwage wasn't a niche payroll product — they saw the global payout rails that enterprise finance has been missing. And they bought it.
That acquisition is the clearest signal I've seen that legitimate payroll infrastructure companies are serious about digital currency. Not as a marketing play. As core product strategy.
January 2026: fast food gets there before HR tech does
On January 21, 2026, Steak 'n Shake announced it would pay hourly employees a Bitcoin bonus of $0.21 for every hour worked at company-operated locations — starting March 1, with rewards vesting after two years. The program runs through Fold, a publicly traded bitcoin financial services company.
Let that land for a second.
A fast-food chain with more than 10,000 hourly workers got further into Bitcoin compensation than most enterprise HR platforms have. The bonus is roughly 1% of the federal minimum wage per hour — not transformative on its own, but the structure is interesting: it functions like a long-term savings program with a vesting mechanic that mirrors how tech companies use equity. Stay two years, and you collect your accumulated Bitcoin.
Steak 'n Shake also holds $10 million in Bitcoin on its corporate balance sheet, accepts BTC via the Lightning Network at US locations, and has seen same-store sales jump more than 10% since rolling out its bitcoin strategy. This is not a stunt.
Fold formalized its Bitcoin Bonus Program for employers in April 2026 — letting companies deliver recurring bitcoin bonuses with built-in vesting without changing their existing payroll systems or taking on custody responsibilities. Fold handles conversion, custody, and employee delivery. The employer just designates a dollar amount on their existing payroll cadence. Simple Mining, a bitcoin mining company in Iowa, is allocating 1% of every employee's pay into Bitcoin, redeemable at year-end.
As Fold's CEO put it: "Cash hits an account and it's gone by Friday." The Bitcoin bonus is designed to be the thing that stays.
February 2026: stablecoins arrive at enterprise scale
Around the same time, the stablecoin side of this story was having its own moment.
On February 6, Papaya Global launched Banco Wallet — a global workforce payment product letting employees receive wages in stablecoins across 180+ countries. Four days later, Deel — which processes $22 billion in payroll annually across 150+ countries — announced its stablecoin payroll offering through a partnership with MoonPay, rolling out first in the UK and EU.
The distinction between Bitcoin and stablecoins matters a lot in payroll, and it's worth being precise about it.
A stablecoin — USDC, USDT, and others — is pegged to the value of a traditional currency, usually the US dollar. Its value doesn't fluctuate. That makes it operationally viable for payroll in a way that Bitcoin, with its volatility, currently is not for most organizations. You can commit to paying someone $1,000 in USDC and know exactly what that means when it lands. You cannot make the same commitment in Bitcoin.
Stablecoins are solving a real logistics problem: cross-border payments are slow, expensive, and opaque. Stablecoin settlement is near-instant, borderless, and significantly cheaper. For organizations with global teams and international contractors, this is genuinely compelling.
There are also significant open questions — about which blockchain the settlement runs on, whether transaction data is visible publicly, state-level wage laws, IRS classification of digital asset wages, and whether your compliance infrastructure is actually ready. I wrote about the compliance landscape in an earlier post and those concerns haven't gone away.
Where I actually land on all of this
I'm going to be honest about my own view, because I think that's more useful than a false neutrality.
I think stablecoins are the near-term answer for global payroll infrastructure. The volatility problem with Bitcoin is real, and for HR and payroll professionals who are responsible for people's livelihoods, building operational processes around an asset that can drop 30% in a week is not something I'd recommend right now. The Deel and Papaya announcements matter. The Paystand/Bitwage acquisition matters. The infrastructure is being built, the regulatory framework is arriving, and stablecoin payroll is going to be a standard offering across global HR platforms within three to five years.
But I also think Bitcoin is the long-term story. Not as the settlement currency — stablecoins win that — but as the savings layer. What Fold and Steak 'n Shake are building, what Block Rewards is doing in Canada with their Bitcoin Savings Plan as an alternative to RRSP contribution, what's happening with 401(k) access to Bitcoin as the Trump administration's executive order works through the Labor Department — this is the infrastructure for Bitcoin to become a standard employee benefit, not just an investment.
The organizations that are starting to think about this now — even if they're just asking the question, even if they're just putting it on the agenda — will be better positioned than the ones that wait for the trend to arrive fully formed.
HODL, as they say.
What I'd actually recommend
If you're an HR or pay leader, here's what's worth doing right now:
Know what your platforms are building. Workday, SAP, Ceridian, UKG — every major HCM has a digital currency roadmap. Ask your account team what it looks like. If they don't have an answer, that's also information.
Understand the regulatory landscape in your jurisdictions. The GENIUS Act (passed in 2025) created a federal framework for stablecoin regulation. Most states still have wage laws requiring payment in US legal tender, which shapes how stablecoin payroll can be structured for employees vs. contractors.
Ask the privacy question. Most stablecoin payroll products settle on public blockchains where transaction data is visible. Employee salary information on a public ledger should raise immediate questions for any HR professional who's spent a career protecting pay data.
Get curious before you get pressured. The Fold/Steak 'n Shake news is going to reach your employees. The Deel stablecoin launch is going to come up in contract conversations. The bitcoin 401(k) question is already in the news. Better to have a point of view ready than to be caught flat-footed.
This is a fast-moving space. I'll keep writing about it.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI and modern HR technology. She holds Bitcoin personally and writes about what's actually happening in the market — without the keynote optimism.
Anthropic just hired Workday's former CTO. Here's why every HR and pay leader should care.
Andy Maren — May 12, 2026
When Peter Bailis joined Anthropic last month as a Member of Technical Staff, the HR technology press gave it about a paragraph.
I've been thinking about it ever since.
Bailis was the Chief Technology Officer at Workday. Before that, he was a Stanford professor whose research focused on database systems and distributed computing — which is to say, the infrastructure that underlies how large organizations store, access, and act on data at scale. He is not a generalist. He is one of the most precise technical minds in enterprise software.
And Anthropic hired him.
Why this matters more than a typical executive hire
Anthropic's pattern of recent hiring is worth examining. The company has been systematically recruiting senior technical leaders from enterprise software companies — people who understand not just how to build AI systems, but how AI systems need to behave inside the operational reality of large organizations.
That's a different skill set than building frontier models. It's the skill set of someone who has watched a payroll system fail at 2am before a holiday run. Who knows what happens when a configuration error cascades through 40,000 employee records. Who understands that "good enough" is not a phrase that applies to pay data.
The fact that Workday's former CTO is now at Anthropic is, to me, one of the clearest signals yet that Anthropic is building toward enterprise HR and payroll capability — not as a distant aspiration, but as an active product direction.
What I've been building
I want to be transparent about something: I'm not writing this as a detached observer.
Over the last several months, I've been using Anthropic's tools — Claude's console, Cowork, and the API — to build HR workflow prototypes. A learning management system. A natural language headcount reporting interface. A document transformation tool for Workday release documentation. A rewards and recognition app.
None of these are production systems. They're prototypes. But building them has given me a practitioner's view of what Anthropic's tools can actually do for HR work today — and what the gap is between where they are and what enterprise HR needs.
That gap is closing faster than I expected.
The reasoning quality on complex HR scenarios is genuinely impressive. Multi-jurisdiction leave analysis. Compensation band modeling. Payroll exception logic. These are not simple tasks — they require understanding context, precedent, and the specific ways that HR data is structured in real enterprise systems. Claude handles them with a level of nuance that, six months ago, I would have told you was years away.
When Anthropic hires someone who built those real enterprise systems? The gap closes faster.
The signal in Workday's own filings
There's a line in Workday's most recent 10-K that I keep coming back to.
Workday's pricing model is substantially per-seat — tied to the number of workers a customer employs. In their risk factors, they acknowledge directly that if customer organizations reduce headcount, Workday's revenue is negatively affected.
AI agents don't have seats.
The scenario where organizations deploy AI agents to handle work that previously required human employees — and those organizations consequently reduce headcount — is a scenario where Workday's revenue model is under structural pressure. This is not speculation. It's a risk Workday has disclosed in their own SEC filings.
The company that is building the agents that might drive that headcount reduction just hired Workday's former CTO.
That's not an accident. That's a signal.
What this means for HR and pay leaders
I'm not writing this to alarm you. I've made that mistake before — alarm is not useful, and the people reading this have seen enough "AI is going to change everything" headlines to last a career.
What I am saying is that the convergence of serious technical talent, proven enterprise domain knowledge, and genuine AI capability at Anthropic is worth paying attention to. Not in a theoretical way. In a "what are the implications for how I think about my platform strategy over the next three years" way.
The HR technology landscape is changing faster than most vendor roadmaps acknowledge. The platforms that will win the next cycle are not necessarily the ones that are winning this one. And the organizations that are going to navigate that transition well are the ones where HR leadership is informed, curious, and asking questions before the contract renewal forces the conversation.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI and modern HR technology. She has spent her career inside the Workday ecosystem and has been building HR workflow prototypes using Anthropic's tools.
Why am I paying so much for Workday… just to see it on a pro golfer's shirt?
A love letter, a question, and a quote from a guy I'm skeptical of.
Andy Maren — April 7, 2026
I watched the Masters last weekend. Like I do every April. And I couldn't stop staring at the logos.
Rory won his second green jacket in a row. Unreal. And there on his bag, all four days, was the Workday logo — the same logo that's been traveling the PGA TOUR for years, the same one I've seen on Justin Rose, Matt Fitzpatrick, Davis Love III, Brandt Snedeker, Phil Mickelson. The same one that presents the Memorial Tournament under a 10-year deal with Jack Nicklaus. The same one on the rear wing of Lando Norris's McLaren every other Sunday.
Then came the thought I've been chewing on all week:
Is this where our licensing fees are going?
Let me be clear before I go any further.
I love Workday. My career was built inside the Workday ecosystem. Some of the best peers I've ever had, the best conferences I've ever been to, the best relationships I've ever made — and let's be honest, a few of the worst hangovers — all trace back to Workday events. I'm not here to throw stones at a company that has given an entire profession, mine, a career, a community, and a lot of Tuesday-morning headaches. So take what follows in the spirit it's meant: philosophical, not personal.
The napkin math
Let me walk through the numbers, because I think it's worth sitting with.
Rory McIlroy — golf's reigning back-to-back Masters champion and the highest-profile athlete in the sport — has been a Workday brand ambassador since 2022, carrying the logo on his bag at every event. Deal terms aren't public, but top-tier PGA TOUR ambassador relationships at that level are estimated in the range of $5–10M per year or more.
McLaren F1 is an Official Partner relationship that started in 2023, with branding on the rear wing of the car and the team kit at every Grand Prix. F1 mid-to-upper partnerships are widely reported to run $10M+ per year. With roughly 24 races on the 2026 calendar, that's a per-race impression cost that would make most HR software buyers wince.
Workday's overall Sales and Marketing spend in FY25 was approximately $2.4 billion — about 28% of $8.4 billion in revenue. That's not unusual for enterprise software. It's how enterprise software gets sold. And yet. When you're a Workday customer looking at a renewal invoice and wondering why the price went up again, $2.4 billion in sales and marketing is worth having in your head.
The question I keep coming back to
I'm not arguing that sports sponsorships don't work. Brand recognition matters in enterprise sales cycles. Decision-makers are human beings who watch the Masters and the F1 race on Sunday and Monday.
But I've also sat across the table from clients who were struggling to get their Workday implementation properly supported. Who couldn't get answers from their account team. Who were paying for modules they couldn't fully use because the implementation budget had run out. Who were looking at renewal costs and not seeing the ROI conversation they expected.
It's a reasonable question to ask: what would it mean if a fraction of that $2.4B went into product instead of Paddock Club hospitality?
The quote from a guy I'm skeptical of
Sam Altman tweeted something in 2015 that I've been thinking about all week. I'll be honest: I'm an Anthropic girl — but more on that in a future post. I find Altman's persona exhausting. But this one landed.
"You can skip all the parties, all the conferences, all the press, all the tweets. Build a great product and get users and win."
He was talking about startups. But it applies.
The HR tech space is littered with companies that won on brand and sponsorship spend and then underdelivered on product. And there's a generation of challengers — some of them running leaner, spending less on polo shirts and more on engineering — who are asking what happens when you just build the thing.
Who's going to be the first to prove that model works at enterprise scale in HR and payroll? I don't know the answer yet. But I'm watching.
What I'd actually want
I want Workday to be the company that proves the two things aren't mutually exclusive. That you can build something your customers genuinely love and show up at Augusta. That the brand investment is a reflection of product confidence, not a substitute for it.
The Workday community is one of the best in enterprise software. The conferences are worth going to. The relationships are real. The product, at its best, is genuinely powerful.
I just want the licensing fees to feel like they're going somewhere that matters to the people paying them.
That's the question worth asking at your next renewal.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI and modern HR technology. She has spent her career inside the Workday ecosystem and writes about what's actually happening in the market — without the keynote optimism.
The Workday-Sana deal is the biggest shift I've seen since Recruiting. Here's what nobody's saying.
Andy Maren — April, 29 2026
Josh Bersin nailed the analysis on the Workday-Sana acquisition. If you haven't read his take, go find it — it's worth your time.
But there's something I haven't seen anyone say yet. And I've spent a decade implementing Workday, so I want to say it clearly.
AI agents are about to make half of your Workday configuration obsolete. Not in five years. Now.
What this acquisition actually signals
Sana isn't just a learning platform. It's an AI-native system built around the premise that knowledge work — including training, skill development, and content delivery — should be automated, personalized, and agentic. Workday didn't buy Sana for its content library. They bought it for its architecture and its AI approach.
This is Workday making a bet on what the platform looks like in three to five years: not a system that HR professionals configure, but a system that agents operate.
That's a fundamentally different product than what most Workday customers are running today.
The part nobody's talking about
The teams still manually configuring business processes? They're going to struggle.
The teams learning how to train agents to do that work? They're going to win.
I know that sounds stark. But I've been close enough to enough Workday implementations to know how much time gets spent on configuration work that is, at its core, rule-based logic application. That's precisely the category of work that AI agents are getting very good at, very quickly.
Workday isn't just adding AI features. They are rethinking the entire platform architecture. The Sana acquisition is one of the clearest signals yet that this is where they are actually going — not as a roadmap item, but as a strategic commitment.
The part that worries me
Most organizations aren't ready for this.
They're still cleaning up data from implementations that went live three years ago. They have field-level customizations that were built around workarounds that nobody documented. They have business process configurations that were set up by consultants who are no longer around and that nobody fully understands.
AI agents need clean data. They need coherent process logic. They need a Workday instance that was built with intentionality and maintained with discipline.
If your Workday instance is a mess — and a lot of them are, through no fault of the teams running them — this wave is going to be harder to ride than the vendor demos suggest.
What I'd be doing if I were in an HR ops or Workday admin role right now
Get ahead of your data quality. I know that sounds unglamorous. But the organizations that will deploy agentic AI in Workday effectively are the ones that have clean, consistent data as the foundation. That's the work that matters most right now, and it's almost never the headline.
Understand what you actually have configured and why. Document it if it isn't documented. Know which business processes are supporting real requirements and which ones are historical artifacts that could be simplified.
Get curious about what AI-native configuration looks like. It's not far away. The consultants and admins who are learning this now will be worth more than the ones who wait.
I'm genuinely curious what other Workday people are thinking about this. Excited? Nervous? Both at the same time, which is where I land?
Come find me on LinkedIn. I want to hear from you.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI and modern HR technology. She has spent a decade implementing Workday across payroll, absence, and time tracking.
19 states now regulate AI in HR. Does your team know that?
Andy Maren — April 14, 2026
There's a number in the SHRM 2026 State of AI in HR report that stopped me cold.
As of February 2026, 19 of the most populous states in the US have enacted AI laws or regulations that apply specifically to employer or employment AI usage.
And 57% of HR professionals working in those states are not aware of those policies.
Read that again. More than half of the HR professionals directly affected by state-level AI employment law don't know the laws exist.
I'm not writing this to make anyone feel bad. I'm writing it because I think it's a genuine organizational risk that's hiding in plain sight — and because "we didn't know" is not going to be a defensible position for much longer.
What these laws actually cover
AI regulation in employment isn't one thing — it varies significantly by state, and the scope is broader than most people assume.
The categories showing up most frequently:
Automated decision-making in hiring. Several states now require that applicants be notified when AI or automated tools are used in screening or selection processes. Some require that a human review be available. Illinois was an early mover here with its AI Video Interview Act; other states have followed with broader requirements.
Bias auditing. New York City's Local Law 144 — which has been in effect since 2023 and influenced state-level legislation — requires employers using AI hiring tools to conduct annual bias audits and publish summary results. Similar requirements are appearing in state legislation.
Transparency and explainability. Some regulations require that employees or candidates be able to request an explanation of how an AI system reached a decision affecting them — particularly for hiring, promotion, or termination decisions.
Data governance. Several states are extending existing data privacy frameworks specifically to cover employee data processed by AI systems, with requirements around consent, retention, and security controls.
The important thing to understand is that these aren't future requirements. They are current law in a growing number of jurisdictions. And unlike GDPR, which many organizations spent years preparing for, these state-level AI employment laws are arriving faster and with less runway.
Why payroll deserves special attention here
I want to flag something that the general conversation about AI employment law tends to underemphasize: payroll is a particularly high-risk area.
Payroll systems are increasingly incorporating AI-driven features — anomaly detection, predictive spend forecasting, NLP-based query interfaces, automated reconciliation. Many of these features are being added by vendors as default capabilities, which means organizations may be running AI on pay data without fully realizing it or having evaluated the governance implications.
Payroll data is also some of the most sensitive employee data an organization holds. Salary, bonus, tax withholding, banking details, garnishments, leave balances — the dataset is rich and the harm from misuse or misconfiguration is immediate and concrete.
If your state is among the 19 that have enacted AI employment law, your payroll AI features are not exempt.
What I'd actually do right now
If you're an HR leader trying to figure out where to start, here's a practical sequence:
Step 1: Find out where you operate. List the states where you have employees. Cross-reference against the states that have enacted AI employment law. SHRM and the National Conference of State Legislatures both maintain updated trackers.
Step 2: Inventory your AI touchpoints. Document every place in your HR and payroll workflow where AI is involved — including vendor-supplied features you may have enabled without a formal evaluation. This is harder than it sounds and usually takes a few conversations with IT.
Step 3: Ask your vendors the right questions. For each AI-enabled feature in your HCM or payroll system, you should be able to answer: What data does this tool use? Does it make or influence decisions that affect individual employees? Is it documented and auditable? Your vendor should be able to provide answers.
Step 4: Update your policies and notices. Most employment AI regulations include a notice requirement — employees or candidates must be informed when AI is used in consequential decisions. If your offer letters, job postings, or employee handbooks haven't been updated to reflect this, that's a gap worth closing.
Step 5: Put someone in the room. Governance doesn't happen by accident. Someone in HR or Legal needs to own the AI compliance question and have a standing seat at the table when technology decisions are made. If that person doesn't exist yet, this is the year to create the role.
I want to be clear: none of this requires a legal team on retainer or a six-month compliance project. It requires knowing what the law says in the states where you operate, knowing what technology you're running, and asking the questions that most HR teams haven't gotten around to yet.
The organizations that will handle this well aren't the ones with the most sophisticated AI strategy. They're the ones where HR leadership is informed, engaged, and asking the right questions before the auditor does.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI and modern HR technology. She writes about what's actually happening in the market — without the keynote optimism.
I built an HR app. On a weekend. With no engineering background.
Andy Maren — March 25, 2026
I want to tell you about the strangest, most humbling, and genuinely exciting thing I've done this year.
Over the last several weeks, I built four functional HR applications. Not prototypes in the "I made a mockup in Figma" sense. Actual working software that runs on a phone. Real interfaces, real data flows, real logic.
I am not a developer. I have never written production code in my life. My background is HR and payroll implementation — Workday, mostly, which means I know configuration, business process logic, and data modeling, but my programming "skills" peaked at writing calculated fields in report builder.
What changed is a tool called Claude Code, combined with VS Code, a mobile development framework called Expo Go, and a UI component library called Gluestack. I've been building with these tools on weekends and evenings, and I want to share what I built and what I actually learned — because I think it has real implications for how HR leaders should be thinking about their own relationship with technology.
What I built
A custom learning management system integrated with Wistia
My first project. A lightweight LMS that hooks into Wistia — a video hosting platform — so that training content can be organized, assigned, and tracked without a bloated enterprise system in the middle. The idea came from conversations with clients who were paying significant amounts for LMS platforms they were using at about 20% capacity.
Building it forced me to think through what a learning system actually needs to do at its core: content delivery, progress tracking, completion reporting, and basic assignment logic. Stripping away everything else clarified why so many enterprise LMS products feel like overkill for what most mid-market organizations actually need.
A rewards and recognition app that pays workers in Bitcoin micro-transactions
This one raised some eyebrows when I described it. The concept: peer-to-peer recognition that actually carries a small monetary reward, settled in Bitcoin, delivered instantly to an employee's wallet. No gift cards, no "points" that expire in a catalog, no HR admin bottleneck.
I'm not suggesting every organization should do this — the regulatory, tax, and policy questions are real. But building it taught me something important about the gap between what digital currency makes technically possible in HR and what the industry has actually built for. That gap is large and it's closing fast.
A document transformation GPT for HR content
This one was built specifically for a consulting use case I kept running into: clients with enormous libraries of user guides, help documentation, and training materials in Workday — all formatted inconsistently, often outdated, frequently hard to find.
What I built was a tool that ingests that documentation, rewrites it to a consistent structure and format, and then runs a check against each new Workday release to flag content that may need updating. The time this could save an HR operations team is not small.
A natural language headcount reporting interface
The one that surprised me most in terms of what it revealed. A simple interface that lets an HR leader ask questions of their headcount data in plain English — "How many open roles do we have in operations that have been unfilled for more than 60 days?" "What's our voluntary attrition rate in the midwest region year to date?" — and get answers without opening a BI tool or submitting a request to analytics.
This one made me feel something I wasn't expecting: a little bit sad. Not because the technology is bad. Because I thought about how many hours I've watched HR business partners spend waiting for data that should be at their fingertips, and how much of that waiting is now technically unnecessary.
What I actually learned
The tools are genuinely different now. I don't want to overclaim this. Building these apps still required patience, iteration, and a willingness to read error messages at 11pm. But the gap between "I have an idea" and "I have a working prototype" is genuinely measured in days now, not months. That has not been true before.
My HR domain knowledge was the asset. The apps I built weren't technically sophisticated — any junior developer would look at them and find things to improve. What made them useful was that they were designed by someone who understood the actual HR workflow, the real pain point, the compliance consideration that needs to be built in from the start. That's not something Claude Code can supply. It's what I brought.
I now understand the vendor conversations differently. Having built something — even something simple — gives you a completely different frame for evaluating what vendors are selling. You understand what's actually hard and what's just positioned as hard. That's worth something.
The skills question for HR is real. I came into this with more technical comfort than most HR professionals because of my Workday background. And I still found parts of this genuinely hard. The HR professionals who are going to thrive in the next five years are the ones developing a working relationship with these tools now — not necessarily building apps, but understanding what's possible, staying curious, and refusing to treat "I'm not a tech person" as a permanent identity.
I'm going to keep building. I have a list of ideas — most of them are things I wished existed when I was in the chair. I'll share more as they come together.
If you're an HR leader who's been curious about this but hasn't started — start. Pick one small pain point. Describe it clearly. See what happens.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI and modern HR technology. She has been building HR software prototypes using Claude Code, VS Code, Expo Go, and Gluestack UI.
Should HR professionals be using ChatGPT? Here's what I actually think.
Andy Maren — March 10, 2026
I get some version of this question every week now.
"Andy, is it safe to use AI tools for HR work?" "Which one should I be using — ChatGPT or Claude?" "Our IT team sent a policy saying we can't use any AI tools at work. Is that right?"
So I'm going to answer it as honestly as I can, from someone who has been actually using these tools for HR work — not just writing about them.
First, a distinction that matters
"AI tools" is too broad a category to give one answer to.
There's a meaningful difference between:
Consumer AI chat interfaces — ChatGPT.com, Claude.ai — free or paid accounts that you access through your browser, where the data you enter may be used by the vendor in various ways
Enterprise or API versions — the same underlying models, but accessed through agreements with specific data handling terms, often with data retention turned off
On-premise or private deployments — AI systems running inside your organization's infrastructure, where data never leaves
When your IT team says "don't use AI tools," they almost certainly mean category 1. And they're not wrong to be cautious.
The risk isn't that Claude or ChatGPT is going to maliciously misuse your employee data. The risk is that data entered into a consumer interface may be:
Stored and potentially used for model training (depending on the vendor's settings and your account type)
Subject to the vendor's data breach exposure, not your organization's security controls
Visible to vendor staff in some support scenarios
Not covered by your organization's data processing agreements
For HR work — where you are routinely handling compensation data, performance information, employee health accommodation requests, termination details — that matters.
What I actually use, and why
I'll be direct: I use Claude, and I prefer it for this kind of work.
That's not a knock on ChatGPT — it's an excellent product and I've used it too. For me, the preference comes down to a few things.
Anthropic's approach to safety and data handling aligns better with the way I think about HR data. Claude tends to handle ambiguous requests more carefully, which I find reassuring when I'm working with sensitive employee information. The reasoning quality on complex HR policy questions — multi-jurisdiction leave analysis, compensation band modeling, HRIS logic — has been consistently strong in my experience.
I also just find the way Claude reasons through problems clearer and easier to follow. When I'm building something, I want to understand the reasoning, not just get an answer.
That said, I don't think either tool is inherently safe or unsafe for HR work. What determines safety is how you use them.
Rules I actually follow
Here's my personal operating policy for using AI tools in HR work. It's not an official framework — it's what I've landed on through trial and error.
Never enter personally identifiable information. Full names, employee IDs, Social Security numbers, dates of birth, specific salary figures tied to named individuals — none of this goes into a consumer AI interface. Ever. If I need to work through a scenario involving a specific employee situation, I describe it in general terms: "a salaried exempt employee in California with 14 months of service" rather than "Sarah Johnson in our San Francisco office."
Use enterprise versions when available. If your organization has a Microsoft Copilot agreement, a Claude Teams account, or an OpenAI enterprise contract, use those versions. They have different data handling terms. If you don't know whether your organization has these agreements, ask IT. The answer might surprise you.
Don't paste policy documents you haven't checked. Employee handbooks, compensation frameworks, benefits plans — these documents may contain information that your organization considers confidential. Understand what you're pasting before you paste it.
Don't ask AI to make decisions. Ask it to help you think. This is the most important one. AI tools are genuinely excellent for drafting, analyzing, stress-testing, and exploring. They are not a substitute for human judgment in HR decisions, and using them as one creates both legal exposure and real risk of harm to employees.
Screenshot or log what you used it for. If you're using AI assistance in an HR process — drafting a performance improvement plan, analyzing accommodation options, reviewing a job description for bias — keep a record of where AI was involved. You'll want that documentation.
What companies are actually doing
The honest answer is: all over the map.
Some organizations have blanket bans on consumer AI tools and haven't yet built out enterprise alternatives — leaving employees either ignoring the policy or doing without tools their peers at other companies use daily.
Some organizations have adopted AI tools organization-wide without adequate HR-specific guidance on how to use them responsibly.
The ones doing it well have: a clear policy that distinguishes between consumer and enterprise tools, specific guidance for HR and people functions on what can and can't be entered, an enterprise agreement with at least one AI vendor, and a training program that treats AI literacy as a core HR competency.
If your organization doesn't have that yet, the gap is worth raising.
The question underneath the question
When HR professionals ask me if they should be using AI tools, what I often hear underneath is: "Am I going to get left behind if I don't figure this out?"
The honest answer is yes — but probably not in the way you're imagining.
The HR professionals who will struggle are not the ones who used the wrong tool. They're the ones who never developed a working mental model for what these tools can and can't do, who never got their hands on them, who waited for the official guidance that sometimes never comes.
You don't need to become a technical expert. You need to be curious, careful, and willing to experiment with appropriate guardrails.
That's very much what I'm still doing myself.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI. She writes about what's actually happening in the market — without the keynote optimism.
The robots are coming. Or are they? What the AI layoff wave actually means for HR leaders.
Andy Maren — January 20, 2026
The headlines have been hard to ignore this month.
Amazon. Atlassian. Accenture. Company after company announcing layoffs — tens of thousands of jobs — and pointing to AI as the reason. Atlassian's CEO put it plainly when announcing 1,600 cuts in March: the company needed to restructure for "the AI era." Amazon has been explicit since last year that it expects to shrink its white-collar headcount as AI agents take on more of the cognitive work that humans currently do.
If you're an HR leader, you're reading these headlines with a particular kind of dread. Because you know what comes next. The board asks the question. The CFO asks the question. And then you're in a room being asked to explain how your organization is going to do more with less, faster than you thought, using technology that nobody on your team has fully figured out yet.
I want to slow down on this for a moment, because I think the way most people are processing the AI layoff wave is both understandable and slightly off.
What's actually happening
There are really two things being bundled together in the "AI is replacing jobs" narrative, and they're worth separating.
The first is genuine AI-driven displacement — cases where software automation is actually taking on tasks that humans used to do, reducing the need for headcount. This is real. It's concentrated right now in certain roles: customer support, coding assistance, data analysis, content production. It's accelerating.
The second is what some are calling "AI washing" — companies using AI as the stated reason for layoffs that are actually about cost discipline, post-pandemic over-hiring correction, or straightforward financial pressure. One survey found that nearly 60% of companies citing AI in layoff announcements acknowledge that the technology has only partially reduced hiring needs, not actually replaced full roles. And some companies are explicitly choosing to frame cost cuts as AI-driven because it reads as strategic rather than reactive.
Both things are true at the same time. AI is causing real job displacement. AI is also being used as cover for decisions that were going to happen anyway.
The nuance matters — especially for the HR professionals who are being asked to execute these reductions.
What this means for HR teams specifically
Here's the part that doesn't get written about enough: while other departments are processing what AI displacement means for their teams, HR is processing it for everyone and trying to figure out what it means for their own function simultaneously.
That's a genuinely hard position to be in.
The work of managing a workforce reduction — communications, severance, legal review, employee experience during transition — has historically been labor-intensive, human-intensive work. And there is a version of this year where HR leaders are asked to manage a larger and more complex wave of reductions with the same headcount, or less.
At the same time, the analytical and administrative work that HR teams do — headcount reporting, workforce planning, policy management, compliance tracking — is precisely the category of work that AI tools are getting meaningfully good at, fast.
So the honest answer is: yes, some HR roles will change significantly. Some will go away. New ones will emerge. And the HR professionals who are leaning into that reality now — understanding the tools, building new skills, staying close to what the technology can actually do — will be far better positioned than the ones waiting for the dust to settle.
The question I'd be asking right now
If I were still in an operational HR or pay role, the question I'd be putting to my team in January 2026 isn't "will AI replace us?" It's "what would our function look like if we designed it today, with the tools that exist today?"
Those are different questions with different answers. The first one is mostly anxiety. The second one is actually useful.
The organizations that are going to navigate this well are the ones where HR is at the table for the AI strategy conversation — not just being handed the outcomes to manage. If that's not where you are right now, that's worth examining.
I'll be writing more about specific tools, specific use cases, and what good AI integration in HR actually looks like in practice. Stick around.
And if you're dealing with this right now and want to think it through with someone who's been in the room, reach out. That's what I'm here for.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI. She writes about what's actually happening in the market — without the keynote optimism.
Hello from the trailhouse!
Andy Maren — January 1, 2026
I almost didn't write this post.
Not because I didn't have anything to say — I've been talking about this stuff for twenty years. But because starting something new at this particular moment in HR and payroll technology feels either brave or foolish, and I haven't decided which.
Then again, that's kind of the whole point.
Who I am
My name is Andy Maren, and I have spent the better part of two decades inside the world of HR and payroll technology. Workday implementations, mostly — the full stack, from Payroll and Absence to Time Tracking. The kind of work that puts you in the room when things go wrong at 11:47pm on a Friday before a holiday payroll run. The kind of work where you know exactly what "a configuration issue" really means, and you know which VP is going to be on the phone in the morning.
I've sat across the table from CHROs trying to explain why their absence balances don't reconcile. I've helped pay teams rebuild processes that were never designed for scale. I've watched organizations spend millions on platforms they didn't fully understand, signed off by leaders who were sold a demo and handed an implementation project.
I've also watched those same organizations — the ones who did the work, got the fundamentals right, built the right partnerships — come out the other side with something genuinely powerful.
I am one of you. I've sat in your shoes.
That's not a marketing line. It's the only credential I'm trading on here.
What Trailhouse is
Trailhouse Solutions is the company I've started to help HR and pay leaders navigate what comes next.
Right now, that means consulting. Advisory work. Being the person in the room who's done this before and can help you ask the right questions — about your current platform, your contract renewals, your AI strategy, your data, your team's readiness.
Eventually, I think it means something more. I have a product thesis I'm developing, and I'll write about it when the time is right. For now, the consulting practice is where I'm putting my energy, because the market needs good advice more urgently than it needs another product announcement.
The name is intentional. Trailhouse is a waypoint — the shelter at the halfway point where you stop, take stock, figure out what you're carrying that you don't need anymore, and decide how you're going to finish the climb.
That's where I think a lot of HR and pay teams are right now. Halfway up the mountain, not entirely sure how they got here, and looking at a lot of trail still ahead.
What's actually coming for this industry
I want to be honest with you about why I think the timing for this matters.
Two things are converging right now that I haven't seen in combination before in this industry.
The first is agentic AI. Not the chatbots. Not the copilots. Actual agents — systems that can reason, plan, take action across platforms, and operate with meaningful autonomy. The vendors are talking about it. The analysts are writing about it. And the gap between the demo and the production reality is getting smaller faster than most organizations are prepared for.
The second is digital currency in payroll. Stablecoins. Crypto-adjacent payroll infrastructure. I know that sounds distant for a lot of readers — like something that only matters to web3 companies or remote-first startups. It's not. It's coming for traditional enterprise payroll, and the compliance, legal, and system implications are real and underappreciated.
Both of these things are arriving faster than most HR and pay teams have bandwidth to absorb. And they're arriving into organizations that are, in many cases, still cleaning up data quality problems from implementations that went live four years ago.
I'm not here to frighten you. Fear is not useful, and alarm is not the same as insight.
But I do want to be the person writing clearly and honestly about what's happening — without the vendor spin, without the conference keynote optimism, without the "this is going to be seamless for your organization" framing that frankly hasn't served our community well.
What I'll write about here
My plan for this blog is simple: write things that I would have wanted to read when I was sitting in the jobs my readers are sitting in now.
That means posts about what's actually happening in the market — acquisitions, product announcements, platform shifts — with a practitioner's eye, not an analyst's.
It means posts about AI tools that are honest about what they can and can't do for HR and pay work specifically.
It means posts about data privacy, system architecture, and the questions that don't show up in vendor demos.
And it means the occasional post where I share what I'm building or learning — because I believe the only way to give credible advice in this industry right now is to stay close to the technology myself.
I post on LinkedIn regularly. This blog is where the longer thinking lives.
If any of this resonates, I'd love to hear from you. My contact page is simple. Drop me a line.
Here's to a year where curiosity turns out to be the most useful thing in your toolkit.
Update your curiosity.
— Andy
Andy Maren is the founder of Trailhouse Solutions, an advisory firm for HR and payroll leaders navigating the shift to agentic AI and modern HR technology. She writes about what's actually happening in the market — without the keynote optimism.