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How is everyone navigating the pullback on DEIA efforts (in the US, at least)? I’m seeing a mix of quiet deprioritization, reframing under different language, or doubling down more intentionally (though this one is rare).  At the same time, workplace culture and employee experience efforts seem to be getting folded into “nice to have” buckets again, which feels… familiar and not in a good way. What’s actually happening inside your organizations right now and how are you handling it with your employees?

Resumes tell you where someone has been. References tell you what their manager was willing to say out loud. Interviews tell you how well someone prepares for interviews. But none of those things reliably tell you whether the person can actually perform in the role on day one. We thought about this - especially for roles where the gap between "interview performance" and "job performance" tends to be widest: customer-facing roles, high-pressure environments, anything that requires quick judgment under uncertainty. A few things I'm curious about from this community: Do you use any form of practical assessment or simulation before making an offer? If so, what does that look like? Where do you draw the line between "thorough vetting" and "asking too much of candidates"? Has anyone found a reliable signal that actually predicts real-world performance, rather than just interview performance? Would love to hear what's actually working (and what's flopped) — especially in high-volume hiring where you can't run 5 rounds for every candidate.

We've assessed 105 candidates for AI skills — here are the insights Over the past few months, we've run 105 AI skills assessments through AISA. Not multiple-choice tests. Not self-assessments. Real conversations where candidates demonstrate how they actually work with AI. Here's what the data tells us: Most people overestimate their AI skills. The biggest gap we see isn't in whether people use AI — most do. It's in how they use it. Accepting the first output. Never iterating. Copy-pasting without verifying. Using one tool for everything when three better options exist. Knowing tools ≠ knowing how to use them. Candidates who can name every AI tool on the market often score lower than those who use two tools deeply. Vocabulary without practice consistently scores in the bottom half. Critical thinking is the rarest skill. Of our five assessment dimensions, Critical Thinking — the ability to evaluate AI output, catch errors, and understand where AI fails — has the lowest average scores. Most candidates trust AI output at face value. The top 15% do something different. They don't just use AI. They've built workflows around it. They iterate with intention. They know when not to use AI. And they can explain their reasoning — not just their results. "My team uses AI" ≠ personal proficiency. One of the most common patterns: candidates describe their organisation's AI strategy fluently but can't demonstrate personal, hands-on skill. Strategy awareness and personal capability are two different things. We built AISA because we believe AI skills are the new literacy — and like any literacy, they need to be measured properly. Not with checkboxes. With evidence. If you're hiring for roles where AI competency matters, the gap between what candidates claim and what they can demonstrate might surprise you. aisa.to

I'm a HR professional and a tech-savy person and when I started building AI agents for our People function, I made every mistake: Picked a flashy platform that forced my team to leave Gmail. Adoption: 0%. Framed it as "save HR 20% time" instead of "remove entire categories of work." Treated chatbots and real agents as the same category. They're not. Tried to convince skeptics with demos instead of letting one early win do the talking. What finally worked: Pick the ONE workflow eating your team's week Build the agent inside the tool they already use — never a new platform Set the bar at "good enough to ship with 30 min review," not "perfect" Measure removed work, not added work Let early users sell the rest of the team. Don't pitch internally. We now have agents handling onboarding plans, JDs, performance scoring, and L&D kit production. Senior team's strategic output is up, not because they have more hours, but because their hours aren't fragmented anymore. Want to go deeper? 🔗 See what we're building → aiydou.com 🎁 Test all 4 agents free (first 20 sign-ups, no credit card) → aiydou.gumroad.com/subscribe 📅 Live training session — "Deploying AI agents in HR, end to end" → https://www.linkedin.com/events/7459682079761543168/ What's the ONE workflow you'd kill first if you could?

Morning everyone, I am a founder building in the future of work space. We want to help companies operate with intelligence as they build out their workforce in the AI era. We are trying to get that ever-elusive first design partner who can write that ever-elusive trustpilot review so that we can get that ever-elusive first sale. Anyone want to help a brotha out? Our tool is live and functional. Happy to demo. Here's my LinkedIn so that you can get in touch: www.linkedin.com/in/zhengallan Thanks!

One of the things that pushed me to build Poli (AI People & Culture Assistant) was realizing how much time HR teams spend answering the same questions repeatedly: PTO policies, leave requests, compliance questions -across Slack, email, and hallway conversations. Curious how others in this community are handling it: Are you using any AI tools to deflect repetitive HR inquiries? Has anyone experimented with a repository-trained assistant, and what were the adoption challenges? What's the biggest barrier: trust, accuracy, employee skepticism? I built a proof-of-concept to tackle this and learned a ton in the process. Happy to share what worked and what didn't but mostly just curious what you're all seeing in your orgs.

Hi everyone—I'm new to the group and looking forward to learning from your experiences 😊 I’ve been thinking about how cascading goals show up in different organizations—especially in companies with 1,000+ employees—and would love to hear how it works where you are. A few things I’m curious about: How are cascading goals actually being implemented in your organization? Is this something driven more at the departmental level, or centrally? Are they mainly used for development conversations, or tied more directly to performance and business outcomes? More broadly, how does your organization use the goals feature overall? Do employees have clear visibility into how their individual goals connect to larger company priorities? Really interested in what’s working (and what’s not), particularly at scale. Appreciate any insights you’re willing to share!

Last year, our AI in HR survey results sparked one of our strongest media moments and surfaced bold, unfiltered perspectives from this community. We featured voices directly from Culture First members , and the conversation was picked up by international news outlets! Now we’re back for round 2. TAKE THE SURVEY HERE --> PASSWORD IS: "HR" AI tools have exploded across the workplace. Hiring, performance, org design, decision-making… they're all shifting fast. Some teams are experimenting while others are overwhelmed. Everyone, though, is rewriting how work gets done. We want your hot take. What changes are actually happening? Is it all noise or more substantive? Where is it creating leverage… and where is it breaking things? What does the next 12 months look like from where you sit? The survey takes ~8 minutes. Mostly, the questions are quick rating scale items. You know we put some spicy ones in there, though !! Your input will shape a report launching end of-June across both Culture First and Transform communities, as well as teeing up more media opportunities. Want to be featured? We’ll again spotlight community voices in the final story and media coverage. If you’re open to being quoted, DM me @Heather Walker after completing the survey. I am Culture Amp's data journalist and I'll be crafting the data story and narratives based on your responses. Take the survey, share your perspective, and unpack what AI in HR actually actually looks like right now . TAKE THE SURVEY HERE --> PASSWORD IS: "HR "

Hey everyone 👋 Hope the hiring season isn't breaking anyone here 😂 Wanted to share something I came across that I think this community will find genuinely useful it's called Candexa AI. It's an AI recruitment tool built for HR folks, and honestly it tackles a lot of the pain points we discuss here regularly slow hiring cycles, CV overload, finding quality candidates without burning out. Some things it helps with: • Faster candidate screening • Smarter shortlisting using AI • Reducing unconscious bias in hiring • Saving hours on repetitive tasks Would love to hear if anyone else has tried AI-powered recruitment tools and what your experience has been like. Also, if you're curious to try Candexa AI — here's the link: [ https://candexa.ai ]