AI and the Future of Work: An Interview with Mercor

What do companies look for when interviewing candidates? Check out this blog by our very own Global Recruiting Manager Mark Butler! Learn why we expect both technical and non-technical people alike to have AI fluency, what expectations come with "AI fluency,” and how we select the best people and AI models for our workflows. Link: https://lnkd.in/gPvFqh_s

Artificial Intelligence (AI) and how they are increasingly replacing human roles. "In the top 40 most exposed jobs were customer service assistants (72%), financial advisers (69%) and product promoters (62%)". https://lnkd.in/dx3NiG6F

What I learned this year about not winging it with AI. When AI first landed on my desk, my strategy was…yes, wing it. Type something into the box, cross my fingers, and hope it gave me brilliance. Sometimes it did. More often it gave me something that sounded like a bad template downloaded from the internet - generic, lifeless, and not remotely usable. I assumed I wasn’t “technical” enough. But what I learned this past year is that you don’t need to be a coder or data scientist to make AI powerful. In fact, the people who use it best aren’t the ones with the fanciest prompts - they’re the ones who know their context, their business, and their people. Sound familiar? It should. That’s HR. Now every time I talk with HR leaders about AI, I share a few lessons I’ve picked up along my own learning journey. Not because I have it all figured out, but because I’ve lived through the awkward “winging it” stage, and I know how to move past it. 1. The human layer Is the secret weapon The same AI tools are available to everyone. The differentiator isn’t the technology - it’s how we use it. Empathy, judgment, pattern recognition, the ability to connect data to culture…that’s what makes outputs valuable. Without the human layer, it’s just words on a screen. 2. Stop asking for magic, start giving context The quickest way to get garbage from AI is to ask it something vague. The quickest way to get gold is to feed it the real details: your culture, your audience, the nuances of your business. Think less “clever prompt” and more “briefing a smart colleague.” 4. Small bets beat big bangs I’ve learned not to overhaul everything at once. The best results came from piloting one workflow, testing it, and seeing if it actually freed up time for better conversations or built trust in the process. Measured progress beats chasing shiny new features every week. 4. The robot can crunch, but only you can judge AI can spit out summaries, synthesize survey results, and draft comms. But only you can see that the real morale issue isn’t the merger - it’s how the rollout landed. Only you can read the room and know what matters. AI doesn’t replace judgment; it gives you more time to use it. What I’ve realized is this: AI won’t reward those who wing it. It rewards the ones with a game plan. The leaders who give it real context. The ones who use their judgment to interpret, not just copy. The ones who start small, learn fast, and keep the human layer at the center. So if AI still feels intimidating, don’t back away from it. Lean in. Treat it like a colleague who’s brilliant when you give it clear input, and absolutely lost when you don’t. Because AI isn’t here to replace HR leaders. It’s here to supercharge the ones who know how to lead.

Everyone’s talking about Artificial Intelligence, but few can explain what it actually means for business. Our latest blog post breaks it down in plain English: what AI really is, how it learns, and where it’s already driving results in HR, finance, marketing, and operations. 💡 Understand how to turn data and automation into measurable business opportunities. 👉 Read the full post: https://lnkd.in/gTZtGr2n 📘 Bonus: Download our free AI Glossary for Business Leaders to keep key terms at your fingertips. (at the bottom of the blog post) #ArtificialIntelligence #AIBusiness #DigitalTransformation #AriosTechnologies

A new Sky News article highlights 40 jobs most at risk of AI replacement (journalists, salespeople, customer service roles among them) — and 40 roles it “can’t touch”, especially those grounded in hands-on work, deep human judgment or physical skills. #AI #FutureOfWork #Upskilling #HumanSkills #CareerResilience #DigitalTransformation #JobSecurity #Innovation

Without doubt, AI will change many things. However, this study effectively shows why it must never be allowed to be a replacement for hard work, critical thinking, and creativity. The notion of "workslop" is present in any industry where AI is applied, and the problem will only be compounded if are not careful. https://lnkd.in/gK438Fpv

Everyone is forwarding these new OpenAI reports, panicking that we're using AI in the "wrong way." They're missing the point. The data is clear: AI can now match human experts at complex work, but most people use it as a glorified search engine to get fast, "good enough" answers. They're using it for "Doing," not "Thinking." And as a CEO, this should terrify you. Because this isn't a problem with your team; it's a mirror of your leadership. If you are the "Chief Problem Solver" who handles all the ambiguity, your team will naturally use AI to just "do" the simple tasks you assign them. They'll bring you the messy, ambiguous problems that AI can't handle, and your 60-hour week will continue. You're creating a culture of dependency. The 10-Hour CEO operates differently. I don't use AI to "do" my work faster. I used AI to build an "alter-ego" that contains my 20 years of expertise. I spent the time "thinking" with the AI, teaching it my decision-making patterns for approvals, hiring, and strategy. Now, my team doesn't ask me the simple questions—they ask my AI Alter-Ego. And it gives them expert-level answers, infused with my logic and context. This frees me up to handle the one thing that can't be automated: the future vision of the company. Stop worrying about how your team uses AI. Start obsessing over how you can use it to codify your own expertise. Are you building a team that uses AI to "do" tasks for you, or are you building an AI that lets your team operate without you?

Assessing GPT-5's Performance: AI vs Human Capabilities OpenAI has put its latest models through a new workplace stress test called GDPval, designed to see how they stack up against real human professionals across 44 job types in nine heavyweight industries like finance, healthcare, and manufacturing. In short: GPT-5-high, the premium version of the upcoming model, tied or beat human-generated work 40.6% of the time. Interestingly, Anthropic’s Claude Opus 4.1 edged it out with a 49% win/tie rate—though OpenAI attributes this to Claude’s knack for sexy visuals, not superior output. It’s worth noting that GDPval only evaluates task-based work like reports or market analyses, not the full spectrum of interactive, messy, and emotional tasks that make up a real 9-to-5. Still, OpenAI sees progress. Their internal economist believes these tools are coming in hot as workplace copilots, freeing skilled humans from tedium so they can tackle “higher value” projects. Read more 👇 https://buff.ly/BPbKNRs

“Wise leaders are those who model thoughtful AI use. Let your people see you thinking critically about AI outputs. Set clear guardrails — not to restrict, but to guide. Champion AI literacy and reward quality over velocity. I know that’s hard in a world that’s moving fast, but as they say: more haste, more slop.”

"Your survey is anonymous" Wink wink nudge nudge 😉 IYKYK... We're doing something at The Alliance that every leadership team should consider. We're surveying our entire organization on AI usage. Right now, every team is using AI differently. Some people use GPT, some use Claude, some use Clay's AI integrations. But for the most part, everyone's working in silos. We're not sharing learnings. How we're thinking about the survey framework We're asking three core questions: 1) How are you using AI currently? 2) How do you want to use it in the future? 3) Where do you see the positives and negatives? The goal is simple: understand the gaps. One of the most important things is we want to create more connection between the winning use cases that we've already started establishing in certain departments and how we can create more of that learning sharing across the entire org. Ex: Take Notebook LM, it can cut research time by 30 to 40% for building courses and content. But not every department who could be benefiting from that research is using this workflow today. That's why we're starting to do a better job at embedding AI training into our new hire onboarding process. We want people to understand how we use these tools internally and how they can make their work more strategic and creative. -- 👋 P.S. How would you react to this situation: We caught someone using an AI avatar during a job interview recently. They had trained an AI to do pre screen interviews for them haha. The only way we figured it out was asking them to spin in their chair. They obviously couldn't. Wild times we're living in haha. What would you have done??