Anthony Sicuranza

If you're a TA leader feeling overwhelmed by AI options, this approach will change everything. Three months ago, I sat in a room with TA leaders discussing automation, AI and the future of TA. The same comment kept coming up: "We need an AI playbook. We need a roadmap." That's when it hit me - by the time a playbook exists, the technology would already be obsolete. But here's what would work: a way for leaders to assess their current TA org, then identify exactly where to focus, what to pilot, and how to unlock efficiency gains specific to their setup. So we have built an AI-first TA maturity model. Instead of generic advice, we take a step-by-step approach where we: ➡️ Baseline your current TA operations and capabilities ➡️ Identify your highest-impact efficiency opportunities ➡️ Recommend the right automation and AI moves for your context We developed this from months of working with TA teams across different company sizes and stages. Each team had different pain points, different AI readiness levels and different needs. This makes our offering comprehensive in solving for a range of TA contexts. We also showcase the work we have delivered for companies like bunq, DataSnipper and The HEINEKEN Company so you can see how we delivered tangible results. The companies making progress in unlocking efficiency and effectiveness through AI aren't waiting for perfect clarity. They're assessing where they are, picking the right first moves, and learning as they go. Doeke Geertsma and I released our first version of the TA maturity model last October. Collaborating with him is always a joy! It has been great to put our heads together once again to elevate that thinking further, this time placing AI front of centre in the model. If you're curious about where your TA org stands and what moves make sense for you, then click the link in the first comment to access our AI-first TA maturity model ⤵️

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Do you trust AI to make hiring decisions? The data says most people don't—at least in the U.S. AI is transforming the Human Resources landscape, but not without generating controversy. A recent article from The Predictive Index reveals a striking fact: in the U.S., 66% of candidates would not apply for a job if AI were part of the selection process. This skepticism is not unfounded. Cases like Amazon's, where a hiring algorithm learned to discriminate against women, demonstrate that AI can amplify existing biases rather than eliminate them. The key question for HR leaders is: can we explain the decisions our technologies make? The solution is not to reject AI, but to integrate it responsibly. The article proposes a hybrid approach that combines AI's efficiency with the objectivity of behavioral science. Behavioral assessments allow us to understand how people think and act, ensuring that hiring decisions are fair, transparent, and, above all, human. The next time you evaluate an AI tool, ask yourself: does this make my decisions clearer or just faster? The answer could change your talent strategy with AI for the better. #ArtificialIntelligence #HumanResources #Hiring #Technology #Leadership #Innovation #TalentManagement

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I was interested to read Bersin’s latest contribution to the thinking about HR today. Bersin’s claim that 2026 marks a “massive, AI-driven reinvention” of HR rightly highlights the momentum behind enterprise AI. I am left wondering whether they’re missing long-standing structural and capability issues that many organisations still haven’t resolved. Their projection that 30–40% of tactical roles can be automated is supported by emerging research on AI’s impact on workplace tasks, but I don’t believe automation inherently translates to value creation… unless it’s accompanied by a redesign of work and employee support systems. I agree that AI can improve efficiency and reduce bias in hiring and performance processes, but it does raise concerns about fairness, transparency, and employee trust that Bersin’s piece doesn’t fully address. So… Rather than positioning AI as a binary force that “resolves” HR’s identity crisis, I urge leaders to recognise that strategic value arises from how technology is integrated into human systems, not just from automation itself. Practically, HR teams need to be developing governance frameworks that mandate explainability, fairness checks, and ongoing validation of AI outcomes before full deployment. Upskilling existing HR professionals to take on hybrid roles (e.g. combining AI orchestration with people-centric expertise) is vital. Because investing in learning pathways now will mitigate displacement AND build resilience. HR functions should also embed continuous feedback loops from employees to monitor unintended consequences of AI systems on morale, wellbeing, and engagement. To avoid over-reliance on tech, we need to blend quantitative insights from AI with qualitative assessments (I’m thinking structured interviews and focus groups, as a start.) I’ve said it for longer than I can remember… Benchmarking and data literacy should become core capabilities within HR, because now we need to be even more discerning rather than just trusting what AI spits out. So, rather than being swept along by AI trends, HR is ideally positioned to shape an ethical, effective future of work that balances efficiency with human dignity. Gosh. Quite the Thursday brain dump! Have a good day! —— Get in touch or follow or 🔔 if you want to discuss! www.sopeople.co.uk

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HR is the pretty face of Discrimination, Racism and many other things. No amount of hiding behind the AI. AI is simply a black mirror what is there to begin with.

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Every HR leader I know assumed the HRBP role would be the last to get AI'd. Including me. I was advising a leader when he mentioned a well known tech company had recently eliminated their HRBP roles entirely. He was considering the same. I was caught off guard, because to me, HRBP isn't a transactional role. Reading a room. Knowing when to challenge a leader and when to support them. That's judgment work. I started as an HRBP and I credit it with why I'm a CPO today. So I went looking for data. I wasn't expecting to find much, but I did. IBM cut hundreds of HR roles. Their AI agent handles 94% of routine HR questions. Josh Bersin wrote that the HRBP is under real pressure at the mid and junior levels. The senior most are staying. For now. That's what prompted me to build a framework to navigate what's next for me and my team. Four buckets. Efficiency. Elimination. Redesign. And delayed elimination, work that looks fine today but probably isn't in a few years. Most organizations are in bucket 1 right now, including me. That's okay. But it's the beginning of the transformation, not the end. Some moved straight to elimination. Block, Atlassian. I get why. But, in my opinion, the tools aren't quite ready and the disruption cost is real. I'd be more deliberate before making that call. My advice to any senior leader right now is to ask yourself and your team: which bucket are you in and how are you planning for the rest?

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