Cognitive Computing in HR

I've been working on something exciting - Eunomia HR is relaunching with a sharper, simpler focus (and some freebies). Every HR leader I speak to says the same thing: “We know AI is coming fast… but we don’t know how to get a grip on it.” The blockers? - Legal & compliance uncertainty (Legislation like the EU AI Act, GDPR/UK GDPR, Data Use Act 2025). - Fear of bias, discrimination, or bad data. - Lack of clear policies, governance, or oversight. So from today, Eunomia HR is focused on two core services: 1) AI in HR Risk Assessments: Uncovering risks across your AI systems, processes, and policies. 2) Fractional AI Governance: Ongoing support as your “AI Policy & Ethics Partner”, without the full-time headcount. And because so many HR teams are starting from scratch, I’m also open-sourcing part of my IP: - AI Recruitment Vendor Scorecard - a structured tool to compare suppliers against compliance & ethics criteria. - AI Usage Policy Template for HR - ready-to-customise starter policy covering governance, risk, and compliance. - Universal Framework for AI in HR - a practical, six-principle governance model that helps HR leaders adopt AI responsibly. - QuickScore™ Self-Assessment – a 12-question quiz to benchmark your AI readiness. If you’re an HR leader worried about AI adoption but want to get a grip on risk, governance, and compliance, this relaunch is for you. The message is simple: AI in HR doesn’t have to be chaotic, risky, or overwhelming. With the right structures in place, you can adopt AI responsibly and with confidence.

The future of work will not be shaped by humans or machines alone, but by how well we blend their strengths in new forms of collaborative intelligence. As Ethan Mollick explains in his book, 'Co-Intelligence', success depends on viewing AI not as just a tool but as a partner to be invited to the table, one whose capabilities and limits will constantly shift, requiring ongoing experimentation and human judgment. This fundamental change raises a pressing question: what happens to HR when the “workforce” is no longer exclusively human? Traditional HR systems, designed for humans as the only source of workplace intelligence, need a redesign. HR must move beyond recruiting, onboarding, and performance reviews for people alone - toward shaping environments where humans and AI collaborate safely and meaningfully . This extends a question I raised in my recent article,  "From Org Structures to Work Structures: Reimagining HR in the Agentic Age" (link below), what happens to HR when the “workforce” is no longer exclusively human? The traditional HR stack was designed for a human cognitive monopoly. As agents take on a material share of work, those pillars need redesign. HR’s mandate must expand from servicing human roles to architecting the environment where humans and agents collaborate effectively, safely, and meaningfully. To frame that redesign, this paper draws on three somewhat complementary perspectives: (1) Dave Ulrich's Human Capability framework (2024-25), which provides a systematic taxonomy for organizing HR's value creation across talent, organization, leadership, and HR systems, giving us a stable foundation for what HR does. (updated in the revised version) (2) Complexity science (CS), which treats organizations as complex adaptive systems: dynamic, emergent, and not fully predictable (Dave Snowden & Boone, 2007) reminding us to work with emergence, not against it. (3) Computational design principles, inspired by the MIT SMR piece "Stop Deploying AI. Start Designing Intelligence" (Michael Schrage & David Kiron, 2025) and Stephen Wolfram's work on intelligence environments, providing practical tools for architecting human-AI collaboration. The landscape is shifting faster than our understanding. What seems clear is that HR's role is evolving beyond managing people to orchestrating beyond human intelligence. I don't know if this framework will hold up over time. But it might offer some practical starting points for those willing to experiment. Thoughts, feedback and counterarguments welcome.

HR is quietly getting rewired by AI - and I’m seeing it firsthand! Over the last few months, I’ve been deep-diving into LLM tools, and honestly, it’s changed how I operate more than any framework or training ever did. Here’s what that looks like in practice: 1. Built custom GPTs to simplify and operationalize company policies 2. Used Claude to structure my data analysis and decisions 3. Created automation workflows on n8n to categorize reward & recognition nominations The result? What used to take days now takes hours. Output velocity is up. Data feels sharper. Decisions feel more structured and scalable. A big part of this shift comes from working at Sirion, an AI-first environment that nudges you to experiment, fail fast, and rethink how work gets done. What actually moved the needle for me: -Treating Custom GPTs like “HR co-pilots,” not just tools -Using Claude for structured thinking, not just answers -Building small automations on n8n that compound over time One thing is clear - HR is evolving from people processes to systems thinking + intelligent tooling. #AIinHR #Productivity #ContinuousLearning #CareerGrowth

Augmenting HR with AI: Embracing the Shift, Not Fearing It Adapting to Artificial Intelligence (AI) has become the new normal. Yet, the fear of job loss often looms in the minds of employees. Like every technological advancement, AI has its pros and cons. But when embraced thoughtfully, it doesn’t pose a threat to jobs—it augments them. By automating routine, repetitive tasks, AI frees up time for HR professionals to focus on more strategic, high-value initiatives. It’s about shifting our role from transactional to transformational. Here’s how AI is reshaping the HR function for the better: 🔹 Talent Acquisition AI tools enable faster screening of resumes by mapping skill sets and required competencies. This not only saves time but also supports data-backed hiring decisions. Some platforms even forecast future talent needs or support DEI goals by analyzing gaps and suggesting focused actions. 🔹 Employee Engagement & Retention AI-driven sentiment analysis, pulse checks, and engagement surveys help us better understand what our people are feeling—early detection of disengagement or attrition risk allows timely and tailored interventions. 🔹 Learning & Development By identifying individual skill gaps, AI helps curate personalized learning journeys—ensuring we’re investing in the right capabilities at the right time. 🔹 Employee Support & Experience Chatbots and virtual HR assistants provide real-time responses to employee queries, improving employee experience and reducing turnaround time on operational matters. 🔹 Data-Driven Decision Making AI enables us to draw insights from vast data sets, allowing for proactive planning, predictive analytics, and smarter people strategies grounded in design thinking. Of course, AI cannot feel or think the way humans do—it lacks emotion, empathy, and context. That’s why continuous human monitoring and intervention remain critical to its success. Technology can guide us, but it’s the people who lead. As HR professionals, the goal is not to fear AI—but to embrace it as an enabler. With AI as our ally, we can evolve faster, lead smarter, and build a more human-centric, future-ready workplace.

I recently had a conversation with #Axios about how #AI is beginning to shift from buzzword to business reality in #HR - not as a standalone tool, but as something deeply woven into how teams work and make decisions. What stood out most to me was hearing how organizations are already seeing tangible outcomes when AI isn’t bolted on as an afterthought, but thoughtfully embedded into systems HR teams rely on every day. When #skills data, #predictiveinsights and core business information live on a common, governed foundation, HR professionals and managers can shift energy away from repetitive tasks and toward strategic people outcomes like development, retention and internal mobility. That shift — from reactive to insight-driven work — also brings real challenges around #dataquality, #governance and #changemanagement. It’s one thing to deploy new technologies; it’s another to ensure they’re trusted, ethical, and genuinely empowering for people and teams. There’s no single formula for success, but the conversation reinforced something I’ve seen again and again: when organizations start with clear, #human-centered #outcomes and prioritize responsibility alongside #innovation, AI can unlock efficiency and a more strategic role for HR. Happy to continue the conversation if you’re thinking about where meaningful AI adoption can truly move the needle in your #HCM practice. https://lnkd.in/g7NRS8bu

AI in Human Resources: Revolutionizing Workforce Management The field of human resources is undergoing a seismic shift as #artificialintelligence (AI) revolutionizes how organizations attract, manage, and retain top talent. From intelligent recruiting and enhanced employee experience to data-driven workforce planning and bias reduction, #AI is transforming #HR functions at an unprecedented pace. AI in HR Market Primed to Surpass USD 26.5 billion by 2033. Gartner predicts that by 2025, 50% of HR leaders will have moved toward algorithmic management to better organize and optimize their workforce. Unilever has implemented AI solutions from Pymetrics to reduce bias in hiring and improve diversity and inclusion efforts. Here I have written three applications in #humanresources leveraging AI with case study, action and tools. 1. Recruitment and Hiring: Case Study: Hilton Situation: Hilton implemented AI-driven tools to enhance their recruitment processes, specifically in screening and evaluating a large volume of applicants efficiently. Action: They employed an AI system that automates the initial stages of screening by assessing candidates' responses in video interviews. The AI analyzes verbal and non-verbal cues to determine suitability for the role. Result: This led to a more efficient recruitment process, reducing the time spent on each hire and improving candidate quality. The system helps in identifying the best candidates based on consistent criteria, reducing human biases. Tools: HireVue Pymetrics 2. Employee Engagement and Development: Case Study: IBM Situation: IBM sought to improve employee development and retention through personalized learning and career pathing. Action: They developed an AI-powered personal development platform that provides employees with tailored learning recommendations based on their current skills, job role, and career aspirations. Result: The platform has led to increased employee engagement and satisfaction as it actively aids in personal and professional growth, making learning opportunities more relevant and accessible. Tools: IBM Watson Career Coach Degreed 3. Performance Management: Case Study: Accenture Situation: Accenture aimed to revamp its traditional performance reviews with a more continuous and real-time feedback system. Action: They implemented an AI-driven platform that collects continuous feedback from various sources, providing employees and managers with more timely and frequent performance insights. Result: This approach has not only improved the accuracy and relevance of performance data but also enhanced the overall experience of performance management, making it more dynamic and aligned with individual goals and company objectives. Tools: Workday Reflektive As organizations grapple with the evolving workforce landscape, those that strategically leverage AI will be well-positioned to attract, nurture, and retain the talent essential for long-term success. #management

The Future of HR won't be defined by the companies that use AI—it will be defined by the ones that build intelligent AI teammates." HR is entering a new era. We're no longer talking about chatbots or automation. We're witnessing the evolution from AI → RAG → Agentic AI, where technology doesn't just answer questions—it understands context, retrieves organizational knowledge, and executes workflows autonomously. Here's how the journey unfolds::: 🔹 AI in HR Automates repetitive tasks such as resume screening, candidate matching, workforce analytics, onboarding, employee support, and performance insights. Popular Tools: ChatGPT, Microsoft Copilot, Claude, Gemini, Workday AI, SAP SuccessFactors AI, Oracle HCM AI, Eightfold AI, Phenom, HireVue. 🔹 RAG (Retrieval-Augmented Generation) Enhances AI by connecting it to your organization's knowledge base, enabling accurate, policy-aware, and context-specific HR responses. Popular Tools: Azure AI Search, Pinecone, Weaviate, ChromaDB, FAISS, Elasticsearch, LangChain, LlamaIndex. 🔹 Agentic AI in HR The next frontier of HR technology. AI agents that can plan, reason, collaborate across systems, and execute end-to-end HR workflows—from recruitment and onboarding to employee support, learning, and performance management. Popular Platforms: Microsoft Copilot Studio, Salesforce Agentforce, OpenAI Agents SDK, LangGraph, CrewAI, AutoGen, n8n, AWS Bedrock Agents, Google Vertex AI. The future of HR isn't about replacing people—it's about empowering HR teams to focus on strategy, leadership, culture, and employee experience while AI handles repetitive and operational work. The umbrella image represents more than technology—it represents the future-ready HR ecosystem. Each layer strengthens the next: ☂️ AI powers intelligence. ☂️ RAG powers knowledge. ☂️ Agentic AI powers execution. Together, they create smarter, faster, and more human-centric HR." The question is no longer, "Should HR adopt AI?" The real question is, "Is your HR function ready for the age of intelligent AI teammates?" #AI #AgenticAI #RAG #GenerativeAI #HRTech #TalentAcquisition #PeopleAnalytics #FutureOfWork #DigitalHR #EmployeeExperience #HRTransformation #Innovation #Leadership #DigitalHR #AIHR #AgenticHR

Guide for HR professionals: How to use AI effectively at work We are actively integrating AI across government processes and developing internal AI tools that streamline our team’s work. AI implementation is not about replacing people, but about empowering teams. Together with our partners, we prepared a practical guide for HR professionals. It shows how to automate routine tasks, improve hiring quality, and avoid mistakes when working with new technologies. Benefits for HR: 🔹 fast analysis of the market and team needs 🔹 clear and compelling job descriptions 🔹 the ability to process hundreds of résumés without losing quality 🔹 improved internal HR processes Safety was our top priority in developing the guide. The recommendations outline how to handle data, documents, and AI tools to prevent personal data leaks. In the guide, you’ll find: 🔸 tailored tips for the public sector and private companies 🔸 innovative examples from the Digital People Hub — from a Slack bot that generates job postings to 3D onboarding avatars 🔸 ready-made prompts and a curated list of tools 🔸 cybersecurity hygiene rules and legal considerations The HR professional will remain at the center of people operations, while AI will help streamline workflows. More details are available at the link: https://lnkd.in/eaUJDYbJ The recommendations were developed by the Ministry of Digital Transformation together with the National Agency of Ukraine on Civil Service and leading AI experts from the private sector, with support from the Digitalisation for Growth, Integrity, and Transparency Project (UK DIGIT), implemented by Eurasia Foundation and funded by UK Dev.

Embracing AI in HR: Eyes Wide Open In a recent enlightening discussion on the Career Club podcast, Hilke Schellmann, an Emmy award-winning journalist and author of "The Algorithm," delves deep into the nuanced interplay of Artificial Intelligence (AI) in our workplaces. As HR leaders, it's crucial we navigate these waters with both enthusiasm and caution. Here's why: The Bright Side: AI is revolutionizing how we attract, hire, and retain talent, offering unprecedented efficiency and scalability. From streamlining the recruitment process with AI-powered ATS systems to enhancing employee engagement through predictive analytics, the potential for positive impact is vast. Imagine customizing employee development paths with AI insights or using AI to match candidates to roles they're genuinely suited for, beyond what resumes can convey. The Cautionary Tales: Yet, the journey isn't without its pitfalls. Schellmann's research raises valid concerns about transparency and bias in AI tools. How does an algorithm decide who's fit for a role? Can it inadvertently reinforce existing biases? It's a reminder that without oversight, AI might not just replicate but amplify systemic biases, affecting who gets hired, who gets promoted, and who gets laid off. Moving Forward with Responsibility: 🔍 Transparency & Accountability: It's imperative we demand clarity on how AI tools make decisions. Knowing the 'why' and 'how' can help mitigate unintended biases. ⚖️ Ethical AI Use: Implement ethical guidelines for AI use that prioritize fairness and diversity, ensuring technology serves to support and enhance human decision-making, not replace it. 🔄 Continuous Monitoring & Adjustment: AI isn't set-it-and-forget-it. It requires ongoing evaluation to ensure it aligns with our values and ethics in practice, not just in theory. #AI in #HR presents a world of opportunities but navigating its complexities responsibly is key. Let's champion AI solutions that are not only innovative but inclusive, ensuring technology works for everyone. Your thoughts? How are you integrating AI in your HR practices while ensuring fairness and transparency? #ethics Career Club Live with Bob Goodwin podcast

Let's talk about AI in HR, because everyone's buzzing about it, but where are we really on the adoption curve? If we look at the classic technology adoption model, HR is still navigating the Early Adopter to Early Majority phase for AI. We're certainly past the "Innovators" – those bleeding-edge teams who were experimenting with chatbots and predictive analytics five years ago. They've laid some groundwork. Now, we see the Early Adopters gaining significant traction. These are the progressive HR organizations actively piloting AI-powered recruitment tools, intelligent HR service delivery platforms, and data-driven insights for workforce planning. They're seeing tangible benefits and are pushing the boundaries. The vast Early Majority is still largely observing, evaluating, and cautiously approaching. This is where the biggest hurdle lies – the "chasm." Concerns around data privacy, ethical AI use, integration complexity, and proving clear ROI are holding many back. They're waiting for more established best practices, proven case studies, and user-friendly solutions that don't require an army of data scientists to implement. The Late Majority and Laggards are the ones who will adopt once AI is ubiquitous and a competitive necessity. While AI's potential in HR is enormous – from streamlining operations to enhancing the employee experience – we're currently at a critical inflection point. HR leaders need to bridge this "chasm." It means focusing on practical applications that solve real problems, ensuring ethical guardrails, prioritizing user-friendly solutions, and demonstrating concrete value. The future of HR is undeniably intertwined with AI, but getting there requires strategic, human-centric implementation, not just hype. #AIinHR #HRTech #FutureofWork #DigitalTransformation #HRStrategy