How to speak AI: A guide to AI fluency in the workplace

#DeepSeek #AI - super interesting on how this helps businesses conceptualise ideas and generate plans, using comparative data. Also interesting is how we can teach AI how to avoid biases. Common theme again: solid structure for commands, not to make them complex, and build on initial commands to help AI process correctly for the best results. Just like humans, we process big pieces of information in manageable sizes. #Coursiv #professionaldevelopment #upskilling #AIadoption #AIforbusiness

Most evaluators know machine learning/AI is powerful, but few know how to actually use it. UNICEF’s new framework shows what that looks like in practice: ↳ how to match AI methods to different types of evaluation data, ↳ what it takes to clean and prepare messy reports for analysis, ↳ how pilots (like automated text scanning of evaluation reports) actually save time, ↳ and where human judgment still matters to avoid bias and misinterpretation. In short, it’s not just theory. It’s a step-by-step playbook for moving from buzzwords to real evaluation practice. 🔥 Follow me for similar content ✅ Join my mailing list to receive content directly to you inbox. It's free! https://lnkd.in/ec8mqV2M #ai

🚀 The PM–AI Paradox: When to Trust AI, When to Trust Your Gut As Product Managers, we’re all experimenting with AI - drafting PRDs, analyzing data, and summarizing research. It’s become the new co-pilot in our day-to-day. But here’s the catch: AI is most useful in the exact areas where judgment still matters most. Over-reliance risks missing the nuance that defines great product decisions. In my latest Substack, I’ve written about a framework PMs can bookmark: 👉 When AI deserves your trust 👉 Where over-reliance backfires 👉 Simple rules of thumb to balance AI’s speed with your own instincts Read the full post here: https://lnkd.in/gfRK_c_C #ProductManagement #AI #DecisionMaking #PMCommunity

The fluffy promise: "Just throw everything at the AI and you're done!" Why it's not that easy: (in the example of AI for market research) 1. Garbage IN → Garbage OUT It's 100% true that you can feed the AI with a ton of information and get insightful and succint outputs. BUT, the input has to actually be GOOD. That's on you. Curate the sources. 2. You must articulate what you look for. If you can't tell the AI what you want as a result of the research, the result will be vague and low quality. 3 Understanding of the basics of how AI works. The difference between a model, a chatbot and an agent. The current limitations. How to evaluate results And how to structure a system. These are the topics in the presentation below. 👇 I have it only in italian. 🇮🇹 It was for a workshop on AI for research. Should I translate it in English? Is it interesting to you? I know the noise on what you can do with AI is overwelming, but set some time to learn the basics. It makes all the difference. 👌

🔎 Struggling to keep policies accessible and up to date? We’re developing Policy Assistant — a secure, AI-powered tool that helps your team quickly find answers only from your approved document libraries. Every response is traceable back to the source, keeping knowledge consistent and reliable. Read more on our blog 👉 https://lnkd.in/gdrUzaYd #KnowledgeManagement #AI #PolicyAssistant #BizHub

"We want to use AI." But what they really needed was simple math. A few weeks back, one of our clients approached us to build an AI-based solution. They were an educational institution. Their goal was to track inventory leak (amongst other things). Now, sure, we could’ve trained a model to detect anomalies. But the outcome could be achieved with basic math. A simple look at standard deviation across inventory consumption was enough to flag concerns. No AI required. No inflated budgets. No tech for the sake of tech. We scrapped the AI idea and built a clean, insight-driven dashboard instead. Fast. Simple. Useful. And the client loved it. Because good AI consulting is about saying no to unnecessary AI. It’s easy to sell the hype. But real value comes from solving the right problem with the right tool. Ever had to say no to a client for their own good? Tell me your story 👇 #AIforGood #AI #ArtificialIntelligence #BusinessCaseStudy

AI doesn’t usually fail because of the models — it fails because the data behind them can’t be trusted. Ataccama’s Data Trust Assessment shows the average organization scores just 42/100 on data trust maturity. I found it eye-opening — worth checking your own score, seeing how you compare, and getting clear next steps to build trust at scale. Get started today: https://okt.to/M3q1Ko. #Ataccama #DataTrust #DataTrustAssessment #AI #DataQuality

Search is changing. 🔍 AI now weighs customer reviews and service quality — not just keywords. We put together a plain-English Radiant Report on what that means and how to adapt: 👉 https://lnkd.in/gsT5JYky #SmallBusiness #MarketingStrategy #Reputation #AI

Some are still on the couch.
 But the couch has been replaced with code. AI sees patterns—not context.
 It doesn’t understand the old ways of doing business, or how to move them forward. That’s where we fit. 👉 AI Won’t Replace Agencies—But It Will Redefine Them https://lnkd.in/eMKYKFrT #AI #AdTech #MarketingStrategy #CreativeAgencies #Firehill

"The Real Problem is not whether machine think, but whether men do ?" Relying solely on AI is unwise, and cultivating strong foundational skills is more important than ever. AI is a powerful tool to be used in support of human expertise, not as a replacement for it. Recently, I had an interesting experience where an AI tool gave me a wrong answer for a simple SQL sorting query. At first glance, the AI’s response looked convincing – but when I cross-checked, I noticed the ordering was completely off. #ArtificialIntelligence #GenerativeAI #CriticalThinking #Upskilling #ProblemSolving #FutureOfWork