Filtered

A year ago I posted a link to some research that highlighted four skills that were emerging as key to productivity in a post-LLM world, beyond the hype and one-off applications. Here are some resources I can recommend to help develop them.

We've collated some common "L&D pain points" that affect our customers, in case our experience in alleviating them can help you too...

The industry’s most accurate, honest, and rich search solution. Our first customer is already harnessing its power to self-curate the most relevant content, empowering admins to pinpoint hyper-relevant resources with ease. With polished metadata, relevance scores, and unparalleled accuracy, it’s search like you’ve never experienced before. Filtered’s search API doesn’t just find—it guides. See how it transforms user experiences and solves the fire-hose problem of irrelevant results. Ready to bring laser-guided precision to your platform? Let’s talk: https://lnkd.in/eNqT25a8 #contentchaos #contentdiscovery #learninganddevelopment #searchAPI

As the 2024 Learning events calendar draws to a close, we have been speaking with this years attendees and sponsors of World of Learning, Learning Technologies Exhibition & Conference, Association for Talent Development (ATD) and The LPI (Learning and Performance Institute) to name just a few. Its been an important year for these high quality (and highly attended) conferences as organisations try and match requirements centred on #skills, #automation and #AI with the latest learning tech vendor feature set and leading edge thinking. However one clear theme kept on coming up. Users and buyers are totally confused by the vendor market narrative in 2024, and particularly lost on how to tell the difference between an LMS and an LXP. How are organisations meant to make informed buying decisions when all providers appear to be saying exactly the same thing? So, if this sounds familiar - our latest research paper "The Future of the LXP" is now available and will guide you through the challenge here. This is essential reading for anyone preparing to come market (or if the process is already underway), if you're discussing how to optimise your learning provision or just feel like you are slipping behind the pace of technological change. Very interested in your thoughts Mike Zealley, Louise Scott-Worrall, Alex Ball FLPI, Alejandro Modarelli, Holly Best, Mark McCarney, Rosanna Ravey, Mark Williamson, Dion Gittoes, Eoghan Thompson, Fiona Burns, Jason Galea, David Smallbone, Adam Caldwell, Jonathan Smith KPMG UK KPMG US #kpmglearningservicesJoe Farrell Eric Thalasinos

I'm exceptionally happy to be teaming up with Dr Ashwin Mehta MBA FLPI to dig into the challenges that genAI will throw up for talent and content strategy (and just, the world, generally!) at #LNConnect24. He knows the research inside and out. I'm here to be aggravating. Topics like: - JUNK: is our codebase suitable for AI bolt ons and, more profoundly, can we break our habit of pushing junk food content on our people and calling it learning? - COST OF SKILLS: in 2025 expect CFOs to question the use of "marketing metrics" like clicks and completions in learning when they've been sold skills. Measuring the cost of skills, and therefore validating skills, will be central - LOCAL LANGUAGE MODELS. The world's greatest yet learning tool it may be, but our thesis is that lasting organisational and social benefit from genAI actually depends on tuning it with contextual and local knowledge. It's in London on Friday, hope to see some of you there.

L&D has always been a cornerstone of growth, but it’s time (it has been for 15 years tbh) to rethink how we deliver and measure learning—especially with GenAI now part of the mix. Learning initiatives are rigid, one-size-fits-all and ignored by the majority of the workforce. What does that result in? Knowledge that’s quickly forgotten and training that lacks impact. We need to move from content overload (which we call #ContentChaos) to focused, strategic learning. GenAI brings all kind of possibilities. It can deliver hyper-personalized, just-in-time learning, adapting instantly to each person’s specific role, goals, interests and skills. And lots more that's coming. And even more that none of us have even thought of yet. But new tech on its own isn’t enough. GenAI is a tool, but the strategy needs to be thought-through, and thought through by you. L&D teams must prioritize relevance, real-world application, and, where possible (it isn't, always!) measurable outcomes. Think beyond training hours and focus on actual capability building that drives the business forward. A substantial part of that is GenAI in the hands of the people we serve. If L&D wants to stay relevant, it needs to be much more proactively intentional now. It’s not about offering more content. It's not even just about offering better content. It's about helping people to do their jobs better. Which of the above was written by GenAI, and which by me? #LearningAndDevelopment #GenAI #FutureOfWork #IntentionalLearning

In a world where we are drowning in content, making sense of chaos is not an easy thing to do. You might say that Marc Zao-Sanders has made this his mission. Now he has generously shared a guide with 80 lessons learned from 15 years in L&D, many of them stemming from the past three years when Filtered launched Content Intelligence as a tool to help cut through the noise. It’s a curated set of reflections across five critical areas of L&D—selected not for their cohesion but for their richness, intrigue, and potential to shape our industry’s future. 💡💡💡 Here are a few of my favorite lessons, but you can download the full guide for free (link in the comments) #learning #learninganddevelopment #edtech #hrtech #learningtechnology [Disclosure: I am a member of the board at Filtered]

Would you like 15 years of high-value, hard-won L&D lessons and insights, distilled into a single, beautifully-crafted 100-page booklet, for free? Here you go. ♻️ Please REPOST so others in your network can benefit. 🏷️ Or tag specific people in the comments who need to see this. In August, I shared some of the most surprising lessons we’ve learned in Learning & Development—and the response was immense. The post went viral, with input from very many of the industry’s bigwigs. That post was followed by five others—each of them also popular and sparking insightful conversations. So, because of all that, I’ve expanded, refined, and polished these insights, turning them into a booklet of 80 lessons learned from 15 years in the field. Many stem from the past three years in particular, when we invented and launched Content Intelligence. This isn’t just another Best Practice guide. It’s a curated set of reflections across five critical areas of L&D—selected not for their cohesion but for their richness, intrigue, and potential to shape our industry’s future. I hope a few resonate with you, spark ideas in your organisation, and inspire further discussion and feedback. Ready to discover? Please share your thoughts (and lessons you've learned) in the comments. Let’s advance L&D together. It could do with some advancement. #Learning #Data #Skills #Tagging #Content #Discovery #ContentIntelligence

Every company is eager to dive into AI—but almost all are equally concerned about the risks. (10-page booklet below. Full article is on Filtered's blog.) On one hand, AI promises revolutionary results—faster decisions, better data insights, and staying ahead of the competition. But on the other, many businesses are worried about potential reputational, legal, and operational risks. We see this tension in almost every corporate conversation about AI: ❗ Data security breaches ❗ Bias and discrimination ❗ Job displacement ❗ Lack of transparency ❗ Misalignment with company values and policies These risks are real and serious, but they needn’t be show-stopping blockers. To reduce AI risk, your organisation will need to pay attention in these three areas: 💡 AI education and governance—make sure your workforce understands your AI ambitions and the risks involved. That also means being clear on your firm’s AI ambitions! 💡 Better data management—AI depends on good data, so prioritise the management of and education about data. 💡 Good old project management—AI initiatives need clear goals, human oversight, and common sense. But perhaps the safest and surest approach to AI adoption isn’t running the AI projects yourself. The best way to avoid risk is to appoint a trusted AI supplier. Have them operate the AI and deliver the insights your organisation needs—without exposing your company to direct risks. This way, you gain all the advantages of AI while ensuring the process is safe, well-managed, and aligned with your goals. If they’re a good, trustworthy, collaborative supplier, they should also be able to marry up their results with other experiments you may be conducting. 🦾 What steps are you taking to integrate AI into your business? Which suppliers do you trust? How did you come to trust them? ♻️ Found this useful? Please share to help others in your network navigate AI safely. 📌 Follow Marc Zao-Sanders for more insights on AI, productivity & tech.

Filtered has a long, intimate relationship with content, creating our own through to Content Intelligence vs Content Chaos. We have many battle scars, shortcuts & tips to share. Read through the full list by Marc Zao-Sanders in more detail here ⤵️ https://lnkd.in/eyuM2DsG