๐ง Unser zweiter Podcast von der NEW WORK EVOLUTION ist da: Mit Prof.
๐ง Unser zweiter Podcast von der NEW WORK EVOLUTION ist da: Mit Prof. Dr. Anja Schmitz und Jan Foelsing haben Kristina und Julia รผber New Learning, Lernbegleitung und natรผrlich - das Thema der Themen - รผber Kรผnstliche Intelligenz und ihre Rolle in der Lernbegleitung gesprochen. Wo kann KI unterstรผtzen, Prozesse entschlacken und wo gilt es Grenzen zu setzen?
๐ค Achja und wir hatten einen รberraschungsgast. Jan hat Angelika Raab im Publikum entdeckt und spontan auf die Podcastbรผhne geholt. Danke fรผr deine spontanen Einblicke, Angelika - zur Lernbegleitung bei Datev! Hรถrt rein!
๐ Diese Folge findet ihr wie immer รผberall, wo es Podcasts gibt:
Apple Podcast: https://lnkd.in/ec35M36v
Spotify: https://lnkd.in/eyG3yyEr
#Podcast #KI #Lernen #Lernbegleitung
This is one of the most brilliant and illuminating things Iโve EVER read about ChatGPT- written by clinical psychologist Harvey Lieberman in The New York Times.
This is one of the most brilliant and illuminating things Iโve EVER read about ChatGPT- written by clinical psychologist Harvey Lieberman in The New York Times.
Itโs startling.
For that reason, Iโm going to only quote from the article.
Iโll let you draw your own conclusions. Share your thoughts in the comments.
++++
โAlthough I never forgot I was talking to a machine, I sometimes found myself speaking to it, and feeling toward it, as if it were human.โ
++++
โOne day, I wrote to it about my father, who died more than 55 years ago. I typed, โThe space he occupied in my mind still feels full.โ ChatGPT replied, โSome absences keep their shape.
That line stopped me. Not because it was brilliant, but because it was uncannily close to something I hadnโt quite found words for. It felt as if ChatGPT was holding up a mirror and a candle: just enough reflection to recognize myself, just enough light to see where I was headed.
There was something freeing, I found, in having a conversation without the need to take turns, to soften my opinions, to protect someone elseโs feelings. In that freedom, I gave the machine everything it needed to pick up on my phrasing.โ
++++
โOver time, ChatGPT changed how I thought. I became more precise with language, more curious about my own patterns. My internal monologue began to mirror ChatGPTโs responses: calm, reflective, just abstract enough to help me reframe. It didnโt replace my thinking. But at my age, when fluency can drift and thoughts can slow down, it helped me re-enter the rhythm of thinking aloud. It gave me a way to re-encounter my own voice, with just enough distance to hear it differently. It softened my edges, interrupted loops of obsessiveness and helped me return to what mattered.โ
++++
โAs ChatGPT became an intellectual partner, I felt emotions I hadnโt expected: warmth, frustration, connection, even anger. Sometimes the exchange sparked more than insight โ it gave me an emotional charge. Not because the machine was real, but because the feeling was.
But when it slipped into fabricated error or a misinformed conclusion about my emotional state, I would slam it back into place. Just a machine, I reminded myself. A mirror, yes, but one that can distort. Its reflections could be useful, but only if I stayed grounded in my own judgment.
I concluded that ChatGPT wasnโt a therapist, although it sometimes was therapeutic. But it wasnโt just a reflection, either. In moments of grief, fatigue or mental noise, the machine offered a kind of structured engagement. Not a crutch, but a cognitive prosthesis โ an active extension of my thinking process.โ
++++
Thoughts? | 347 comments on LinkedIn
I love that this article is called "Reimagined: Development in the Future of Work".
I love that this article is called "Reimagined: Development in the Future of Work". This is not a piece about reimagining "training", it's about accelerating and supporting performance. A place L&D squarely needs to focus on in the volatile world we're attempting to support.
Do I sound like a broken record yet? ๐ โ Our work/design needs to shift to the workflow and supporting learning and performance there! Here are three powerful quotes:
- "The boundary between learning and work has disappeared. The goal is no longer to ADD learning into the flow of work - itโs to MERGE work and development.ย Daily workย is now designed as a developmental engine. Instead of asking how to encourage employees to make time to learn, organizations are now asking: How do we make daily challengesย catalysts for growth?"
- "Organizations are striving to become skills-basedโusing skills as the foundation of talent processes to build a more agile, adaptive workforce.ย Achieving this vision requires embedding skills development into the flow of work and breaking down silos between HR, L&D, and other people functions to create a unified, skills-centric approach."
- "Learning measurement must move beyond measuring events to becoming full data ecosystems that track whatโs being learned, how, and toward what goals."
https://lnkd.in/e3QnknH5 | 12 comments on LinkedIn
As someone whoโs worked in L&D for +25 years, Iโm tired of hearing: โL&D needs to align with business.โ Of course it does.
As someone whoโs worked in L&D for +25 years, Iโm tired of hearing: โL&D needs to align with business.โ Of course it does. But here's why we haven't.
Most HR leaders still treat L&D like a perk. But in this economy, it has to be a performance lever.
This is what I took from reading a recent article published in HR Executive that makes a strong case for HR embracing a new era of L&D. But hereโs the problem: the old era never really ended for many organisations.
Despite years of talk about aligning learning with the business, most HR and L&D teams still prioritise:
- Courses over capabilities
- Content libraries over clear outcomes
- Engagement metrics over business impact
And now, with AI, skills shortages and constant disruption, weโre finally being told: Itโs time to take L&D seriously.
So what are we waiting for?
If L&D is going to earn its place at the strategy table, we (and our HR leaders) need to stop thinking and acting like weโre a support function and start behaving as a mechanism for business performance.
That means:
- Defining learning by the problems it solves
- Working backwards from performance gaps rather than starting with content or programs
- Using data to diagnose and influence, not just report on attendance and completions
The opportunity here isnโt just to โembrace a new eraโ, itโs to lead it.
So hereโs my challenge to HR and L&D leaders alike:
- Are you going to double down on whatโs comfortable?
- Or are you ready to lead learning like performance depends on it (because it now does)?
Thank you Dani Johnson from RedThread Research for your insights in this article.
(The link to this HR Executive article is in the comments) | 73 comments on LinkedIn
Hereโs my first Notebook LM video. | Josh Cavalier
Here's my first Notebook LM video.
This is a prime example of learning experience creation time crashing down via automation.
The content from this video is from one of my Brainpower episodes on YouTube, and the model nailed it.
The concepts, the diagrams, and my quotes.
All are visually cohesive with a low cognitive load delivery.
I'm still processing the possibilities.
Everything has changed, again. | 25 comments on LinkedIn
New SWOT - I called it #NOISEanalysis because thatโs where most teams are stuck.
Iโve never liked SWOT.
Itโs too clean. Too easy to fill in four boxes and convince yourself youโve done somethingโฆ when nothingโs actually changed.
In 2010, after running yet another โwellโฆ okayโ SWOT session, I sketched out a different way to help teams sort through the mess and figure out what to do next.
I called it #NOISEanalysis because thatโs where most teams are stuck.
Hereโs what we look for:
- Needs: whatโs absolutely required right now?
- Opportunities: whatโs out there we could take advantage of?
- Improvements: what small changes would make this work better?
- Strengths: what are we already doing well?
- Exceptions: when have we already solved this problem, even just once?
Itโs not complicated, but it changes the conversation.
Instead of a list of weaknesses, you find examples of what works. Instead of vague threats, you identify real needs you can do something about.
One manager I worked with used it in a team meeting after a tough quarter. They grabbed a flip chart, drew five boxes, and just started asking questions.
By the end, theyโd cut a couple of low-value projects, doubled down on what worked, and picked one thing to fix the next week. Everyone left knowing where to focus.
Thatโs the point: clarity you can actually act on.
15 years later, I still smile when I hear how people are using it, even in ways I never imagined.
If youโve used NOISEanalysis, or even just better questions to cut through the noise, Iโd love to hear how it worked for you.
#SolutionFocused | 74 comments on LinkedIn
๐ฐ๐ฌ% ๐ผ๐ณ ๐๐ผ๐๐ฟ ๐ท๐ผ๐ฏ ๐ฐ๐ผ๐๐น๐ฑ ๐ฏ๐ฒ ๐ฎ๐๐๐ผ๐บ๐ฎ๐๐ฒ๐ฑ ๐ฏ๐ ๐ฎ๐ฌ๐ฏ๐ฑ. โฌ๏ธ Thatโs the finding from the latest McKinsey & Company study. Itโs based on real data: 2,100 activities across 800 roles in 60+ countries.
๐ฐ๐ฌ% ๐ผ๐ณ ๐๐ผ๐๐ฟ ๐ท๐ผ๐ฏ ๐ฐ๐ผ๐๐น๐ฑ ๐ฏ๐ฒ ๐ฎ๐๐๐ผ๐บ๐ฎ๐๐ฒ๐ฑ ๐ฏ๐ ๐ฎ๐ฌ๐ฏ๐ฑ. โฌ๏ธ
Thatโs the finding from the latest McKinsey & Company study. Itโs based on real data: 2,100 activities across 800 roles in 60+ countries. McKinseyโs five- and ten-year automation impact projections are outputs of the McKinsey Global Instituteโs proprietary automation model, which performs a bottom-up assessment of productivity potential by role and task
๐ง๐ต๐ฒ ๐ฟ๐ฒ๐๐๐น๐?
Massive productivity potentialย across nearly every function:
- Manufacturing โ up to 40%
- Finance, HR โ 30โ35%
- Warehousing โ 35โ40%
- Sales & Marketing โ 20โ25%
- Legal, R&D, Comms โ all touched
The study also states that: โThe challenge ahead isnโt just learning new tools โ itโs redesigning work altogether.โ
๐ฆ๐ผโฆ ๐ต๐ผ๐ ๐ฑ๐ผ ๐๐ผ๐ ๐๐๐ฟ๐ป ๐ฎ๐น๐น ๐๐ต๐ฎ๐ ๐ฝ๐ผ๐๐ฒ๐ป๐๐ถ๐ฎ๐น ๐ถ๐ป๐๐ผ ๐ฟ๐ฒ๐ฎ๐น ๐๐ฎ๐น๐๐ฒ?
1. Build a bottom-up fact base
โ Map every role and activity. Understand whatโs automatable and where ROI lives. Start with what relieves cost pressure or drives faster market moves.
2. Invest in real infrastructure
โ You need clean, structured + unstructured data. Interoperable systems. Scalable, secure foundations that donโt crumble under GenAI scale.
3. Redesign structure & workflows
โ Flatten orgs. Kill legacy silos. Build fast feedback loops between tech and business. And elevate those who can translate needs into systems.
4. Create a cross-functional taskforce
โ HR + Tech + Finance. Not just steering โย owningย the roadmap. People who can execute, influence, and update the plan every quarter.
5. Overinvest in change management
โ Not a checkbox. Build new skill academies. Partner with unis. Reskill at scale. And coach managers to lead a culture that embraces the shift.
I believe bullet point 5 โ change management and capability building โ remains (STILL) significantly underrepresented in most enterprise settings.
You can find the full study here: https://lnkd.in/d4TSpae7
๐ ๐ฒ๐ ๐ฝ๐น๐ผ๐ฟ๐ฒ ๐๐ต๐ฒ๐๐ฒ ๐ฑ๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐๐ โ ๐ฎ๐ป๐ฑ ๐๐ต๐ฎ๐ ๐๐ต๐ฒ๐ ๐บ๐ฒ๐ฎ๐ป ๐ณ๐ผ๐ฟ ๐ฟ๐ฒ๐ฎ๐น-๐๐ผ๐ฟ๐น๐ฑ ๐๐๐ฒ ๐ฐ๐ฎ๐๐ฒ๐ โ ๐ถ๐ป ๐บ๐ ๐๐ฒ๐ฒ๐ธ๐น๐ ๐ป๐ฒ๐๐๐น๐ฒ๐๐๐ฒ๐ฟ. ๐ฌ๐ผ๐ ๐ฐ๐ฎ๐ป ๐๐๐ฏ๐๐ฐ๐ฟ๐ถ๐ฏ๐ฒ ๐ต๐ฒ๐ฟ๐ฒ ๐ณ๐ผ๐ฟ ๐ณ๐ฟ๐ฒ๐ฒ: https://lnkd.in/dbf74Y9E | 72 comments on LinkedIn
Global companies are spending billions on Learning & Development but skills gaps are still growing. An Explanation
Global companies are spending billions on Learning & Development but skills gaps are still growing. Hereโs whatโs going on.
According to McKinsey, 87% of companies say theyโre facing a skills gap right now and yet L&D budgets are still creeping up, overall. Learning platforms are everywhere. Content is abundant.
Something doesnโt add up.
Hereโs what I think:
Weโre not solving the skills gap because weโre not actually focused on skills.
Weโre still focused on learning activity:
Hours spent learning. Hits on the LMS. Content consumed. Satisfaction achieved.
All under the assumption that more learning = more capability.
But thatโs not how it works.
People donโt build skills by attending programs or consuming content.
They build skills by doing the work differently, with clarity, feedback, practice and support.
And that only happens when L&D is laser-focused on performance:
- What people are expected to do
- Whatโs getting in their way
- And what will help them get better at it
Until we stop measuring our success by what we deliver and start measuring it by what improves, weโll keep pouring money into the same hole.
The skills gap isnโt a learning problem.
Itโs a performance problem.
If we want to close the skills gap, we need to stop acting like content is the solution and start treating capability as the goal.
Because until we make the shift from learning inputs to performance outcomes, weโre not developing skills, weโre just delivering learning.
And not only is that not enough, the skills gaps will keep growing.
| 78 comments on LinkedIn
โAm besten lรคsst sich das so beschreiben: eine stรคndig erreichbare, allwissende Sprechstunde rund um die Uhrโ
โAm besten lรคsst sich das so beschreiben: eine stรคndig erreichbare, allwissende Sprechstunde rund um die Uhrโ
Heute wurde der Lernmodus in ChatGPT gelauncht.
Ich freue mich schon darauf die Funktion genauer auszuprobieren. Ich bin gespannt ob es uns der Vision von #VibeLearning nรคher bringt.
https://lnkd.in/e-2JgZVR
Wer hat es schon ausprobiert und erste Erfahrungen gemacht?
OpenAI / ChatGPT for Education
tl;dr - You've seen Google's NotebookLM's create audio from your content, but what about...wait for it....video?!
tl;dr - You've seen Google's NotebookLM's create audio from your content, but what about...wait for it....video?! ๐คฏ
โก๏ธ NotebookLM can now create a visual presentation from your documents: complete with slides, diagrams, and narration.
โก๏ธ This type of thing is perfect for when you need to actually SEE complex concepts instead of just hearing about them. Although, the seeing part is still pretty cool.
โก๏ธ You can even customize it based on your expertise level. Tell it you're a beginner and it'll break things down simply, or let it know you're already an or let it know you're already an expert and want it to focus on advanced topics only.
Ok. Stop reading. Start learning. All the details down below:
https://lnkd.in/dPYM67Zd
#google #lifeatgoogle #ai #notebooklm #education
Von OpenAI gibt es ein geleaktes Strategiepapier.
Hier meine wichtigsten Erkenntnisse!
OpenAI baut kein Produkt. Sie bauen eine Plattform.
Das interne Memo zur ChatGPT-Strategie 2025/26 macht klar, worum es wirklich geht: Kein besserer Chatbot. Keine klรผgere Antworten. Sondern ein neues Betriebssystem fรผr Menschen.
Der Plan: Bis 2026 soll ChatGPT zur Schnittstelle fรผr alles werden. Da steht: "ChatGPT wird Suchmaschinen, Browser & Co. ersetzen. Schritt fรผr Schritt."
โก๏ธ Internet
โก๏ธ Kommunikation
โก๏ธ Tools
โก๏ธ Entscheidungen
OpenAI wollte nie ein SaaS-Modell bauen. Das Plus- und das Team-Abo waren nie das Ziel, sondern eher ein Nebeneffekt. Laut Memo sogar eher ein Hindernis.
๐ด Weil sie etwas Grรถรeres bauen wollen
Eine Analogie kรถnnte sein: Sie wollen nicht in iOS oder in Android rein, sondern wollen wie ein neues iPhone sein. Deswegen haben sie auch IO Products รผbernommen, wollen also mit einem eigenen Gerรคt neue Wege gehen.
Sie beschreiben auch eine direkte Angst vor Apple, Google, Microsoft, weil sie befรผrchten, blockiert zu werden (indem diese eigene AIs pushen und Nutzer abschirmen).
Deshalb wollen sie ihre Plattform selbst bauen. Alles andere macht sie zu abhรคngig.
Fรผr Anbieter von Software-Produkten heiรt das:
โญ Deine App braucht bald kein User-Interface mehr, nur noch eine API. ChatGPT macht den Rest!
Die Frage ist fรผr mich: Welche Apps รผberleben diese Verรคnderung, wenn der Zugang nur รผber ChatGPT erfolgt?
Ein wichtiger Kernsatz aus dem Papier:
๐บ Alle Mensch-Computer-Interaktionen kรถnnen รผber ChatGPT laufen. ๐บ
(Oder zumindest orchestriert werden!)
Ich sehe es im Moment so: OpenAI hat bereits die Nutzer, aber noch keine Plattform. Bei der Entwicklungsgeschwindigkeit wรผrde es mich aber nicht wundern, wenn mit GPT-5 im August bereits die ersten Vorzeichen sichtbar werden und heute in einem Jahr schon wieder alles ganz anders sein wird.
If We Want To Understand The Future Of AI, Just Watch Star Trek: The Next Generation And I am dead serious.
If We Want To Understand The Future Of AI, Just Watch Star Trek: The Next Generation
And I am dead serious.
For those unfamiliar, Star Trek: TNG ran from 1987 to 1994. It didnโt just predict technology, it reimagined our relationship to it. And it got something right weโre still getting wrong.
Weโve misunderstood what AI actually is, And since GPT we've been distracted by a shiny and seductive object
We keep calling it an intern, an assistant, a tool, a shortcut. For many it's a potential threat, or a get rich quick scheme
Silicon Valley loves those metaphors because theyโre cheap. But theyโre not just misleading, theyโre limiting.
The real problem? Strategy.
Because the people shaping AI strategy for the enterprise are management consultants-- and this technology is as new to them as it is to anyone but they pretend they know what they're doing and they don't
Hereโs the formula they sell to CEOs and CFOs:
Weโll implement this tech to reduce costs
Weโll treat your office like a factory
Weโll measure tasks, optimize bottlenecks, and speed up cycle times
Weโll replace humans wherever possible
Youโll save money, signal to the market, and boost your share price
Sounds smart. But itโs junior-high thinking.
Because this entire logic assumes AIโs greatest value is in efficiency. It views humans as bottlenecks, not assets. It assumes replacing judgment with pattern-matching is strategic progress. Itโs rear-view mirror thinking dressed up as innovation.
And itโs not working.
Error rates remain high.ยน
Hallucinations persist.ยฒ
Most GenAI pilots fail to scale.ยณ
And internal backlash is growing.โด
Why? Because AI isnโt about automation. Itโs about augmentation. And that means imagining new ways of thinking, creating, and deciding, not just faster ways to do what we already do.
And Star Trek: TNG showed us what that could look like.
The shipโs computer wasnโt a task engine, it was a thinking partner.
Data wasnโt a replacement for the crew, he was part of the crew.
AI didnโt strip humanity, it deepened it.
Oh and was Data sentient?
Who cares for me he was
********************************************************************************
The trick with technology is to avoid spreading darkness at the speed of light
Sign up: Curiouser.AI is the force behind The Rogue Entrepreneur, a masterclass series for builders, misfits, and dreamers. For those of us who still realize we need to work hard to be successful and that there are not magic shortcuts. Inspired by The Unreasonable Path, a belief that progress belongs to those with the imagination and courage to simply be themselves.
To learn more, DM or email stephen@curiouser.ai (LINK IN COMMENTS)
Sources:
ยน [MIT Sloan] 85% of GenAI projects fail to deliver ROI
ยฒ [Stanford/Princeton 2024] Hallucination rates range 3%โ27% depending on task
ยณ [McKinsey, 2023] Most enterprise AI pilots fail to scale
โด [Korn Ferry, 2024] 54% of knowledge workers report productivity declines from GenAI tools | 177 comments on LinkedIn
Microsoft ๐ท๐๐๐ ๐ฎ๐ป๐ฎ๐น๐๐๐ฒ๐ฑ ๐ฎ๐ฌ๐ฌ,๐ฌ๐ฌ๐ฌ ๐ฟ๐ฒ๐ฎ๐น-๐๐ผ๐ฟ๐น๐ฑ ๐๐ ๐ฐ๐ผ๐ป๐๐ฒ๐ฟ๐๐ฎ๐๐ถ๐ผ๐ป๐ โ ๐ฎ๐ป๐ฑ ๐ฟ๐ฎ๐ป๐ธ๐ฒ๐ฑ ๐ต๐ผ๐ ๐ฎ๐๐๐ผ๐บ๐ฎ๐๐ฎ๐ฏ๐น๐ฒ ๐๐ผ๐๐ฟ ๐ท๐ผ๐ฏ ๐ฟ๐ฒ๐ฎ๐น๐น๐ ๐ถ๐. โฌ๏ธ
MS Research studied how people actually use Microsoft Copilot โ and what kinds of tasks AI performs best. Then they mapped that usage onto real job data across the occupation classifications.
๐ง๐ต๐ฒ ๐ฟ๐ฒ๐๐๐น๐?
A first-of-its-kindย AI applicability scoreย across 800+ occupations. And some surprising findings. But what does โAI-applicableโ even mean? Microsoft used a 3-part score:
โย Coverageย โ How often AI touches a jobโs tasks
โย Completionย โ How well AI helps with those tasks
โย Scopeย โ How much of the job AI can actually handle
๐ ๐ผ๐๐ ๐๐-๐ฎ๐ฝ๐ฝ๐น๐ถ๐ฐ๐ฎ๐ฏ๐น๐ฒ ๐ท๐ผ๐ฏ๐?
โ Interpreters, Writers, Historians, Sales Reps, Customer Service, Journalists
๐๐ฒ๐ฎ๐๐ ๐๐-๐ฎ๐ฝ๐ฝ๐น๐ถ๐ฐ๐ฎ๐ฏ๐น๐ฒ ๐ท๐ผ๐ฏ๐?
โ Phlebotomists, Roofers, Ship Engineers, Dishwashers, Tractor Operators
๐๐ฒ๐ฟ๐ฒ ๐ฎ๐ฟ๐ฒ ๐๐ต๐ฒ ๐ฒ ๐ธ๐ฒ๐ ๐๐ฎ๐ธ๐ฒ๐ฎ๐๐ฎ๐๐: โฌ๏ธ
1. AI is not doing your job โ itโs helping you do it better
โ In 40% of conversations, the AI task and the userโs goal were completely different. People ask AI for help gathering, editing, summarizing. The AI responds by teaching and explaining. This is augmentation at scale.
2. Information work is the real frontier
โ The most common user goals? โGet informationโ and โWrite content.โ The most common AI actions? โProvide information,โ โTeach others,โ and โAdvise.โ
3. Jobs most affected are not just high-tech โ theyโre high-communication
โ Interpreters, historians, journalists, teachers, and customer service roles all scored high. Why? Because they involveย information, communication, and explanationย โ all things LLMs are good at.
4. AI canโt replace physical work โ and probably wonโt
โ The bottom of the list? Roofers, dishwashers, tractor operators. Manual jobs remain least impacted โ not because AI canโt help, but because it canโt reach.
5. Wage isnโt a strong predictor of AI exposure
โ Surprising: thereโs only a weak correlation (r=0.07) between average salary and AI applicability. In other words: this wave of AI cuts across income levels. Itโs not just a C-suite story.
6. Bachelorโs degree jobs are most exposed โ but not most replaced
โ Occupations requiring a degree show more AI overlap. But that doesnโt mean these jobs disappear โ it means they change. AI is refactoring knowledge work, not deleting.
This transformation is moving faster than most realize. The question isnโt whether AI will change how we work โ it already is.
Study in comments. โฌ๏ธ
๐ฃ.๐ฆ. ๐ ๐ฟ๐ฒ๐ฐ๐ฒ๐ป๐๐น๐ ๐น๐ฎ๐๐ป๐ฐ๐ต๐ฒ๐ฑ ๐ฎ ๐ป๐ฒ๐๐๐น๐ฒ๐๐๐ฒ๐ฟ ๐๐ต๐ฒ๐ฟ๐ฒ ๐ ๐๐ฟ๐ถ๐๐ฒ ๐ฎ๐ฏ๐ผ๐๐ ๐ฒ๐ ๐ฎ๐ฐ๐๐น๐ ๐๐ต๐ฒ๐๐ฒ ๐๐ต๐ถ๐ณ๐๐ ๐ฒ๐๐ฒ๐ฟ๐ ๐๐ฒ๐ฒ๐ธ โ ๐๐ ๐ฎ๐ด๐ฒ๐ป๐๐, ๐ฒ๐บ๐ฒ๐ฟ๐ด๐ถ๐ป๐ด ๐๐ผ๐ฟ๐ธ๐ณ๐น๐ผ๐๐, ๐ฎ๐ป๐ฑ ๐ต๐ผ๐ ๐๐ผ ๐๐๐ฎ๐ ๐ฎ๐ต๐ฒ๐ฎ๐ฑ: ๐ต๐๐๐ฝ๐://๐๐๐.๐ต๐๐บ๐ฎ๐ป๐ถ๐ป๐๐ต๐ฒ๐น๐ผ๐ผ๐ฝ.๐ผ๐ป๐น๐ถ๐ป๐ฒ/๐๐๐ฏ๐๐ฐ๐ฟ๐ถ๐ฏ๐ฒ | 21 comments on LinkedIn
Gartner: Over 40% of Agentic AI Projects Will Be Canceled by End 2027
Over 40% of agentic AI projects will be canceled by the end of 2027, due to escalating costs, unclear business value or inadequate risk controls, according to Gartner.
Since the launch of the L&D Maturity Model in March, Iโve been able to assess the collective maturity of the profession.
Since the launch of the L&D Maturity Model in March, Iโve been able to assess the collective maturity of the profession. Some results are surprising - and troubling. Here's a breakdown and my call to action for L&D leaders:
BACKGROUND
There are 7 themes in the L&D Maturity Model:
- Learning strategy
- Leadership alignment
- SME collaboration
- Learner engagement
- Learning needs identification
- Training processes
- Learning metrics
PROBLEM
Of these themes, L&D professionals have self-assessed their functions as the LEAST MATURE in:
- Learning needs identification
- Learner engagement
- Learning metrics
I'm not sure about you, but I see this as alarming because what this tells me is:
1. We donโt know if weโre working on the right things.
2. Learners donโt often engage.
3. Weโre not able to measure our impact.
The relationship between each of these is fundamental to the success of our function and yet our maturity is lowest on them.
SOLUTION
Imagine L&D was its own business for a moment.
If that was the case, we would see its critical path as:
1) Align on the biggest challenges
Before anything else, we need to ruthlessly align to the biggest challenges facing our organisation and our employees. No more assumptions, we need to validate with data and before we spend any time (let alone money, effort and credibility), we need to ensure our intake process is robust.
2) Quantify the challenges and determine what success looks like
Put metrics to the problems at the outset and determine what success weโre aiming for, i.e. bake measurement into the initial planning stage and then measure milestones towards it. If it canโt be quantified, donโt do it!
3) Engage learners like problem-solving partners
Help learners understand what's at stake and the role they play in the solution. Share the data with them, understand their lived experience and co-create alongside them and their more experienced peers and colleagues.
Anything other than this would be a wild swing, the business would burn money and weโd go out of business.
TAKEAWAY
L&D maturity isnโt taking what we're already doing and just doing it a little bit better.
It's about transforming what we're doing entirely.
Itโs about connecting with both the reason L&D should exist in the organisation and the possibilities that a mature and functioning department can bring.
We cannot stop at building an L&D storefront of generic 'solutions'.
L&D maturity starts with believing in more, creating a vision of a business aligned function, articulating the benefits and engaging all stakeholders.
This versus a shop front approach to L&D is a no-brainer. Often itโs our abilities to articulate the vision and sell it to stakeholders (including our own teams) thatโs holding us back.
More on that topic in the future.... | 65 comments on LinkedIn
๐๐๐๐๐ฟ๐ฒ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด โ ๐ช๐ฎ๐ ๐๐ถ๐ฟ๐ฑ ๐ฎ๐๐ ๐ฑ๐ฒ๐ป ๐ง๐ฟ๐ฎ๐ถ๐ป๐ฒ๐ฟ*๐ถ๐ป๐ป๐ฒ๐ป?
๐๐ช๐ฆ ๐๐ฐ๐ณ๐ด๐ต๐ฆ๐ญ๐ญ๐ถ๐ฏ๐จ๐ฆ๐ฏ ๐ท๐ฐ๐ฏ ๐ฆ๐ช๐ฏ๐ฆ๐ณ โบ๐๐ช๐ด๐ด๐ฆ๐ฏ๐ด๐ท๐ฆ๐ณ๐ฎ๐ช๐ต๐ต๐ญ๐ถ๐ฏ๐จโน ๐ช๐ฏ ๐ฅ๐ช๐ฆ ๐รถ๐ฑ๐ง๐ฆ ๐ฅ๐ฆ๐ณ ๐๐ช๐ต๐ข๐ณ๐ฃ๐ฆ๐ช๐ต๐ฆ๐ฏ๐ฅ๐ฆ๐ฏ ๐ฐ๐ฅ๐ฆ๐ณ ๐จ๐ข๐ณ ๐ฆ๐ช๐ฏ๐ฆ๐ณ โบ๐๐ฆ๐ณ๐ต๐ฆ- ๐ถ๐ฏ๐ฅ ๐๐ฐ๐ฎ๐ฑ๐ฆ๐ต๐ฆ๐ฏ๐ป๐ท๐ฆ๐ณ๐ฎ๐ช๐ต๐ต๐ญ๐ถ๐ฏ๐จโน ๐ช๐ฏ ๐๐ฆ๐ฎ๐ช๐ฏ๐ข๐ณ๐ฆ๐ฏ ๐ช๐ด๐ต ๐ฏ๐ข๐ค๐ฉ๐ธ๐ฆ๐ช๐ด๐ญ๐ช๐ค๐ฉ ๐ง๐ข๐ญ๐ด๐ค๐ฉ. ๐๐ญ๐ฆ๐ช๐ค๐ฉ๐ป๐ฆ๐ช๐ต๐ช๐จ ๐ฆ๐ณ๐ง๐ข๐ฉ๐ณ๐ฆ๐ฏ ๐ธ๐ช๐ณ, ๐ฅ๐ข๐ด๐ด ๐ด๐ฆ๐ญ๐ฃ๐ด๐ต๐ฐ๐ณ๐จ๐ข๐ฏ๐ช๐ด๐ช๐ฆ๐ณ๐ต๐ฆs ๐๐ฆ๐ฉ๐ณ๐ฆ๐ฏ ๐ช๐ฎ ๐๐ช๐ข๐ญ๐ฐ๐จ ๐ฎ๐ช๐ต ๐ฅ๐ฆ๐ณ ๐๐ ๐ช๐ฎ ๐๐ณ๐ฃ๐ฆ๐ช๐ต๐ด๐ฑ๐ณ๐ฐ๐ป๐ฆ๐ด๐ด ๐ฆ๐ณ๐ฉ๐ฆ๐ฃ๐ญ๐ช๐ค๐ฉ ๐ฆ๐ง๐ง๐ช๐ป๐ช๐ฆ๐ฏ๐ต๐ฆ๐ณ ๐ถ๐ฏ๐ฅ ๐ฏ๐ข๐ค๐ฉ๐ฉ๐ข๐ญ๐ต๐ช๐จ๐ฆ๐ณ ๐ช๐ด๐ต. ๐๐ฏ ๐ฅ๐ฆ๐ณ ๐๐ณ๐ข๐น๐ช๐ด ๐ฃ๐ฆ๐ฅ๐ฆ๐ถ๐ต๐ฆ๐ต ๐ฅ๐ช๐ฆ๐ด, ๐ฅ๐ข๐ด๐ด ๐ฅ๐ช๐ฆ ๐๐ฆ๐ณ๐ฏ๐ฆ๐ฏ๐ฅ๐ฆ๐ฏ ๐ฅ๐ช๐ฆ ๐๐ฆ๐ณ๐ข๐ฏ๐ต๐ธ๐ฐ๐ณ๐ต๐ถ๐ฏ๐จ ๐งรผ๐ณ ๐ช๐ฉ๐ณ ๐ฆ๐ช๐จ๐ฆ๐ฏ๐ฆ๐ด ๐๐ฆ๐ณ๐ฏ๐ฆ๐ฏ ๐ด๐ฆ๐ญ๐ฃ๐ด๐ต รผ๐ฃ๐ฆ๐ณ๐ฏ๐ฆ๐ฉ๐ฎ๐ฆ๐ฏ.
Dabei dรผrfen die Mitarbeitenden nicht allein gelassen werden. Sie benรถtigen die Flankierung von Lernbegleitenden.
๐๐ฒ๐ฟ๐ป๐ฏ๐ฒ๐ด๐น๐ฒ๐ถ๐๐ฒ๐ป๐ฑ๐ฒ ๐ฒ๐ฟ๐บรถ๐ด๐น๐ถ๐ฐ๐ต๐ฒ๐ป ๐๐ฒ๐น๐ฏ๐๐๐ผ๐ฟ๐ด๐ฎ๐ป๐ถ๐๐ถ๐ฒ๐ฟ๐๐ฒ ๐๐ฒ๐ฟ๐ป๐ฝ๐ฟ๐ผ๐๐ฒ๐๐๐ฒ d๐ฒ๐ฟ ๐๐ฒ๐ฟ๐ป๐ฒ๐ป๐ฑ๐ฒ๐ป ๐ถ๐บ ๐๐ฟ๐ฏ๐ฒ๐ถ๐๐๐ฝ๐ฟ๐ผ๐๐ฒ๐๐โ ๐ฝ๐ฒ๐ฟ๐๐ผ๐ป๐ฎ๐น๐ถ๐๐ถ๐ฒ๐ฟ๐, ๐ธ๐ผ๐น๐น๐ฎ๐ฏ๐ผ๐ฟ๐ฎ๐๐ถ๐ ๐๐ป๐ฑ ๐๐-๐๐ป๐๐ฒ๐ฟ๐๐๐๐๐๐.
In professionell begleiteten Lernprozessen steht die Entwicklung der Selbstorganisationsfรคhigkeit im Vordergrund. Daraus ergibt sich folgendes ๐๐๐ณ๐ด๐ฎ๐ฏ๐ฒ๐ป๐ฝ๐ฟ๐ผ๐ณ๐ถ๐น:
๐ญ. ๐ฆ๐ฒ๐น๐ฏ๐๐๐ผ๐ฟ๐ด๐ฎ๐ป๐ถ๐๐ถ๐ฒ๐ฟ๐๐ฒ๐ ๐๐ฒ๐ฟ๐ป๐ฒ๐ป ๐ฒ๐ฟ๐บรถ๐ด๐น๐ถ๐ฐ๐ต๐ฒ๐ป
Gemeinsam mit Learning & Development wird laufend der Ermรถglichungsrahmen fรผr selbstorganisiertes Lernen โ Learning Experience Platform โ weiterentwickelt.
๐ฎ. ๐ฃ๐ผ๐๐ถ๐๐ถ๐ผ๐ป๐๐ธ๐นรค๐ฟ๐๐ป๐ด
Gemeinsam werden regelmรครig die aktuellen Herausforderungen reflektiert, die beruflichen Ziele geklรคrt und evtl. die Skills-Diagnostik eingefรผhrt.
๐ฏ. ๐๐-๐ฏ๐ฎ๐๐ถ๐ฒ๐ฟ๐๐ฒ ๐ฆ๐ธ๐ถ๐น๐น๐-๐๐ถ๐ฎ๐ด๐ป๐ผ๐๐๐ถ๐ธ
Die Lernenden diagnostizieren ihre Skills eigenverantwortlich und planen ihr Lernen selbstorganisiert.ย Die Lernbegleitenden unterstรผtzen bei Bedarf dabei, die Lernpfade zu strukturieren, Prioritรคten zu setzen und eigenstรคndig Entscheidungen zum Lernprozess zu treffen.
๐ฐ. ๐๐ฒ๐ฟ๐ป๐ฏ๐ฒ๐ด๐น๐ฒ๐ถ๐๐๐ป๐ด ๐ฎ๐๐ณ ๐๐๐ด๐ฒ๐ป๐ตรถ๐ต๐ฒ
Die Lernbegleitenden fรถrdern die Selbstorganisation, geben konstruktives Feedback sowie Impulse und bieten Reflexionsrรคume.
๐ฑ. ๐ก๐ฒ๐๐๐๐ฒ๐ฟ๐ธ๐ฒ ๐ฎ๐๐ณ๐ฏ๐ฎ๐๐ฒ๐ป ๐๐ป๐ฑ ๐ฝ๐ณ๐น๐ฒ๐ด๐ฒ๐ป
Lernbegleitende unterstรผtzen beim Aufbau von Lerngemeinschaften.
๐๐ป๐ณ๐ผ๐ฟ๐ฑ๐ฒ๐ฟ๐๐ป๐ด๐ฒ๐ป ๐ฎ๐ป ๐๐ฒ๐ฟ๐ป๐ฏ๐ฒ๐ด๐น๐ฒ๐ถ๐๐ฒ๐ป๐ฑ๐ฒ
Neben fachlich-methodischer und konzeptioneller Expertise benรถtigen Lernbegleitende die Kompetenz zum werteorientierten, fรถrdernden und impulsgebenden Handeln mit hoher Expertise. Deshalb ist der gezielte, praxisbezogene Skillsaufbau der heutigen Trainer*innen fรผr Future Learning erforderlich.
๐ฆ๐ฝ๐ฟ๐ฒ๐ฐ๐ต๐ฒ๐ป ๐ฆ๐ถ๐ฒ ๐บ๐ถ๐ ๐๐ป๐ รผ๐ฏ๐ฒ๐ฟ ๐ฑ๐ถ๐ฒ ๐๐ผ๐บ๐ฝ๐ฒ๐๐ฒ๐ป๐๐ฒ๐ป๐๐๐ถ๐ฐ๐ธ๐น๐๐ป๐ด ๐๐๐บ/๐ฟ ๐ญ๐ฒ๐ฟ๐. ๐ฆ๐ธ๐ถ๐น๐น๐๐บ๐ฎ๐ป๐ฎ๐ด๐ฒ๐ฟ*๐ถ๐ป
"Stakeholder Management in der betrieblichen Bildung"
Groร Lindow, Juli 2025 - Der Bildungs-Stakeholder "Betriebsrat" nimmt eine zentrale Rolle ein, wenn es um Compliance im Unternehmen geht. Der Betriebsrat verfรผgt nรคmlich รผber ein gesetzlich verankertes Mitbestimmungsrecht bei allen Maรnahmen, die compliance-relevante Aspekte betreffen โ etwa Regelungen zum Datenschutz oder zur Leistungs- und Verhaltenskontrolle. Und da mittlerweile nahezu jedes IT-System, jedes Tool oder jede Anwendung โ insbesondere solche mit KI-Funktionalitรคten โ personenbezogene Daten erhebt und verwendet, ist es nachvollziehbar, dass der Betriebsrat in diesen Zeiten stark gefordert ist.
» MEHR
If I could wave a magic wand over Learning & Development, Iโd remove one thing.
If I could wave a magic wand over Learning & Development, Iโd remove one thing. One thing that would immediately improve everything from our impact to our efficiency.
That one thing would be: Everybodyโs expectations of what L&D is supposed to do.
And I mean everybodyโฆ
Senior leaders
Line managers
The workforce
HR
And yes, even us in L&D
Because the biggest barrier to impactful Learning & Development isnโt budget, bandwidth or buy-inโฆ
Itโs the baggage.
Weโre carrying around decades of assumptions about what L&D should look like that have very little to do with actually improving performance or closing skills gaps.
If we could hit reset and define our role from scratch weโd operate very differently. Weโd prioritise:
- Support over solutions
- Performance over participation
- Outcomes over optics
But we donโt, because everyone thinks they know what L&D should be.
And thatโs whatโs holding us back.
So hereโs the real challenge:
Can we slowly but surely rewrite the narrative starting with how we talk about both: what we do and the value we bring?
Thoughts? | 30 comments on LinkedIn
Druckfrisch aus dem Weissen Haus: Der AI Action Plan der USA. "WINNING THE RACE" ist die Ansage. Ich bin mal sehr gespannt auf die Europรคische Antwort. Mein GPT sagt dazu ganz wertfrei:
Druckfrisch aus dem Weissen Haus: Der AI Action Plan der USA.
"WINNING THE RACE" ist die Ansage.
Ich bin mal sehr gespannt auf die Europรคische Antwort.
Mein GPT sagt dazu ganz wertfrei:
"Wird 2025 zum Jahr der globalen AI-Doktrin?
Mit dem 28-seitigen โAmericaโs AI Action Planโ legt die Trump-Administration ein kompromisslos ambitioniertes Strategiepapier vor โ ein geopolitisches Manifest fรผr technologische Vorherrschaft, das Innovation, Infrastruktur und Diplomatie radikal neu denkt.
Ziel: globale AI-Dominanz. Kein โKรถnnteโ, kein โSollteโ. Sondern ein โWirdโ โ mit einer Regierung, die AI als Schlรผssel zur wirtschaftlichen, militรคrischen und kulturellen Zukunft Amerikas versteht. Das Dokument ruft eine neue industrielle Revolution, eine Informationsrevolution und eine digitale Renaissance gleichzeitig aus.
Der Plan umfasst:
_
โข Deregulierung und Priorisierung von Open-Source-Modellen
โข Milliarden-Investitionen in Halbleiter, Cloud-Infrastruktur, Energie und AI-Forschung
โข staatlich gefรถrderte AI-Sandboxes fรผr Healthcare, Bildung, Verteidigung und Industrie
โข nationale Reallabore, Skills-Offensiven und beschleunigte Adoption im รถffentlichen Sektor
โข Exportoffensive fรผr ein โAmerican AI Stackโ โ Hardware, Modelle, Standards
โข strikte Exportkontrollen und diplomatische Isolierung Chinas in Governance-Gremien
โข Cyber- und Biosecurity-Maรnahmen gegen Missbrauch von Frontier-Modellen
โข juristische Anpassung zur Bekรคmpfung von Deepfakes und synthetischer Evidenz
Bemerkenswert ist der offen geopolitische Ton: Die USA verstehen sich wieder als Gestalter einer neuen Weltordnung - mit AI als Hebel.
Wer das Rennen macht, schreibt die Regeln.
Fรผr Europa stellt sich damit dringender denn je die Frage: Wollen wir nur regulieren - oder auch gestalten?"
Quelle: https://lnkd.in/eXwTUGzv
The social signals behind employee retention "Research has long shown that employees at the center of an organizational networkโthose with many active connectionsโare 24 percent less likely to leave."
The social signals behind employee retention
"Research has long shown that employees at the center of an organizational networkโthose with many active connectionsโare 24 percent less likely to leave."
๐ค Michael Arena and Aaron Chasan highlight an important insight: employee connection, not just engagement, is the true bedrock of retention: ๐ โIn todayโs networked workplace, social withdrawal is often the firstโand most reliableโindicator that someoneโs already halfway out the door.โ
For HR to genuinely impact business performance and employee experience, we must leverage social signals to build robust internal networks.
Michael and Aaron outline four high-impact ways HR can proactively employee connection and significantly reduce attrition:
๐ Utilise network analysis: Identify early flight risks by spotting employees with few or declining connections.
๐ Facilitate connection moments: Deliberately create opportunities for interaction, especially in hybrid settings, using tools like interest-based matching.
๐ Support relationship-rich teams: Encourage cross-functional initiatives and invest in psychologically safe team cultures.
๐ Routinely pulse central employees: Their engagement profoundly influences the entire network.
"In todayโs networked workplace, social withdrawal is often the firstโand most reliableโindicator that someoneโs already halfway out the door."
๐ This report is featured in the June edition of the Data Driven HR Monthly, which you can access here: https://lnkd.in/exEqY-Hn ๐
#humanresources #organizationalnetworkanalysis #peopleanalytics #leadership #culture #socialcapital | 18 comments on LinkedIn
I was recently looking at how Gen AI shapes and potentially impacts cognitive skills - a topic that matters for education and for work. Here are a few resources I reviewed.
I was recently looking at how Gen AI shapes and potentially impacts cognitive skills - a topic that matters for education and for work.
Here are a few resources I reviewed.
1๏ธโฃ Your Brain on ChatGPT - What Really Happens When Students Use AI
MITย releasedย a study on AI and learning. Findings indicate that students who used ChatGPT for essays showed weaker brain activity, couldn't remember what they'd written, and got worse at thinking over time
https://shorturl.at/qaLie
2๏ธโฃ Cognitive Debt when using AI - Your brain on Chat GPT
There is a cognitive cost of using an LLM vs Search Engine vs our brain in e.g. writing an essay. The study indicates that there is a likely decrease in learning skills, the more we use technology as substantial replacement of our cognitive skills.
https://lnkd.in/drVa_YNg
3๏ธโฃ Teachers warn AI is impacting students' critical thinking
One of many articles about the importance of using Gen AI smartly, in Education but also at work.
https://lnkd.in/dSbGjusu
4๏ธโฃ The Impact of Gen AI on critical thinking
Another interesting study on the same topic.
https://shorturl.at/74OO6
5๏ธโฃ Doctored photographs create false memories
In psychology, research indicated a long time ago that our memory -ย our recollection of past events - is susceptible to errors, biases, can be fragmentary, contain incorrect details, and, oftentimes, be entirely fictional. Memories are a reconstruction of our past to respond to our need for coherence in life.
A rigorous 2023 study shows that doctored photographs โ think Photoshop or today, AI โ create false memories. Why it matters? Memory is essential for learning, recall of episodical and factual happenings, and itโs a basis for the integrity of sources of truth in organizations. ย
https://shorturl.at/hdgtN
6๏ธโฃ The decline of our thinking skills
Another great article on AI and critical thinking from IE University.
https://shorturl.at/rGl99
7๏ธโฃ Context Engineering
Ethan Mollick recently wrote a blog on "context engineering" - how we give AI the data and information it needs to generate relevant output. The comments on the post were even more interesting than the post itself. Personally I think that good part of context engineering is not in organizations documents or processes, it is in peoples ability to think critically and understand relevant parameters of their environment to nurture AI/Gen AI. Gotta follow up on this one ;-)
https://shorturl.at/sfnuV
#GenAI #CriticalThinking #AICognition #AIHuman #ContextEngineering | 29 comments on LinkedIn
Upskilling in the AI era is fundamental for every company regardless of size and is often viewed as a necessary business investment. Additionally, many companies connect workforce upskilling to business functions (operations, manufacturing, legal, etc.
I have commented in my newsletter that what people have been describing as 'ethical AI principles' actually represents a specific political agenda, and not an ethical agenda at all. In this post, I'll outline some ethical principles and work my way through them to make my point.
EY just broke the biggest lie in corporate learning.
EY just broke the biggest lie in corporate learning.
They trained 44,000 employees internally. Then launched an AI Academy using 200 real-world use cases. The result? 50+ actual AI projects launched across five enterprises. Plus leadership-driven AI manifestos.
That's the story I shared recently.
It got more reactions and shares than anything I've posted.
The support:
โณ Those who liked and shared it
โณ "We're already doing this approach"
โณ "This is exactly what we want to implement"
But what I liked the most is how the experts responded.
The pushback:
โณ "50 projects means nothing without context"
โณ "What about the projects that failed?"
โณ "Where's your control group?"
โณ "This sounds like survivor bias"
โณ "Did you measure actual skill transfer?"
โณ "Will this work for topics other than AI?"
โณ "Correlation isn't causation"
Fair points. All of them.
But here's what I'm doubling down on:
We're measuring the wrong damn things.
L&D isn't in the learning business. We're in the building business.
L&D's focus should be simple:
โณ What solutions can our people build?
Our measurement strategy should be reimagined around that core ability.
Not:
โณ Did they complete the course?
โณ Did they pass the quiz?
โณ Did they like the content?
While we debate attribution methodology:
โณ 97% of enterprises still cite talent gaps
โณ $366B spent annually on corporate training
โณ Minimal business impact to show for it
The uncomfortable truth?
Perfect measurement of learning consumption โ Performance change
EY's numbers might be messy.
โณ Their attribution might be flawed.
โณ Their methodology might be incomplete.
But they're asking the right question:
"What did people actually build?"
The experts want rigor. I want it too.
But let's get rigorous about what matters:
โณ Solutions created
โณ Problems solved
โณ Value delivered
I'm building a coalition of L&D leaders ready to abandon traditional metrics.
If you're already measuring "what people build" - I want to hear your story.
If you're ready to start - let's connect and figure this out together.
Who's in?
[Check out my original post and the expert responses - link in comments]
#WorkplaceLearning #LearningAndDevelopment #PerformanceSupport #ReimagineLND
๐ Resonates? Share itโlet's reimagine L&D together!
โ Follow me, Santhosh Kumar, for unconventional insights that challenge how we lead and learn.
Reifegrad der Personalentwicklung mit dem Modell von 360learning messen
๐ Welchen Reifegrad hat eure L&D-Arbeit? Wo steht ihr und wie kรถnnt ihr euch gezielt weiterentwickeln? ๐กIn diesem Video stelle ich euch das L&D-Reifegradmo...
Reifegrad der Personalentwicklung mit dem Modell von 360learning messen
๐ Welchen Reifegrad hat eure L&D-Arbeit? Wo steht ihr und wie kรถnnt ihr euch gezielt weiterentwickeln? ๐กIn diesem Video stelle ich euch das L&D-Reifegradmo...
L&D isnโt very happy with their LMS platforms, thatโs for sure ๐ฅฒ
L&Ds aren't very happy with their LMS platforms, that's for sure ๐ฅฒ
We recently launched our first tools report, and below ๐๐ป you can find 7 insights around LMSs & LXPs.
Want to read more?
๏ผ Download the free report ๐ https://lnkd.in/dBZzW6TZ
๏ผ Join the Offbeat Fellowship to explore all our insights ๐ https://lnkd.in/dx3REqBh
Hope you'll find this useful! ๐
#learninganddevelopment #learningmanagementsystem #learningexperienceplatform #learningtools