Unpopular opinion: Most businesses are using AI entirely wrong by trying to replace their best people. The real magic happens when you stop treating AI as a replacement and start using it to automate the 80% of repetitive tasks that burn your top talent out. What is one task you do every day that you wish could be handled by a digital twin?
AI Automation for Repetitive Tasks Not Replacing Top Talent
This title was summarized by AI from the post below.
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There's nothing as exciting as a shiny new AI tool or pilot. But the reality is, what really contributes to successful AI adoption involves a [bleep!] ton of change management. I love how our experts break this down, as they've seen the pitfalls mentioned here come to life over and over again. They've identified some of the most common patterns in hopes that you, too, will be as successful as possible: https://ow.ly/KLf150Z5mVy
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Mathew providing us with the numbers behind AI usage in #GlobalMobility. Check out the link to K2 Group's guide to using AI while maintaining that human touch. Appreciate the information, mate!
Marketing Executive (Global Mobility) | Relocation & Talent Mobility Marketing | Demand & Lead Gen | K2 Group - NPS 82 | Great Place to Work® Certified
AI in global mobility shouldn’t be about removing people. It should be about helping us show up better for them. If you’re exploring AI right now, this guide from K2 Group is a useful starting point, including where AI already fits, where human judgement stays critical, and a simple framework to evaluate opportunities responsibly. Download: https://lnkd.in/eHBphHaQ What’s one mobility touchpoint you wouldn’t want to automate?
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AI incidents aren’t business as usual. When something goes wrong, it’s not just about containment — it’s about understanding how the model failed, correcting it, and keeping operations moving. As AI becomes embedded in everyday decisions, preparedness matters just as much as adoption. 👉 Read our article to explore what effective AI incident response really looks like: https://okt.to/T8dxrj
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The single biggest jump in AI output quality is not a better model. It's centralizing what you know about yourself, your projects, your products, your processes, your writing style in a real knowledge system; then pointing AI at it. That is Level 5 of context management. The curve goes vertical right there. Even 100 well-structured notes about you and your work changes everything. https://lnkd.in/euC5B2T2
Levels of AI Context Management: From Generic Answers to Precision Results
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Looking to reinvent through AI? Check out this great article https://lnkd.in/gWzS72wJ by Farbod Nassiri, P.Eng on the workforce considerations along the way.
The biggest risk in AI right now isn't moving too fast. It's thinking incrementally. Organizations are investing in strategy, governance, and agents and then wondering why the returns haven't shown up. The pattern is consistent: the winners aren't the ones with the best models. They're the ones rewiring the work itself! My recent article goes deeper into different stages of embracing AI at work, and how to move from PoCs to Agentic Functional Model Reinvention and beyond. Read the article: https://lnkd.in/eKebpZgZ
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Some helpful perspective from Farbod on what many organizations are beginning to recognize: the future of work isn't about choosing between people and AI, but designing an operating model where both can contribute their unique strengths. The organizations that get this balance right will be best positioned to drive innovation, productivity, and long-term value.
The biggest risk in AI right now isn't moving too fast. It's thinking incrementally. Organizations are investing in strategy, governance, and agents and then wondering why the returns haven't shown up. The pattern is consistent: the winners aren't the ones with the best models. They're the ones rewiring the work itself! My recent article goes deeper into different stages of embracing AI at work, and how to move from PoCs to Agentic Functional Model Reinvention and beyond. Read the article: https://lnkd.in/eKebpZgZ
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The biggest risk in AI right now isn't moving too fast. It's thinking incrementally. Organizations are investing in strategy, governance, and agents and then wondering why the returns haven't shown up. The pattern is consistent: the winners aren't the ones with the best models. They're the ones rewiring the work itself! My recent article goes deeper into different stages of embracing AI at work, and how to move from PoCs to Agentic Functional Model Reinvention and beyond. Read the article: https://lnkd.in/eKebpZgZ
