LinkedIn's Economic Graph reposted this
On LinkedIn, we’ve seen an 82% rise in the number of professionals posting about feeling overwhelmed, alongside a 23% increase in AI-related conversations globally. These signals reveal a growing divide: As the new technology progresses quickly, many professionals are struggling to keep up. The current pace of change is undeniable, and it’s reshaping how people work and businesses grow. But here’s what’s striking: nearly 80% of professionals say their most trusted source of insight isn’t a tool—it’s their network. More details on trends we're seeing across LinkedIn in my article below.
Geri Maroney
1d
Great article, Karin! I think the pace of change is clearly having an impact. Nothing beats a great network, and now more than ever, business professionals should rely on the collective strength of their community. 👍
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Kailas Datir
9h
Dear, AI is a complement for human users, it works on command based input and supports us, rather than replacing the human element. Networking, in contrast, isn’t built by AI, but by social character, trust, and shared human experience. Please don’t take this as criticism of the data you shared. I just wonder given LinkedIn’s scale and how representative the sample size is when drawing such broad conclusions. I honestly appreciate your expertise and the valuable insights you bring to this field.
Sometimes the best way to navigate the AI storm is with a compass from your network. This one pointed me in the right direction. 🧭 👉 https://shorturl.at/tcZ3l
Many leaders are still struggling with how to integrate AI for content creation or other purpose. I was too. That’s why I created the STAR(T) framework: To help leaders figure out what questions to ask and to identify the right entry point for their team. S – Spot the Right Entry Point: Find high-pain, low-risk tasks + get governance approval early T – Test with Small Stakes: Start with volunteers who want to experiment + document failures A – Audit What Actually Works: Measure impact honestly + build integration requirements: Measure impact honestly + build integration requirements R – Refine and Scale Systematically: Fix integration issues + train more people + set boundaries T – Transform Culture Through Success: Roll out in waves + support reluctant users + keep measuring ROI It's built for content teams, but flexible enough to scale across functions. And easy enough to apply for other purposes as well. Remember to keep it simple. Start small. Read my post to learn more:
AI is exhausting, technology is a constant, and people are paying WAY less attention to details as they were in 2015. Never a better time to learn, educate, and take practical steps to simplify the load of the future.
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Brian Carter
19h
Depends on network. If you are not constantly gaining new skills. No one can brief you. Especially if you're stuck in the 2000's. Tech changes every 3-6 months. I outgrew my network while re-skilling.
Marc Monteil
9h
Tech keeps accelerating, but people still turn to their network first not tools. Maybe that’s the real signal: trust travels faster in relationships than in algorithms. Karin Kimbrough , do you see that trust gap widening or narrowing with AI?
Helping HR pros develop AI skills & drive people-first tech adoption | AI for HR Mastermind | Workplace Labs | Organizational Psychologist
14mFinding signals relevant to your job is the best strategy for navigating the news cycle and overcoming overwhelm. These signals come from joining a trusted group of like-minded professionals who are figuring out how to adopt AI together.