Niklas Jansen’s Post

79% of AI companies use “AI-powered” in their positioning and messaging and that’s cray. (something like 79%, maybe, pretty sure) It’s too bad bc they could be using other words and phrases to say it differently and simply. For example: - Computer that learns - Tech that thinks - Brainy robot assistant - Computer with a brain - Thinking machine "AI-powered" is overused corporate jargon. we can do better But you know what would be even better? Doing voice of customer research. I bet your customers wouldn’t say “AI-powered” when they talk about you That’s just strange Maybe they’d say brainy robot assistant I don’t know You don’t know either until you do the research Find out, and say it simply so people understand ✌️&❤️️ #marketing #startups #founders

#DisruptiveTech Technology Magazine considers some of the leading technology startup companies that are committed to accelerating global business innovation. As technologies like artificial intelligence (AI) and cloud-based services continue to digitally transform businesses, there is greater demand for services around the world. This has led to an increase in startup companies emerging, with big tech companies continuing to pump money into new innovation to remain competitive in a rapidly changing industry. These startups are often successful, as they are adept at leveraging disruptive technologies to expand quickly and handle increasing demands. #startups #ai #digitaltransformation #innovation #technology Campaign Catapult, Pravo Consulting

Great post by Scott Beechuk, Bayan Alizadeh, and the great folks at Norwest Venture Partners on the promising future and potential pitfalls of autonomous AI agents in the enterprise. https://lnkd.in/gfqNTB8A From where I sit, the agentic future looks very bright. Yes, there are real-world issues, ranging from hallucinations and bad decision-making to talent gaps. But...the promise of faster, cheaper, and safer business process execution is simply impossible to ignore. It's going to be fun to watch, but I think the innovators will win the day. They are the people and companies who are creating this agent-centric future as I write this post. So buckle-up. It may be a bumpy ride for a while. But in the end, I see a world full of enterprise AI agents that perform increasingly complex tasks with a degree of accuracy and efficiency the world has never seen.

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The first wave of AI products at application layer is over. Most went for low hanging fruits - fancy toys that failed to deliver enough value for end users to excite them and drive substantial adoption. 2025 will be about humanoids and robots. From a commercial adoption point of view, this world is much more blueocean! For software AI companies - 2025 will be year of consolidation. Most startups that failed to get descent traction (which is 99% of market) will shut down. good chunk of 1% will get acquired What do you think? comment below #ai #2025

I’m a hands-on learner. If I don’t try something, it’s hard for me to envision it solving a real problem. Same for AI. I just built my first agent in Copilot Studio this week (I’m behind, I know). Because of that, I feel like I have so many more ideas of where AI would fit in my life. If you’re a business owner or decision maker, struggling to identify or prioritize AI use cases. Test some stuff. Build some things. Have some fun with it. You might gain some clarity. It helped me. It might help you. #ai #startup #enterprise #agent

What people miss on their Journey Building AI Products? #BuildinPublic After multiple interactions with amazing people building cutting edge companies in the AI space, across the spectra and learning from both their successes and setbacks, I've noticed a few crucial patterns: We often get caught up in the technical brilliance while missing the human element, which many startups did as well. In my experience, it's not just about the models or the accuracy scores. The real magic happens when you: 1. Start with the pain point, not the solution: I've learned (sometimes the hard way) that falling in love with the technology instead of the problem is a recipe for building something nobody wants, which is way too common nowadays. 2. Embrace the messy middle: The gap between a working model and a valuable product is where most teams struggle. Data quality, user feedback loops, and edge cases aren't glamorous, but they're where the startup battle is won. 3. Focus on trust-building: Your users don't care about your model architecture. They care about feeling safe, understood, and in control. I'm reminded daily: the best AI products don't just work well - they make users feel empowered. What lessons have you learned in your AI journey? Drop your insights below 👇 #ArtificialIntelligence #ProductDevelopment #TechLeadership #startups #BusinessStrategy

While it seems we are already on the receding end of the AI hype, speculation precedes real change by a large margin because it takes time to develop the technology and even more time for it to get wide-scale adoption. Consequently, exploring in which sectors AI could have a real-world impact is still a worthwhile exercise. Having a good understanding of where AI could make the biggest difference is crucial for early-stage startup founders who want to take advantage of the availability of startup funding for AI projects.

𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗠𝘆𝘁𝗵𝘀! 💡 𝗠𝘆𝘁𝗵: "Automation will replace jobs." ✅ 𝗙𝗮𝗰𝘁: Automation helps teams focus on creative and strategic tasks, not repetitive ones. It’s not humans vs. AI—it’s humans with AI. #Automation #TechWithGrit #FutureOfWork #Processes #Startups #AI #HubSpot

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