Data Science Society’s Post

95% of companies spend billions on AI. They get nothing back. MIT tracked 300 projects to find out why the math doesn't work. The results are sobering. Enterprise spending on generative AI hits $30-40 billion annually. Yet 95% of AI initiatives deliver zero measurable business value. Zero. The MIT study reveals a harsh truth. It's not about model size or compute power. It's about execution. The "GenAI Divide" shows: • Only 5% of AI projects generate rapid revenue gains • Legacy enterprises consistently underperform startups • Organizational readiness matters more than technology specs • Most companies see productivity dips after AI adoption Startups are winning this race. They build AI-ready processes from scratch. They align technology with workflows. They focus on single, specific use cases. One startup went from zero to $20 million in revenue within a year. Not because they used bigger models. Because they executed better. Large enterprises throw money at compute-heavy solutions. They skip the foundation work. They ignore workflow integration. They wonder why AI fails to deliver. The research suggests a shift is coming. Algorithmic efficiency gains will soon outpace brute-force compute scaling. Smaller, targeted models will compete with massive ones. This isn't about anti-AI sentiment. It's about smart AI deployment. Success factors include: • Strategic governance frameworks • Workflow alignment • Organizational preparedness • Measurable outcome tracking The companies winning with AI aren't using the biggest models. They're using the right approach. What's your experience with AI implementation? Are you seeing real returns or just hype? #AI #ArtificialIntelligence #BusinessStrategy 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/em4KQ75Q

95% of companies spend billions on AI. They get nothing back. MIT tracked 300 projects to find out why the math doesn't work. The results are sobering. Enterprise spending on generative AI hits $30-40 billion annually. Yet 95% of AI initiatives deliver zero measurable business value. Zero. The MIT study reveals a harsh truth. It's not about model size or compute power. It's about execution. The "GenAI Divide" shows: • Only 5% of AI projects generate rapid revenue gains • Legacy enterprises consistently underperform startups • Organizational readiness matters more than technology specs • Most companies see productivity dips after AI adoption Startups are winning this race. They build AI-ready processes from scratch. They align technology with workflows. They focus on single, specific use cases. One startup went from zero to $20 million in revenue within a year. Not because they used bigger models. Because they executed better. Large enterprises throw money at compute-heavy solutions. They skip the foundation work. They ignore workflow integration. They wonder why AI fails to deliver. The research suggests a shift is coming. Algorithmic efficiency gains will soon outpace brute-force compute scaling. Smaller, targeted models will compete with massive ones. This isn't about anti-AI sentiment. It's about smart AI deployment. Success factors include: • Strategic governance frameworks • Workflow alignment • Organizational preparedness • Measurable outcome tracking The companies winning with AI aren't using the biggest models. They're using the right approach. What's your experience with AI implementation? Are you seeing real returns or just hype? #AI #ArtificialIntelligence #BusinessStrategy 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/dk-kGkbv

95% of companies spend billions on AI. They get nothing back. MIT tracked 300 projects to find out why the math doesn't work. The results are sobering. Enterprise spending on generative AI hits $30-40 billion annually. Yet 95% of AI initiatives deliver zero measurable business value. Zero. The MIT study reveals a harsh truth. It's not about model size or compute power. It's about execution. The "GenAI Divide" shows: • Only 5% of AI projects generate rapid revenue gains • Legacy enterprises consistently underperform startups • Organizational readiness matters more than technology specs • Most companies see productivity dips after AI adoption Startups are winning this race. They build AI-ready processes from scratch. They align technology with workflows. They focus on single, specific use cases. One startup went from zero to $20 million in revenue within a year. Not because they used bigger models. Because they executed better. Large enterprises throw money at compute-heavy solutions. They skip the foundation work. They ignore workflow integration. They wonder why AI fails to deliver. The research suggests a shift is coming. Algorithmic efficiency gains will soon outpace brute-force compute scaling. Smaller, targeted models will compete with massive ones. This isn't about anti-AI sentiment. It's about smart AI deployment. Success factors include: • Strategic governance frameworks • Workflow alignment • Organizational preparedness • Measurable outcome tracking The companies winning with AI aren't using the biggest models. They're using the right approach. What's your experience with AI implementation? Are you seeing real returns or just hype? #AI #ArtificialIntelligence #BusinessStrategy 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/d5N2HHNa

AI startups are taking control of their data, investing in proprietary datasets to enhance model performance and gain a competitive edge. Link: https://lnkd.in/di2CpuPe #AI #Data #Startups #Innovation #Technology #Models #Performance #Edge #Proprietary #Investment #Growth #Development #Future #Digital #Intelligence #Analytics #Trends #Leadership #Strategy #Success

🧨 Is Generative AI a Bubble? Let’s Talk Facts. 🧨 GenAI is everywhere—apps, startups, job titles, even toothbrushes. But behind the buzz, some serious questions are being asked: Is this hype sustainable? Or are we heading for a correction? Here are 5 signs that GenAI might be overinflated: 1️⃣ Too much money, too little profit Thousands of GenAI startups have huge valuations, but very few are profitable. OpenAI reportedly spent $9.7B in just six months. 🔗 https://lnkd.in/dWg-jJyU 2️⃣ Massive energy and water use AI data centers are consuming more power than some countries. Water usage is also becoming a concern. 🔗 https://lnkd.in/dz9Cppt5 3️⃣ Most pilots don’t scale Enterprises love experimenting with GenAI, but 95% of pilots fail to go live. 🔗 https://lnkd.in/dE-WcN8V 4️⃣ Losing money per user Many GenAI platforms spend more to serve users than they earn. That’s not sustainable. 🔗 Scott Logic: GenAI sustainability review 5️⃣ Regulators are watching Governments and watchdogs are raising concerns about data privacy, misinformation, and monopolies. 🔗 FTC: GenAI competition concerns 💬 GenAI is powerful—but it’s not magic. We need to ask hard questions, build responsibly, and focus on real value. What do you think—is GenAI a bubble, or just early-stage chaos? #GenAI #AIHype #TechBubble #AIRealityCheck #DigitalTrends #AIInvesting #SustainableTech #AIRegulation #FutureOfAI #LinkedInTech

Early-stage startups beware! Not every AI feature is a win. Learn why the AI feature trap can waste resources—and when AI truly adds value. Via Alan Gold https://hubs.la/Q03PRCr10

The Agentic AI Boom: Inside Tech’s Next Big Race 🏇 The machines are no longer just answering questions—they’re making decisions. A new wave of agentic AI models is reshaping what it means for technology to “assist” us, blurring the line between tool and teammate. 👩💻 From managing workflows to booking flights and even writing code that writes more code, agentic AI marks a turning point: intelligence that acts, not just reacts. 🧠 Sectors like Life Science and Healthcare are some of the fastest growing data segments and stand to benefit exponentially from the rise of Agentic AI. 👩⚕️ See our latest article --> https://lnkd.in/dXvbzjqZ

Agentic AI heralds a new era where machines evolve beyond mere responders to become proactive thinkers, planners, and actors, turning tools into independent collaborators. Explore more on this transformative technology in our latest article: (https://lnkd.in/dM8rV8tw).

⚡Scavenger AI Raises €2.5M Seed to Bring Enterprise-Grade AI Analytics to Europe’s Mid-Market Frankfurt–based Scavenger AI, a software company redefining business intelligence for Europe’s SMEs, has raised €2.5 million in Seed funding to accelerate product development and expand across the continent. 🔹 Leads: BMH Beteiligungs-Management Hessen 🔹 Participants: xdeck, HTGF | High-Tech Gründerfonds, Calm/Storm Ventures Founded by: Felix Beissel and Maximilian Hahnenkamp What Scavenger AI Does: Scavenger AI is building the next generation of business intelligence—a platform that lets users query company data in natural language, no dashboards or code required. Its proprietary semantic layer transforms complex datasets into clear, reproducible analyses, empowering decision-making across teams. ⚙️ Tech & Compliance Edge: – Fully GDPR-compliant and hosted entirely in Europe – Serves leading mid-sized companies across Sales, Controlling, and Production – Focused on making enterprise-grade analytics accessible to every SME 🌎 What’s Next: Funds will accelerate AI product development, strengthen European market presence, and push toward a future where every business can act on data as intuitively as asking a question. PS: Repost & follow 👉 Future Techly for more on European AI innovation, business intelligence, and data-driven transformation. ------------ Graphic Created By Muhammad Asad

“Stop sprinkling AI on top — start building with it at the core.” Most companies treat AI solutions like a plugin, something you bolt on after the fact. At AutomateMe, we’ve learned that real efficiency doesn’t come from adding automations later. It comes from building with AI and Automations from day one. When automation is built into your foundation not slapped on as a fix , everything changes: • Workflows optimize themselves. • Teams focus on strategy, not repetition. • Speed and clarity become the default, not the exception. We’ve seen it firsthand startups that integrate AI at the core are scaling faster, making smarter decisions, and are turning chaos into momentum. Don’t ask, “Where can we use AI?” Ask, “What does our company look like when AI powers every layer of it?” Because when you build with AI from the ground up, you don’t just automate tasks, 𝐘𝐨𝐮 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐆𝐫𝐨𝐰𝐭𝐡. #AIFirst #AutomationStrategy #AITransformation #BuildWithAI #ScaleWithAI