Gerben Blom’s Post

20 strategies to make AI faster, leaner and more effective — from quantization to federated learning to orchestration. What stood out most to me? The insight from Charles Crouchman, Chief Product Officer at Redwood Software: without unifying automation tools and processes, AI gets stuck managing silos instead of delivering outcomes. The question isn’t just “How do we make AI smarter?” It’s “How do we clear the path for AI to perform at its best?” #AI #Automation #DataDriven

20 strategies to make AI faster, leaner and more effective — from quantization to federated learning to orchestration. What stood out most to me? The insight from Charles Crouchman, Chief Product Officer at Redwood Software: without unifying automation tools and processes, AI gets stuck managing silos instead of delivering outcomes. The question isn’t just “How do we make AI smarter?” It’s “How do we clear the path for AI to perform at its best?” #AI #Automation #DataDriven

20 strategies to make AI faster, leaner and more effective — from quantization to federated learning to orchestration. What stood out most to me? The insight from Charles Crouchman, Chief Product Officer at Redwood Software: without unifying automation tools and processes, AI gets stuck managing silos instead of delivering outcomes. The question isn’t just “How do we make AI smarter?” It’s “How do we clear the path for AI to perform at its best?” #AI #Automation #DataDriven

AI won’t reach peak performance if it’s running on fragmented systems. That’s why I love the perspective from Charles Crouchman of Redwood Software in this Forbes article: companies need to unify their automation tools and processes to unlock the full power of AI. Disconnected solutions slow down innovation — orchestration accelerates it. This is a must-read if you’re exploring how to scale AI effectively. #AI #Automation #Data #Leadership

AI won’t reach peak performance if it’s running on fragmented systems. That’s why I love the perspective from Charles Crouchman of Redwood Software in this Forbes article: companies need to unify their automation tools and processes to unlock the full power of AI. Disconnected solutions slow down innovation — orchestration accelerates it. This is a must-read if you’re exploring how to scale AI effectively. #AI #Automation #Data #Leadership

AI won’t reach peak performance if it’s running on fragmented systems. That’s why I love the perspective from Charles Crouchman of Redwood Software in this Forbes article: companies need to unify their automation tools and processes to unlock the full power of AI. Disconnected solutions slow down innovation — orchestration accelerates it. This is a must-read if you’re exploring how to scale AI effectively. #AI #Automation #Data #Leadership

AI won’t scale without automation. What really stood out to me in this Forbes piece featuring Redwood Software's Chief Product Officer Charles Crouchman: Companies must prioritise unifying their automation tools and processes to fully unlock AI’s potential. Too often, organisations chase AI pilots without a strong automation foundation — that’s where scalability breaks down. This article is a great reminder that AI and automation aren’t separate conversations; they’re two sides of the same coin. 📖 Worth a read if you’re exploring how to scale AI effectively. #AI #Automation #Data #Leadership

🚀 New LinkedIn Series: Data Products – The Fuel of Enterprise AI AI isn’t powered by algorithms alone—it’s powered by trustworthy, usable, and intelligent data products. In this series, I explore: 🔹 What Data Products are & why they matter 🔹 The architecture that makes them scale 🔹 How they accelerate AI adoption 🔹 The future of intelligent, AI-curated data 💡 Pro Tip: Think of data products as APIs—documented, governed, and designed for consumers. 💬 Question for you: Do you see data products becoming as critical as APIs in the next 5 years? #DataProducts #AI #DataStrategy #DigitalTransformation

🚨 95% of enterprise generative AI PoCs fail — not because the AI itself fails, but because it’s poorly integrated into real workflows and not driven by business rules. As MIT underscores: “95% of generative AI implementations in enterprises fail to impact profit and loss … due to flawed integration with existing workflows” At thinkeo, we take the opposite approach: instead of a "top‑down" rollout, we embrace bottom‑up, demand‑driven AI. MIT also highlights that “external partnerships with learning‑capable, customized tools reached deployment ~67% of the time, compared to ~33% for internally built tools” When we co‑create document‑generation workflows tailored to the exact needs of business teams — whether it’s drafting technical reports, responding to complex RFPs, or generating audit documents — we align with what MIT calls “solutions built by external vendors” that “succeed twice as often as internal builds” Thinkeo turns PoCs into production by listening to the teams who know the pain points. Bottom‑up, not up‑to‑down. Read the full MIT report: State of AI in Business 2025. Link below. #AI #DocumentAutomation #GenerativeAI #MITstudy #BottomUpAI #EnterpriseSoftware #Thinkeo