I wrote AI Operations: The Solution to the Enterprise AI Adoption Gap in just 10 days, but it took 20 months of learning to get to that point. Organizing years of knowledge, refining it, and working alongside AI as a writing partner unlocked a completely new way of thinking. It wasn’t just faster—it was transformative. And what’s even more interesting is that this is the worst AI will ever be. As the technology improves, so will the ability to create at this pace, making the process even more seamless.

Imagine you’re a salesperson at a company with a brilliant idea—a new webpage that could significantly support your selling efforts by showcasing customer testimonials, interactive product comparisons, or a personalized ROI calculator. But to bring this idea to life, you’d have to navigate a maze of departments. Marketing would need to approve and write the content. Engineering would have to build the page. Leadership would need to sign off, and various stakeholders would need to be convinced it was worth the effort. Realistically, it might take weeks—if not months—before anything materialized, if it even got prioritized at all. And after a few rounds of pitching the idea, your manager might say something like, "Stop trying to be creative and just do your job." The message is clear: innovation at the individual level is not worth the trouble.

Below is a list of statistics I used while writing my AI Operations book. Here is a list of AI statistics that Deep Research (from OpenAI) produced along the journey of writing this book (and as of February 13th, 2025). I have not tested all of these links but most seem legit.

In just a few short years, generative AI has gone from a fascinating novelty to an indispensable partner in our daily lives. Much like the iPhone reshaped how we communicate and work, AI is rapidly embedding itself into every facet of our existence. But while smartphones made us all connected, AI is poised to fundamentally augment our human capabilities. In this post, we’ll explore how generative AI is changing society, compare it with previous technological revolutions, and take a glimpse into a future defined by AI-human collaboration.

Artificial intelligence (AI) is generating excitement across boardrooms, but many decision-makers still hesitate, waiting for a neatly defined, quantifiable return on investment (ROI). History, however, tells a different story. Transformative technologies—from email to the internet, cloud computing, mobile-first strategies, and cybersecurity—were adopted long before their full economic benefits could be precisely measured. In this post, we explore how these technologies changed the business landscape despite initial uncertainties, and why the same spirit of bold experimentation should apply to AI today.

Small business owners are increasingly exploring AI to overcome everyday challenges and drive growth. Recent studies reveal that a significant portion of small and micro businesses are already experimenting with AI tools—with up to 75% of small businesses trying them in some capacity [1]. However, many owners are held back by concerns over complexity, cost, and the unpredictability of traditional AI solutions [2][3]. This is where FrenchFryAI comes in. Designed specifically for small business needs, FrenchFryAI combines a broad suite of easy-to-use tools with unique, guided features—most notably, the Flow enhancement for AI chatbots—to transform how small businesses adopt and benefit from AI.

AI-driven coding assistants like GitHub Copilot, OpenAI’s ChatGPT, and newer tools (e.g. Jolt AI) are increasingly being integrated into software engineering workflows. These AI tools can generate code, explain snippets, and even assist in debugging. Research and industry reports show both excitement and concern about their impact, especially in large, established codebases. This report surveys academic literature, industry discussions, and case studies to understand how such AI coding tools are being adopted, the key challenges that arise, and emerging solutions. We focus on enterprises and teams managing massive code repositories, where issues of code quality, knowledge retention, and workflow changes are especially pronounced.

Over the Thanksgiving break, I wanted to work on something separate from my everyday job. I’ve done this throughout my career, and it’s a great way to be creative, learn and test new skills, and generally get my mind thinking outside the day-to-day grind. This time, it was about bringing to life a spur-of-the-moment idea I had: creating an app for people who don’t really know how to leverage the power of AI—specifically small business owners.

In a remote sales world, practicing cold-call skills can be tough—but I’ve built a tool to make it easier. Using a custom ChatGPT, BDRs at data.world can now engage in realistic, on-demand role-play sessions that challenge them to handle objections just like in real sales conversations. This GPT-based “virtual trainer” not only provides real-time feedback but also suggests personalized learning resources through our Vectorizer system, making it a unique way for reps to sharpen their skills on their schedule. Listen to an example interaction, and see how this AI-powered approach is helping our team build confidence and proficiency, one role-play at a time.

In a groundbreaking study on AI’s role in scientific discovery, Aidan Toner-Rodgers explores how a specialized AI tool transformed materials innovation in a leading U.S. R&D lab. While AI-assisted scientists discovered more novel compounds and filed more patents, the impact varied widely across skill levels. This case demonstrates why AI Operations is essential in bridging the gap between technology and human expertise—aligning AI capabilities with scientists’ skills to maximize innovation. Read on to see how AI Operations provides the critical link between AI’s potential and real-world productivity in scientific research.

At data.world, we’re embracing AI with a proactive approach that aligns closely with industry trends. Our focus on training, experimentation, and consistent usage of generative AI tools has led to impressive engagement: 78% of our employees use ChatGPT Teams accounts, averaging 2.35 Custom-GPT sessions per week—well above industry averages. By fostering an “internally led” AI strategy, we’re not only tracking with the report’s findings but also setting ourselves apart in adoption, education, and responsible innovation. As generative AI continues to evolve, data.world is committed to leading the way in meaningful AI integration.

Owl Genius is data.world’s latest AI-powered app, developed as part of our AI Champions initiative. By combining OpenAI’s language capabilities with our in-house Vectorizer middleware, Owl Genius delivers personalized learning plans that adapt to each user’s unique needs. In this post, I’ll share how the AI Champions team built Owl Genius, how it’s helping our employees grow, and how it taps into data.world’s vast knowledge ecosystem to provide powerful, targeted learning experiences.

At data.world, we’re always looking for ways to use AI to make our teams more productive and deliver value faster. Our latest innovation, the Custom Demo Generator, automates the creation of personalized demos, transforming a process that once took days into one that’s completed in minutes. By tailoring demos to each client’s unique industry and needs, we’re helping prospects see the true impact of our platform in their own context. In this post, I’ll walk through how the tool works, how it’s saving time for our sales team, and how it’s enhancing our customer interactions.

AI isn’t just a buzzword anymore—it's the backbone of modern innovation. But while the potential is clear, scaling and operationalizing AI effectively is where most organizations hit a wall. That’s where AI Operations (AIOps) comes in. It’s not just about deploying AI, it’s about keeping it healthy, adaptive, and value-driven.

Learn how data.world developed Fedbot, an AI-driven chatbot tailored specifically for the federal sector. Embedded on a partner’s site, Fedbot leverages our Vectorizer with a custom Knowledge API to deliver accurate, real-time answers from a curated knowledge base. This post dives into the unique build process, from integrating federal-specific PDFs to creating a fully responsive, embeddable app—resulting in a powerful tool that serves as a one-stop solution for federal agencies.

The following is a text message I sent to my son and daughter the night before their sophmore and freshman year first day of school. I don’t share 99.9% of what I send them but for some reason this one felt like it might benefit others. So here it is…

The world of AI has seen rapid evolution, and at data.world, we've been at the forefront of this revolution. As we continue to grow and adapt to the ever-changing landscape, it's essential to look back at where we started, understand the challenges we faced, and appreciate the solutions we've implemented to meet those challenges. This post will take you through the journey of AI Operations (AI Ops) at data.world, the need for scaling, and the pivotal role that Chat-GPT Teams has played as a front-end for our operations.

Discover how data.world’s AI Docs Bot is transforming access to critical documentation. Built on our Vectorizer and seamlessly integrated into our documentation site, the AI Docs Bot uses vector search and retrieval-augmented generation (RAG) to quickly surface relevant answers from over a thousand pages. This post explores how we created this tool in just four weeks, optimized its performance with prompt engineering, and the impact it’s having on our internal teams and customer experience.

I'm sharing this short article in case others are trying to solve a similar problem. Here is the setup: we’ve created several early and MVP versions of some generative AI tools for data.world. These tools were either quick Streamlit or React/Node apps that interacted with OpenAI through a detailed system message and a Retrieval-Augmented Generation (RAG) architecture.

Juan and Tim’s engaging conversations on enterprise data just got even more interactive – with our new app. Ask questions, explore episodes, and dive into discussions with your favorite guests, all powered by data.world's cutting-edge AI Operations. Ready to chat? Jump in now!