A.Team

?? NEW RESEARCH: Only 36% of AI initiatives reach production. What are the winners doing differently? We surveyed 250 tech leaders and found: - Companies using blended teams are 2X more likely to deploy AI successfully - 94% say talent shortage is their #1 barrier - 92% plan to increase freelance engagements in the next 24 months - 93% say custom solutions deliver more value than off-the-shelf tools - The AI talent crisis is real, but some organizations are breaking through. Preview of our research below. Download the full "2025 State of AI Innovation Report" to see how leaders are structuring teams, measuring ROI, and making technical investments: https://hubs.la/Q037K7qn0

Earlier this month our team attended HumanX in Vegas, and it was excellent. 4,000+ of the worlds top tech leaders, all there for one purpose: to bridge the gap between AI innovation and practical implementation. Stefan Weitz and Andrew Blum put together an incredibly well-run conference, especially for a first-time event. The lineup and attendance were exceptional, offering attendees actionable insights and strategies to navigate the AI-driven future. We saw impressive tech demos like AWS's holographic AI avatars you can have conversations with. Cool stuff. But on the other hand, there was widespread recognition that great demos don't translate as-is to business value. Enterprise leaders are realizing that the real challenge isn't just choosing from the overwhelming number of tools and infrastructure options. It’s making AI work in their actual business. Because, in AI, the last mile is the longest mile: Building systems that work - integrating multiple providers without getting locked in, creating UX that fits naturally into existing workflows, and establishing proper control, oversight, and handling of sensitive data. As some of the founders of leading LLM foundational models shared - AI models are already really strong. GPT-4.5 wasn't nearly the splash that GPT-3 and GPT-4 were. But while there's been massive investment at the foundational model level, the application layer is still very thin and incredibly difficult to get right. Even the best off-the-shelf AI product can only take you 80% of the way. The companies seeing real ROI aren't just buying tools, they're building AI-ready infrastructure. Because that last mile - workflow integration, data governance, quality control - is where AI efforts succeed or fail. Over the past two years, A.Team has helped 500+ companies move past the hype and deliver tangible value with AI. If your team has big AI ambitions but lacks the expertise to deliver, shoot me a DM. And if you attended HumanX, I'd love to hear what insights you took away in the comments!

In the latest of our?#HowISolvedIt Series, Gowri Shankar - a leading AI expert in the A.Team Network - reveals how he uses Claude as a peer programmer to debug his builds ?? Read it here: https://hubs.la/Q03djFxM0

Long before ChatGPT rocked the world, Zack Kass was bullish on AI. He started his career during the “AI winter,” in the middle of the 2009 financial crisis. Fresh out of Berkeley, he joined CrowdFlower (later Figure Eight) - the first human data labeling company at scale, built by ex-Yahoo search scientists. From there, a decade in leadership across AI startups led him to a small research lab called OpenAI. He was one of their first 100 employees. He built and led their go-to-market team as OpenAI became the fastest-growing tech platform in history - spearheading the first successful enterprise GenAI applications with partners like Morgan Stanley. Since then, Kass has had a front-row seat to the biggest friction points in AI adoption. After leaving OpenAI, he traveled the globe speaking to corporate teams and helping enterprise execs design their AI strategy. We sat down with him in late December to talk about what most companies are still getting wrong, how to move faster, and why the biggest winners in AI aren’t who you think. Here's what he told us: https://hubs.la/Q03dgH-m0

What's the #1 thing that attracts senior AI talent? It's not just compensation. Kyle Langworthy, Head of ML/AI at Riviera Partners, reveals what truly motivates top AI leaders: Impact. -> Impact on the organization -> Impact on users -> Impact on markets -> Impact on industries Our State of AI Innovation research found that 82% of companies are worried about losing their AI talent. Yet the companies succeeding at retention understand this fundamental truth. When AI leaders leave established tech giants for smaller companies or even startups, they're typically making a calculated bet on where they can have the greatest influence. Want to learn how successful organizations are attracting, retaining, and structuring AI teams for maximum impact? Download our complete report: https://hubs.la/Q03cGLsX0

The AI gap is widening: Only 36% of companies have escaped what we call "Prototype Purgatory." Our State of AI Innovation research found that while impressive demos abound, getting AI into production is where organizations struggle. As our Head of Content & Research explains, reaching production deployment is the dividing line between AI leaders and laggards. It's that crucial "last mile" that separates impressive demos from business impact. What are these AI leaders doing differently? - Their team structures are 2x more likely to deliver - 93% prioritize custom solutions over off-the-shelf tools - They're investing strategically in infrastructure and monitoring Want the full breakdown of what separates AI leaders from the pack? Our comprehensive research reveals the strategies, investments, and team structures that drive results. Download the complete State of AI Innovation Report: https://hubs.la/Q03chmWx0

94% of tech leaders say talent constraints are their #1 barrier to AI innovation. But the solution isn't as simple as "hire more people." Kyle Langworthy, Head of ML/AI at Riviera Partners, explains how top CTOs are tackling this challenge: - Get specific about your constraint: Is it geographic? Attraction? Role design? - Align your product roadmap with your current talent capabilities - Develop a talent strategy that matches your development timeline Our State of AI Innovation research found the most successful companies are using blended teams that integrate freelance specialists with full-time employees—making them 2x more likely to reach advanced stages of AI maturity. Interestingly, the hardest roles to fill aren't always what you'd expect. Data Scientists (48%) and Data Engineers (44%) topped the list, followed by AI Research Scientists. Want the complete playbook for building high-performing AI teams? Download our report: https://hubs.la/Q03bLWb_0

That’s a wrap! Thanks to then HumanX team for an incredible event. Truly inspiring to hang with some of the greats in #AI! A.Team

Traditional software is deterministic. AI is anything but. Vineet Sinha, a top fractional CTO in the A.Team Network, shares a critical insight from our State of AI Innovation research: to succeed in AI, you need to fundamentally rethink established roles and approaches. - QA needs new testing frameworks - Product managers must adapt requirements - Ops faces new monitoring challenges This mindset shift is exactly what separates the 36% of organizations successfully deploying AI from those stuck in prototype purgatory. What else are successful AI leaders doing differently? Download our complete State of AI Innovation Report to discover: - The team structure making organizations 2x more likely to reach AI maturity - Which technical investments are delivering the fastest ROI - How leading CTOs are building teams that ship AI faster Get it here: https://hubs.la/Q03bhZvP0

Having a blast at HumanX! If you're here, catch some of the Enterprise sessions tomorrow - opening remarks and MC'd by me (A.Team) ??♀? ?? 12:15PM | Rethinking Prediction with Cameron Fink (Aaru) on AI agents revolutionizing predictive simulations across industries ?? 12:30PM | AI at Scale: Enterprise Transformation with David Bromberg ?? (Lantern), Vanessa Larco (NEA), Steve Irvine (integrate.ai), Jo?o Gra?a (Unbabel), Sachin Dev Duggal (Builder.ai). Moderated by Jon Victor (The Information) ?? 1:00PM | AI & The Future of Work with Rahul Vohra (Superhuman) exploring how AI transforms core productivity tools and collaboration. Moderated by Anna Tong (Reuters) ?? 2:30PM | AI's Impact on Workflows & Code featuring Prashanth Chandrasekar (Stack Overflow), May Habib (Writer), Doug Pepper (ICONIQ Growth). Moderated by Heather Joslyn (The New Stack) 3:00PM | Driving Business Success with AI panel with Cristina Gonzales (Cantellus Group), Vineet Kumar (Fanatics), Deborah Weinswig 韋葆蘭 (Coresight). Moderated by Elizabeth Weil (Scribble Ventures) ?? 3:45PM | AI Agents Rewriting Work Rules keynote by Miranda Nash (Oracle AI) on how AI agents are reimagining the workforce