Maryam Ashoori, PhD’s Post

⚠️ The Unseen Complexity of Generative AI in Enterprise The market is glorifying the potential of Generative AI for enterprise, while overlooking the complexity of what it takes to deliver on that potential. Behind a seamless AI application, there exists an immensely complicated AI stack that developers must master to unlock its true value 🔓. 👩🏽💻We spoke with 1000+ developers in the US who are charged with building AI applications for the enterprise. The findings highlight the challenges they face, including: 🛠️Tooling Challenges: Developers are frustrated with the tools at their disposal. Most surveyed use between 5 and 15 tools to create an AI enterprise application. Given the pace of change in generative AI, developers crave tools that are easy to master. Only 1/3 of those surveyed are willing to invest more than 2 hours in learning a new AI development tool. 💎The four most essential qualities in AI development tools – performance, flexibility, ease of use, and integration – are also the rarest to find. 🧠 Skills Variance: Generative AI skill levels vary significantly among developers, with app developers ranking themselves particularly low in genAI skills. ⚖️ Lack of Standardized Processes: Survey respondents cited a lack of standardized AI development process and developing an ethical and trusted AI lifecycle as top challenges. 🤖 Agents: These development challenges will only become exacerbated as the industry pushes further into agentic AI, which promises greater power and autonomy – but also hinges on trust and integration. Almost all developers surveyed (99%) are exploring or developing AI agents, with trustworthiness being the top concern. Simplifying the AI stack and AI development lifecycle is a key focus for IBM. In a future post, I’ll share the watsonx.ai AI stack for agents and how we're simplifying the stack with a focus on choices at every layer, targeting a broad skillset from no code experiences to pro-code SDK and APIs for developers. I spoke with Michael Vizard at TechStrong Group about the findings -- how developers can address tool sprawl, prioritize transparency and traceability, and more: https://lnkd.in/eiFvVaZz Survey: https://lnkd.in/e-ezE-h7 IBM Blog: https://lnkd.in/etVatrKq