How to identify new AI job roles

New AI job roles, the certifications tech companies want 

The big subject of interest this week remains AI. How to build a career as an AI developer, how AI can support your personal productivity, and how to build agentic AI platforms. Truly, we spoil you.  

Getting certified in one or more leading AI development platforms won’t necessarily land you the job, but it could help you get noticed. InfoWorld this week went all in on identifying the AI developer certifications tech companies really want. 

Important information because the impact of AI on the jobs market is in the early development stage. We don’t know what the roles will be, which creates a challenge for both hirer and aspirant employee. CIOs are wrestling with which blend of hire, train or upskill they should be unleashing. And those building careers need to understand how tech companies are identifying those emerging AI job roles.  

Smart Answers, our generative AI chatbot which parses insights from decades of human reporting, has some insights.  

It says that companies identify emerging roles by monitoring labor market data and employer priorities. They analyze job growth, frequently appearing job titles, and new skill sets requested in job postings to pinpoint roles such as prompt engineering and AI systems architects.  

Find out: How do tech companies identify emerging AI job roles?  

Take note   

Computerworld takes great pleasure in promoting the business value to be found in end user devices. This week we were happy to report that despite Google Keep losing its location-based reminders, you can still use set location-based reminders on your Android device. It’s a useful function for those that want it.  

This led to readers of Computerworld asking broader questions about use of tech as admin assistant, specifically the use of AI in supporting productivity.  

Smart Answers knows: saying that AI assistants are significantly transforming note-taking within productivity tools by automating various tasks, enhancing content organization, and providing advanced analytical capabilities. These integrations aim to streamline workflows, reduce cognitive load, and improve the overall utility of digital notes. Want details? As our generative AI answers service.  

Find out: How are AI assistants enhancing productivity tool note-taking?  

How to build successful agentic AI 

For all the potential of generative and agentic AI, truly successful products and platforms are thin on the ground. InfoWorld this week reported on how LinkedIn built an agentic AI platform. We explained that working with AI at scale requires that you use models and their APIs like any other components in a software development stack. 

This prompted our more technical readers to ask for more detail. How does one build an agentic AI platform? 

Smart Answers says key architectural components for building production-grade agentic AI systems include modular orchestration, behavioral safety, observability, and the integration of LLMs with business logic. There’s much more, and you know where to go for answers… 

Find out: What are the core architectural components of agentic AI?  

About Smart Answers 

Smart Answers is an AI-based chatbot tool designed to help you discover content, answer questions, and go deep on the topics that matter to you. Each week we send you the three most popular questions asked by our readers, and the answers Smart Answers provides. 

Developed in partnership with Miso.ai, Smart Answers draws only on editorial content from our network of trusted media brands—CIO, Computerworld, CSO, InfoWorld, and Network World—and was trained on questions that a savvy enterprise IT audience would ask. The result is a fast, efficient way for you to get more value from our content. How to identify new AI job roles