10 most in-demand generative AI skills

3. TensorFlow

Developed by Google as an open-source machine learning framework, TensorFlow is most used to build and train machine learning models and neural networks. As a popular and effective tool that assists companies with the development and deployment of AI models, the skill is in high demand across several industries and job roles. Relevant job roles include machine learning engineer, deep learning engineer, AI research scientist, NLP engineer, data scientists and analysts, AI product manager, AI consultant, AI systems architect, AI ethics and compliance analyst, among others.

4. Image processing

AI is being used to analyze and process images, while also pulling data and information from visuals and text documents, and interpreting or manipulating that data as needed. AI image processing enables organizations to analyze and extract data from documents such as invoices, purchase orders, packing lists, receipts, and more. It also has important applications in the healthcare industry, contributing to analyzing medical imaging from MRI and CT scans. There are several steps involved with image processing, including image acquisition, enhancement, restoration, processing, compression and decompression, morphological processing, image recognition, and data visualization. Relevant job roles include image processing engineer or scientist, robotics engineer, AI research scientist, quality control analyst, AR or VR developer, among others.

5. PyTorch

Developed by the Facebook AI Research (FAIR) team in 2017 as an open-source machine learning library, PyTorch is a popular framework that helps organizations build and train deep learning models and neural networks that can be employed in technology such as NLP and other applications. PyTorch is known in the deep learning and AI community as being a flexible, fast, and easy-to-use framework for building deep neural networks. Lauded features include dynamic computation graphics, a Python foundation, and automatic differentiation for creating and training deep neural networks. Relevant job roles include machine learning engineer, NLP engineer, AI research scientist, data scientist or analyst, medical imaging specialist, and AI ethics and compliance analyst.  

6. AI content creation

Generative AI’s promise for content creation can’t be denied, and more companies are turning to generative AI to create content such as blog posts, social media posts, graphics, articles, and even videos. However, generative AI isn’t always successful at producing content that comes off natural or relevant to humans, resulting in clunky or awkward text that requires some level of human editing to make sense. As a result, there’s been an increase in demand for professionals who can prompt gen AI engines effectively in the production of relevant content and cast an eye over AI-generated content to ensure it flows smoothly, makes sense, and will resonate with a human audience. Relevant job roles include AI copywriter, content strategist, AI content analyst, AI graphic designer, AI video producer and editor, AI chatbot content developer, and AI content compliance manager.

7. Midjourney

Midjourney is a generative AI service that was developed in 2022 to generate images using natural language prompts. It’s currently available only for use through the company’s official Discord server, using a bot that will generate four images per user request. Its release sparked some controversy, especially among members of the arts and graphic design communities, who worried that the technology could replace artists and human-made content. Concerns around copyright violation have also arisen — including lawsuits from artists who claim that the AI is infringing on artists rights due to its being trained on the existing work of millions of artists. However, the Midjourney research lab claims it wants to work with artists, and serve as a tool to help them create content easier. No matter where you stand on AI-generated art, the demand for Midjourney skills is high as organizations seek to capitalize on the technology to create custom ads, and as an alternative to searching Google Images for inspiration.

8. AI chatbot

AI chatbots have become commonplace in modern society, especially in e-commerce, customer service, and retail. Companies increasingly employ AI to reduce the workload on human representatives, typically rerouting customers to helpful documentation, direct answers to common questions, and support for simpler issues before connecting them with a human representative. Using AI chatbots, organizations can better streamline the customer experience, but these services also require regular maintenance and management by human workers. Organizations are looking for professionals who can test and debug, deploy and integrate, and analyze and monitor chatbot services. They’re also seeking skills around APIs, deep learning, machine learning, natural language processing, dialog management, and text preprocessing.