In recent years, news media have been hugely disrupted by the potential of technological-driven approaches in the creation, production, and distribution of news products and services. Artificial intelligence (AI) has emerged from the realm of science fiction and has become a very real tool that can aid society in addressing many issues, including the challenges faced by the news industry. The ubiquity of computing has become apparent and has shown the different approaches that can be achieved using AI. We analyzed the news industry AI adoption based on the seven subfields emanated from AI: (i) machine learning; (ii) computer vision (CV); (iii) speech recognition; (iv) natural language processing (NLP); (v) planning, scheduling, and optimization; (vi) expert systems; and (vii) robotics. Our findings suggest that three subfields are being more developed in the news media: machine learning, planning, scheduling & optimization, and computer vision. Other areas are still not fully deployed in the journalistic field. Most of the AI news projects rely on funds from tech companies, such as Google. This limits the potential of AI in the news industry to a small number of players. We conclude by providing examples of how these subfields are being developed in journalism and present an agenda for future research.