Artificial Intelligence (AI) has come a long way, from answering simple queries and playing chess to solving complex business problems and predicting future trends. Despite anxious perspectives of mass unemployment, AI-induced automation of production chains and operations is an inevitable reality. Companies are already banking on recent technological breakthroughs for enhanced customer experiences and quicker business insights. This guide aims to dispel the myths surrounding AI and further democratize it by looking at the top eight AI trends of 2023.
Top 8 AI Trends of 2023
Gartner expects low-code AI optimization to account for at least 80% of the new no-code user base by 2026. More active involvement of nontechnical personnel in the world of AI will democratize its usage across industries and businesses of all sizes.
No-code platforms such as Sway AI enable project managers to streamline the AI optimization process for complex data analysis and visualization processes. With 50% of medium-to-large companies adopting low-code development, it will drastically reduce the dependency on IT development and support teams.
The Rise of Augmented Analytics
Augmented analytics empowers AI tools to assist with data preparation and insight generation methods by deploying Machine Learning (ML) and Natural Language Processing (NLP), augmenting the prevalent data exploration methods.
Every industry has found an application for augmented analytics as it transforms how organizations look at data, making it one of the definitive 2023 AI trends. Gartner predicts that by 2025, 75% of data stories will be automatically generated using augmented analytics techniques. This growing data culture will enable business users and executives to access deep insights and automate the processes of identifying critical change without any expertise in working with data.
In 2022, the average cost of a data breach in the U.S. was $9.44 million. The 2022 Electric Cybersecurity report also mentions that at least 67% of small businesses have faced more than one security breach, which could influence AI trends in cybersecurity in the coming year.
AI will be used to monitor employees as 51% of all knowledge workers now work remotely. In addition, advanced observation programs will enable software systems to integrate network devices, applications, and servers to provide real-time monitoring of employees, instant cloud-based solutions, and foresee threats.
AI in the World of Art
MidjourneyAI has taken the world by storm with its ML algorithms that create unique images from text prompts by combining chunks from large amounts of preloaded data. Generative art will continue to develop its incredible versatility with the emergence of more agile hardware systems.
As marketers begin to understand its true potential in transforming creative thinking, the quality of generative art will only increase. The automated content generation will optimize creative production and lead to more informative or appealing content, making it one of the defining AI trends of 2023.
Greater Human-AI Collaboration
As cited in a Nature Machine Intelligence study, the future lies in human-AI collaboration rather than one replacing the other. Deploying machines with built-in AI systems will free humans from repetitive tasks, streamline responses to operational failures, and improve safety mechanisms. Some of these developments have already penetrated a few industries such as:
Healthcare: Increased use of sample collections for more robust testing; the rise of robotic surgeries
Agriculture: AI-regulated seed planting; invasive species tracking
Automotive Industry: Automated car assembly; systems checking; optimizing car production lines
Personalization and Generative AI
The explosive popularity of ChatGPT 3 has given us a glimpse into the potential of large language models and their importance in scaling relevant marketing content without actually writing it. So, another trend to keep track of is the rise of AI-optimized hyper-personalization.
AI will combine the latest developments in deep neural networking with developments in audio, video, and image processing techniques to tailor brand messages according to the individual cyber personas of consumers. This trend will have a great impact on the entertainment and e-commerce industries.
When AI meets edge computing, the result is called Edge AI—the next frontier of computing technology that will decentralize the entire process of data analysis. Edge computing brings analysis closer to the data sources, meaning the data source is equipped with the infrastructure requirements for real-time data processing. Though in its nascent stages, Edge AI is looking at a potential market size of over $3 billion by 2027.
However, it is increasingly favored by the growing prevalence of Internet of Things (IoT) devices. In fact, Edge AI is gaining record popularity as it drastically reduces energy usage with its local analysis and neutralizes privacy concerns of offloading data to external computer systems.
A digital twin is a digital replica of a real-world object where advanced ML models create simulations of physical entities and observe their behavior in real time. The glTF file format is the result of a synergy between the digital twin and generative AI. In essence, this has been a game changer in simplifying 3D model sharing across different tools.
Moreover, optimizing production chains in manufacturing industries, testing prototypes and designing architectural concepts, monitoring the health of humans—the ramifications of digital twin technology are staggering. And companies such as Bentley, Siemens, and General Electric have already marked their territories in the infrastructure metaverse by introducing connecting data points across digital twin software systems.