The Rise of AI: top 7 trends for 2023

5 min readMay 5, 2023

In the world of technology, Artificial Intelligence has been making waves in recent years. AI applications have been used in various industries, from healthcare to finance, and it has revolutionized the way businesses operate. As we look forward to the future, it is essential to understand what is happening in the world of AI and the most relevant trends for 2023.

Generative AI

The sub-field of machine learning known as Generative AI creates new data or content by utilizing an existing data set. Its goal is to produce results that closely resemble the original input data from the real world. This type of AI employs deep learning algorithms to discern patterns and features within the data set, which can encompass code, text, images, audio, video, and other forms of data.

Concerning AI-generated text, ChatGPT has been one of the most successful innovations of the year. Launched in November 2022, ChatGPT is capable of answering questions via prompts and carrying out instructions after being trained through human conversations and internet content written by humans.

The use of AI can generate new audio from a person’s voice sample. An example of this is FakeYou, which has gained popularity among GenZ for creating TikTok videos featuring VIPs or popular videogames or series characters. Voice cloning can help companies localize content and allow people to receive promotions and instructions in their native language. Filmmakers can also use it to alter an actor’s voice to speak in different languages.

AI-human collaborative robots

The level of assistance provided by AI to various human tasks has reached new heights and is expected to increase further, as with “cobots” or collaborative robots. Industry experts predict that more companies will utilize machines incorporating AI to perform repetitive and physically demanding tasks, letting human employees focus on more specialized duties.

In different industries, cobots are expected to become more prevalent. This includes areas such as automotive manufacturing, where they will be used for tasks such as car assembly, spray painting, surface polishing, and retrofitting production lines for electric vehicles. In agriculture, cobots will be employed for tasks such as seed planting, fertilizer and pesticide application, trespasser and invasive species tracking, and indoor farming with the use of LED lighting and hydroponics.

Democratization: low-code and no-code

The trend of low-code and no-code development in websites and apps creation will extend to AI, enabling organizations to customize intelligent systems through pre-built templates and drag-and-drop methods. This will facilitate the integration of AI into existing workflows and expedite its deployment within corporate settings.

Radicalbit’s Decision Intelligence platform, Helicon, is an example of this concept. It serves as the ultimate toolbox for data scientists and data engineers, facilitating the development of real-time applications and decision support systems through AI technology. Helicon offers swift and autonomous deployment, monitoring, and serving of AI models, as well as low-code capabilities that can be combined with Python code for maximum flexibility and limitless scalability.

According to a Business Wire report, low-code and no-code tools for IT modernization are 70% faster to complete (as short as three days) than traditional methods. By 2026, “citizen developers” who have not undergone formal coding training are forecasted by Gartner to account for 80% of low-code tool development users.

Adaptive AI

Recently included by Gartner in the 2023 Top 10 Strategic Technology Trends for 2023, Adaptive AI concerns AI systems that can learn and adapt over time based on ever-changing circumstances. Model behavior change and unceasing evolution in production can definitely have a beneficial impact on organizations, supporting a continual alignment between AI practices and business goals. As Gartner points out, “by 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the number and time it takes to operationalize artificial intelligence models by at least 25%.”

Adaptive AI is akin to online machine learning, also known as incremental or out-of-core learning. It means that a model learns from examples in something close to real-time, while it infers predictions and actionable outputs on the fly. We are talking about a stateful process, since the model keeps on training on new data points (fine-tuning).

Digital Twin

A Digital Twin is a virtual model of a real-word system. Thanks to the combination of IoT, Machine Learning and Artificial Intelligence, it enables the replication of physical objects and processes in a virtual environment to increase efficiency in manufacturing and optimize the supply chain.

Today, Digital Twins are mainly used in testing and predictive maintenance. Being able to replicate in vitro various aspects of objects and processes, they allow to carry out experiments without creating expensive real-world prototypes. The real-time virtualization also helps preempt anomalies or malfunctions that may affect the physical equivalent, while enabling a more effective planning of maintenance routines.

The Omniverse platform developed by NVIDIA, a leading GPU manufacturer, is one example of this technology in action. For instance, BMW uses Omniverse for virtual manufacturing, allowing remote access to real-time simulations of their 31 factories.

AI for customised services

For eCommerce, 69% of those who participated in a Salesforce survey have stated that they are willing to accept its implementation by brands if it enhances their shopping experience. This sentiment is expected to grow as 91% of customers are already engaging with chatbots, which are mostly powered by AI.

Employers also have concerns about artificial intelligence, but industry experts predict that AI tools will still be used to enhance team communication software and workplace learning. PwC reports that 54% of executives at companies have noticed an increase in employees productivity, and 80% think automation will be beneficial in making business decisions.

AI for Health

The optimization of electronic health records through AI can enable medical professionals to provide precision medicine, including targeted diagnostics, personalized drug development, and customized treatment plans.

Telehealth will expand its capabilities to include remote physical exams using smartphone apps or wearables, facilitating virtual exams and decentralized clinical trials.

The current trends in AI are geared towards democratization, enabling everyone to take advantage of its potential. This includes generative AI that boosts efficiency and provides quicker insights, explainable AI that promotes transparency and reveals biases in automated decision-making processes, improved customer experiences, and an overall enhancement of brand experiences through AI tools. Businesses need to keep up with the latest developments in AI to maximize its benefits.

If you want to learn more about Helicon, Radicalbit’s Decision Intelligence platform, and how to enrich real-time data with AI, enhance decision-making and drive your business results, take a look at this link.




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