11 Areas Transformed thanks to Generative AI

The year 2023 was defined as a breakthrough in the field of technological development. We have witnessed unprecedented growth in the capabilities and applications of generative AI. The landscape of creative, analytical and research tasks has been irreversibly changed. It marks a revolutionary phase both in the IT industry and in everyday life.

The past year has demonstrated the immeasurable potential of generative tools (GenAI) to optimise processes, create sophisticated code and works of art, and unlock new possibilities in their applications. There has been a sharp increase in the use of GenAI in many spheres of life, science, and economy. The transformations that occurred redefined the creation and production processes.

11 areas and related transformations

1. Transformation in the field of language and communication

Advanced AI-based language models have made it possible to generate human-like text. They are able to write articles, compose poetry, or prepare technical documents with minimal human intervention.

Their impact has proven profound in sectors such as journalism, marketing and education, where the quality and quantity of written content are crucial. It has revolutionised many areas, including customer service and even literature.

Copywriters, journalists and writers use GenAI tools to increase their creativity and efficiency, creating content on a scale and speed previously unattainable.

Google attempted to transform journalism with AI Genesis, a revolutionary initiative using AI in writing. The company has demonstrated it in, among others, the Times, the Washington Post and the Wall Street Journal as “responsible technology that gathers facts and spits out news copy”. These media outlets consider it to support and enhance the journalist's work, not replace it.

2. Transformation in the sphere of creativity

GenAI's profound impact on the creative arts has proven transformative for artists, designers, and creators across various fields. Using its tools has improved the creative process, leading to a combination of human ingenuity and algorithmic precision.

The greatest invention turned out to be tools for generating and editing images. Using simple text prompts, sometimes it is possible to create works of art that are often indistinguishable from human creations. The world of GenAI has also entered the sphere of music generation, presenting increasingly innovative models.

The transformation in the creative field shows that GenAI not only imitates human creativity but offers completely new perspectives.

By pushing the boundaries of creativity, these technologies have challenged traditional notions of creation and authorship and raised philosophical questions about art and authorship.

3. Transformation in software development

AI models have changed the way software is generated and maintained. GenAI supports users in coding, debugging, and even conceptualising software architecture. Coding assistants like Github Copilot have become essential tools for developers, helping them write more efficient and bug-free code.

GenAI tools offer real-time suggestions, automate routine tasks, and even help solve complex problems, significantly speeding up the software development process.

This transformation has lowered the skill barrier in software development among beginners and experts alike, democratising access in the field.

We also witnessed AI models contributing to open-source projects, suggesting improvements and optimising existing code bases. It sparked a discussion about the future role of AI in software development, whether it will be able to create it independently.

4. Transformation in the field of scientific research

GenAI's models have been used to simulate complex scientific experiments, predict molecular structures, and even contribute to breakthrough discoveries in fields such as medicine and environmental science.

AI has become a vital tool in understanding complex scientific problems by processing and interpreting large data sets. It not only accelerated research processes but made it possible to obtain previously unattainable insights due to the limitations of human analysis, opening up new opportunities for discovery. Interdisciplinary research has also been significantly facilitated, enabling scientists from different fields to cooperate more effectively.

In medical research, GenAI has been used to model protein structures, predict drug interactions and design new ones, significantly shortening the time and costs associated with drug development. In another revolutionary move, researchers have developed AI that can create artificial enzymes or proteins from scratch. AtomAI introduced AI to the analysis of microscopic data, which increased their precision and efficiency, opening new opportunities in fields such as biology and materials engineering.

5. Transformation in the field of healthcare

The use of advanced GenAI technologies has led to improvements in diagnostics, identification, and drug discovery. It serves patients by simplifying complex medical information and provides physicians with actionable insights from complex data, making it easier to make informed decisions.

AI-based diagnostic tools created for this purpose have increased cancer detection rates, optimised surgeries, forecasted patient volumes, and streamlined administration. Clinically proven applications of AI demonstrate significant improvements in diagnostic testing, including a 70% reduction in cancer detection errors.

When MIT researchers collaborated with Mass General Hospital to develop a deep learning model that would assess lung cancer risk based on low-dose CT scans, „Sybil” was created. This AI tool accurately predicts a patient's lung cancer risk without using additional demographic or clinical information.

6. Transformation in product design and quality

Revolutionising product design with GenAI tools has reduced time and costs while increasing product efficiency and quality.

Production processes have been modernised, creating workflows that reduce waste, increase productivity, and improve final product quality. Additionally, GenAI tools optimise supply chains and automate supplier assessment.

In quality control, it has been a game changer by identifying defects through advanced inspection methods, increasing accuracy, efficiency, and product quality while reducing time and costs.

7. Transformation in the media and entertainment sectors

These sectors have benefited from GenAI in terms of content creation, recommendation systems and audience engagement. This trend is expected to continue as companies recognise its potential for innovation and growth. GenAI optimises designs, reduces costs and transforms personalised content, increasing engagement and creating new revenue streams.

For example, OpenAI's DALL-E has transformed media and entertainment by generating realistic images from text messages, and platforms (like Netflix and TikTok) are using AI to predict user preferences, further improving content recommendations.

8. Transformation in education

AI has seen many changes in how we learn and create personalised learning experiences in the education sector.

GenAI-based tools have made a strong impact in recommending courses and tailoring content to individual students, improving the quality of online learning.

Virtual bots work as advisors, curriculum designers, and teaching assistants. Additionally, AI-based assessment tools are being developed to maintain academic integrity in online examinations.

In the field of education, Bill Gates predicted a future where AI-powered chatbots would play a key role in teaching children to read in just 18 months.

9. Transformation in climate and environmental sciences

GenAI played a crucial role in counteracting unfavourable climate change in 2023. Its effects are monitored in real-time by analysing data from satellites, weather stations, and other sources.

Climate modelling platforms use AI to predict future climate change, mitigating tipping points. In environmental science, AI models analyse massive datasets to develop climate patterns, assess climate impacts on the environment, and propose sustainability solutions.

AI-based energy management systems have optimised energy consumption in buildings, contributing to achieving sustainability goals.

10. Transformation in the field of materials science

In the field of materials science, GenAI (e.g. thanks to Google DeepMind) has predicted the structure of over 2 million new materials, potentially paving the way for advances in batteries, solar panels and computer chips.

This transformation allows to reduce time and save costs associated with the discovery and synthesis of new materials.

11. Cybersecurity transformation

GenAI solutions have significantly improved real-time threat detection and response, and vulnerability scanners have helped organisations proactively identify and patch vulnerabilities. An example would be adopting a zero-trust security model.

In turn, fraud detection tools have improved the ability of financial institutions to combat fraudulent transactions.

A further cyber arms race is underway, in which advances in computing power must be balanced by strengthened digital defences. New GenAI solutions related to the development of quantum computing are already visible on the horizon.

Predicting upcoming transformational trends

1. Quantum AI

Quantum AI, combining quantum mechanics, AI, and machine learning, has enormous potential to revolutionise many significant areas of life. For example, in healthcare, quantum-enhanced algorithms can result in more sophisticated risk assessment models and the development of more accurate diagnostic tools and personalised medicine. In finance, quantum-enhanced algorithms can result in more effective risk assessment models. Quantum technology will undoubtedly have a massive impact on cybersecurity.

2. Semiconductors

The semiconductor industry is at the threshold of an era of digital transformation, and many factors are converging to redefine it in 2024. Chips are reaching 2 nm in size, transistors are approaching the size of a few atoms, and R&D investment requirements are increasing. Despite reaching the absolute physical limit of chip miniaturisation, we can expect breakthroughs in 3D chip stacking, materials science innovations and new lithography forms to increase computing power further.

3. Batteries: the power of new chemistry

Research in this area will likely accelerate in 2024. This is a significant change in battery technology, mainly for electric vehicles. Several technologies related to battery chemistry have already been explored, such as cobalt-free (sodium-ion) and solid-state batteries. The new type of batteries have a higher energy density (i.e. storage capacity) at a lower price than traditional batteries, making them independent not only of cobalt but also of lithium, nickel, or graphite.

4. Space technology

A return to interest in space technologies may become a driving force for new scientific discoveries and help solve Earth's most critical challenges. These include monitoring climate threats and disasters and better access to telecommunications. The New Space Age is driven not only by government agencies but also by private entities, from startups to corporations. It is supported by various technologies such as 5G, advanced satellite systems, 3D printing, big data, quantum computing.

The first topic that will ignite people's imagination in 2024 will include accelerating the above-mentioned innovations and supporting technological projects in the field of sustainable spacecraft propulsion (electric or nuclear). The second is new satellites in low Earth orbit (MEO – Medium Earth Orbit), i.e., orbiting the Earth at a distance of 2,200 to 22,236 miles, potentially to be used for seamless communication and safe quantum transport.

5. Multimodal GenAI

Multimodal systems can understand and generate multiple data types simultaneously. By combining different kinds of data such as text, images and audio, GenAI will lead to more innovative applications in the realm of virtual assistants and chatbots, especially emotion-driven virtual assistants that can detect and respond to human emotions. These advances can significantly impact customer service.

Summary

As we continue to evolve and make revolutionary progress in 2024, more and more leaders will be focused on the future and increase funding for AI processes, research and development, training programs and more. I you want to be up to date with the next transformations made by GenAI in different areas, follow our YouTube channel Beyond AI, where we discuss latest AI innovations!