Even though various sectors of the economy have been using AI for many years, these days the term is not used by anyone except the lazy. The hype is partly due to the public release of ChatGPT, which allowed people to use AI in their daily lives, saving them time and effort on many routine tasks.
Artificial intelligence refers to the ability of a computer or machine to imitate the abilities of the human mind, which often learns to understand and respond to language, decisions and problems.
Artificial intelligence brings to mind images of robot assistants, creative machines, and for some, scenes from their favorite sci-fi movie. The reality, although not so futuristic, is not far from this. The capabilities of artificial intelligence are of interest not only to people, but also to business, so the size of the market for AI technologies in 2023 was about 241 billion US dollars, and by 2030 it is expected to grow significantly and exceed 1.8 trillion US dollars.
Every day there are fewer and fewer people who have not yet been touched by AI in any of its forms. If you order a product from an online store, then on the way to its production, you are probably assisted by some complex equipment controlled by artificial intelligence. The website you use is most often monitored by artificial intelligence-enabled software, collecting all your activity so the seller can get back to you with a personalized offer.
This article will tell you more about where artificial intelligence is being used, how AI is helping humanity, and what to expect from the use of AI and machine learning technologies in the near future.
How is AI used now?
According to Statista, the AI market size will grow from US$241.8 billion in 2023 to nearly US$740 billion in 2030 (in other words, a compound annual growth rate of 17.3%). Meanwhile, according to Next Move Strategy Consulting, its value will increase 9 times by 2030, reaching approximately US$1.85 trillion.
Indeed, the AI market spans a huge number of industries, including healthcare, education, finance, manufacturing, media and marketing. The pace of implementation and adaptation of this technology is becoming increasingly rapid throughout the world, and competition is also growing. Chatbots, image-generating AI, mobile apps are all examples of major solutions that will propel the development of AI in the coming years.
Europe, for example, has an extremely dynamic technology sector that strongly supports the development of artificial intelligence. Funding for startups specializing in this technology totaled more than $1.4 billion at the end of 2022. Many of the largest economies in Europe are leaders in the development and implementation of AI and are even ahead of global dynamics (for example, Asian countries, the USA).
Which industries are most likely to use AI advances?
Healthcare
AI has been transforming the healthcare and pharmaceutical industries for several years now. Johnson & Johnson and Moderna have even used artificial intelligence tools to develop their COVID-19 vaccines. But then we could not yet think that we would use Chat GPT almost every day.
How can AI be useful in medicine? For example, it excels at processing medical images (X-rays, CT scans, MRIs) to detect abnormalities and diseases with better accuracy and speed than traditional methods used by radiologists. Thus, the introduced technologies have made it possible to speed up the detection of lung and breast cancer in the early stages, as well as tumors, aneurysms and other neurological disorders.
Several drugs have already been invented with the help of AI. One of the first, Insilico Medicine, a company specializing in the use of AI in biomedical research, has created a new drug for the treatment of a fatal disease – chronic pulmonary disease caused by fibrosis.
AI-based virtual medical assistants provide consultations to patients based on their medical history and all previously registered complaints, and also help take medications and make appointments. This type of assistant was developed to provide regular and timely care to patients with diabetes, asthma and other chronic diseases.
At the same time, generative AI helps doctors process patient documentation faster.
Finance
The business area most interested in implementing AI tools is, of course, fintech. The financial services business increased the adoption of AI by 11% for the development of digital products and services. Between 2021 and 2023, companies are focusing their strategies on tools that will help expand their product offerings and improve the customer experience.
Artificial intelligence is being used in finance and insurance to improve the accuracy of fraud detection and financial forecasting. Mastercard analyzes transaction data and detects potential fraud using AI. Financial forecasting models are needed by companies to more accurately predict future revenues and profitability.
At the same time, many companies are using cognitive AI to reduce the time spent analyzing contracts, invoices and other documents. With these solutions, important information is automatically extracted from them, reducing decision time, thereby opening up new business opportunities.
For the banking industry, the most important advantage is the quality of service. Thus, some banks have already introduced virtual assistants to increase customer satisfaction. For example, Bank of America virtual assistant “Erica” checks their account balances, handles fund transfers, and schedules payments. A Russian example of a virtual banking assistant is “Oleg” from Tinkoff.
Artificial intelligence technologies have the potential to transform the financial industry by improving the accuracy and speed of decision-making, reducing costs and improving the customer experience.
Game industry
One of the key AI technologies used in the gaming industry is machine learning. Machine learning is used to develop intelligent game characters (NPCs) that can adapt to player actions and make decisions in real time. To achieve this, the game “Middle-earth: Shadow of Mordor” uses the Nemesis system, which allows enemies to remember the player’s actions and develop their own personality, which makes the gameplay more dynamic and unpredictable.
Natural language processing (NLP) is used to create interactive dialogues with NPCs. This allows characters to respond to players’ questions and commands in a more natural and varied way.
Generative AI models are actively used for procedural content generation. In No Man’s Sky, the developers used AI algorithms to create game planets with a variety of flora and fauna. This is an example of how technology makes it possible to create vast and diverse game worlds without the need to manually design every element, saving significant time and resources for businesses.
AI algorithms are also used to improve the quality of graphics and animation. Nvidia’s Deep Learning Super Sampling (DLSS) system uses deep neural networks to improve resolution and image quality in games. DLSS analyzes low-quality frames and converts them into high-resolution images, allowing you to achieve smoother, sharper graphics without significantly increasing the load on your hardware.
AI analyzes player behavior, thereby optimizing the gaming experience. For example, developers can use player behavior data to adjust game difficulty. In Left 4 Dead, the AI dynamically changes the difficulty of the level, choosing the right number and strength of enemies to keep things interesting and suspenseful.
Manufacturing
Energy and manufacturing primarily rely on computer vision systems to predict machine and plant failures. They are capable of detecting defects such as cracks, chips or other non-compliance with standards. Promptly identifying and correcting problems on production lines improves production efficiency and reduces defects, which in turn reduces costs and improves brand reputation.
In the energy industry, AI is used to manage networks and optimize energy consumption. Smart control systems distribute energy depending on peak loads and predict the need for equipment maintenance, which reduces the risk of accidents and increases energy efficiency.
AI can also improve human safety in industrial settings.
What type of AI is most commonly applied?
Narrow AI. This type of AI is designed to perform very specific actions or commands, hence its name. ANI technologies are designed to process pre-existing data and cannot acquire skills on their own. To perform these tasks, they often use machine learning and neural network algorithms, which we discussed in the article MLOps as a methodology: how is it different from DevOps and DataOps?
For example, natural language processing (NLP) is a type of narrow AI because it can recognize and respond to voice commands, but cannot perform other tasks beyond the scope of its training. Examples of narrow AI include image recognition software, self-driving cars, and AI virtual assistants.
Problems of using AI
One of the biggest challenges associated with artificial intelligence is whether it is used ethically or morally. This also includes the issue of copyright.
It is problematic to ensure the confidentiality and security of data that is used to train and operate artificial intelligence systems. In healthcare, AI requires access to patient medical records for AI to work, and in finance, a detailed study of the client’s history and personal payment information plays an important role. Ultimately, ensuring privacy and security is proving to be a major barrier given that the volume of this data is only growing. There have already been several high-profile leaks that exposed the personal information of millions of people, and the use of artificial intelligence may increase the risk of similar leaks in the future.
Moreover, the use of AI for surveillance and monitoring raises concerns about violations of the right to privacy and freedom. For example, facial recognition systems used in public spaces can track people’s movements and behavior without their consent, raising concerns about mass surveillance and potential abuse of power.
Automating processes with AI is leading to significant job losses, especially in areas that involve repetitive tasks. This could lead to increased unemployment and social inequality. People whose skills are no longer in demand will find it difficult to find new jobs. Such changes in employment patterns require the development of strategies to support affected workers and create new employment opportunities.
As it turned out that legislation in the field of AI does not have time to adapt with the development and implementation of AI technologies, which began to create a legal vacuum and uncertainty. It is important to develop international standards and norms that promote the responsible and safe use of AI, while protecting the rights and interests of people.
To sum up,
We learn and achieve new discoveries in various fields thanks to machines that learn from our own data. This fact makes AI an invaluable source of information and an indispensable tool for adapting to consumer behavior and demands.