Biggest Artificial Intelligence (AI) Trends in 2023

The dominant part of the whole technological industry consists mainly of artificial intelligence and machine learning which are increasingly becoming a part of humanity's everyday life. Developments allow companies to obtain desired goals with less time and money, making important decisions quickly and creating new innovative products as well as services.

By the end of 2022, many companies predict that businesses will be creating and producing about 35 AI projects to achieve certain goals. In fact, the average annual market growth for AI and ML is 44 or $9 billion. In recent years, AI and machine learning technology have received a strong boost in development which has given several major breakthroughs. Let's try to figure out the biggest AI trends 2023.

Global overview of technology in the retail market environment

Many analytics companies expect global retail AI to register a CAGR of 35% by 2026.

COVID-19 pandemic was the impetus for the active development of technologies and caused a demand for online shopping. The reason is that many people have switched to online platforms to make various purchases. This channel became one of the only available and convenient ones. Changes have provided an opportunity for sellers, large consumer goods companies to take the initiative in the area of development which are intertwined with digitalization.

With the help of artificial intelligence, it is possible to make the right decisions quickly in the following areas of business:

• marketing;
• e-commerce;
• product management.

It is a part of the opportunity reducing the imbalance between ideas and their implementation. According to the U.S. Department of Commerce, there's a chance of nearly $6 trillion in retail sales in 2023.

In fact, machine learning techniques are generally used for artificial intelligence. When it comes to commerce and retail sales, this methodology is helping to provide users with a personalized experience and interactive task environment.

According to IBM research, the integration of AI in commerce and manufacturing will increase from 40% to 80% within 3 years. Along with this, the technology receives ongoing investment which gives an opportunity for improvement and development. The reluctance of some large corporations to innovate can slow overall market growth. Another problem for trend development in 2023 is likely to be a shortage of skilled employees who know how to implement AI into business.

Key market AI trends 2023

Experts are confident that in the near future the area of product optimization will begin to take a significant share of the market. As a result, any recommendations and planning in the retail business will be the domain of AI. With the development of big data analytics, there will be an increasing adoption of AI-enabled devices and programs.

There are technologies already in place working with AI and big data warehouses, including machine learning.

Among them are:

1. Human speech processing.
2. Deep learning.
3. Programs for automated decision making.

New AI technology has a number of advantages for operation and usage in the retail industry.

Among the pluses, the Consumer Technology Association highlights:

• cost savings;
• high productivity;
• quick decision-making to solve business problems;
• rapid delivery of goods;
• the growth of innovation (smart bots, autonomous vehicles).

According to expectations, the described benefits can improve users' analytics and behavioral experience, thereby increasing the importance of optimization.

In 2020, Baker Hughes launched an AI-based application. It gave operators the ability to see production data from wells in a real-time environment. As a result, forecasting of oil and gas production has improved and methods have been used to optimize a number of operational processes with a positive update on production rates.

In the next few years, North America is probably going to dominate the market, as it is the most active in using AI technology. This is largely because of the presence of a number of fully industrialized countries including the U.S. and Canada. They are directing investments to modernize retailing and solutions to specific challenges in this area. North America was one of the first to adopt AI to optimize the supply chain of goods and services. With the help of innovation, it is easier for retailers to support customers, manage their business and understand customers' buying patterns.

In order to increase sales and attract new customers, AI technology is being integrated into offline and online stores. Global brands and corporations are actively engaged in optimizing the products and developing.

The leaders of this market:

• NVIDIA;
• Intel;
• Salesforce;
• Sentient Technologies;
• Microsoft;
• Google;
• IBM;
• Amazon Web Services.

In 2020, the active use of AI in various fields began. Kenco Logistics has launched DaVinci AI. This product provides a wide range of analytical services covering all supply chains. The technology can be used to obtain predictive information, which is later translated into actions. Mastercard introduced Drive Through solutions for merchants to simplify in-store shopping, working with minimal contact and maximum party engagement.

The best artificial intelligence trends 2023

Now let's look at the biggest trends in AI and machine learning in 2023. They will help you to get ideas about how to control business and other areas of activity.

Hyperautomation

Hyper-automation means the processes of applying innovative developments to speed up and simplify tasks with minimal use of human power and knowledge. This concept is often referred to a digital or intellectual automation.

Lots of modern companies have to work with large flows of information and automation is needed to retrieve it effectively. Data knowledge and data analysis can be found everywhere, so these days, these tools are becoming more accessible to everyone.

Professions that have been in great demand in this area are:

• application architect;
• machine learning specialist;
• data engineer;
• enterprise architect.

Data Science is suitable for financial institutions, manufacturing, insurance companies, marketing firms, etc. Hyperautomation is necessary to perform research in order to increase a firm's profit.

The main advanced technologies in this direction are:

1. Robot-assisted process automation (RPA).
2. Artificial intelligence and machine learning (AI/ML).
3. Cognitive process automation.
4. Correct Process Management Software (iBPMS).

The main idea is to combine innovations in order to simplify, design and automate business processes instead of applying methods that are based for a narrow activity.

Specific methods of using hyper-automation in a company may vary. For example, a conversational AI and RPA company can be used to improve customer support. This will help automate responses to customer emails, as well as improving CSAT scores. Improving the productivity of a company's employees can be done by incorporating technology into labor-intensive processes. Through this implementation, manual work is reduced and productivity is improved. System integration will enable the company to integrate any digital technology into business work processes.

Cybersecurity apps

One of the important components of today's world is information security. AI and ML technology make it possible to create new methods of reliable protection and all cybersecurity becomes risk-free and automated.

The main methods of improving cybersecurity with machine learning and AI are:

1. Artificial Intelligence is suitable for classifying, processing, clustering and filtering incoming information as there is a lot of information data in such area.
2. Machine learning provides the ability to analyze past information, provide the best solution methods for the future and present. With past data, algorithms provide instructions to find threats or malware. AI and ML help disrupt anyone who wants to infiltrate the system.
3. Implementing technology will systematize information according to set parameters, allowing different information to be matched and track any threats.
4. AI will simplify the audit of information protection ways, allowing you to quickly learn about the effectiveness of implementing restrictions. This protects the users of a particular company.
5. AL and ML quickly find threats, harmful software, creating a security platform to scan large amounts of information.

With the help of AI in 2023, enterprises strengthen cloud migration methods, improving performance with large amounts of data.

Intersection of AI and ML with loT

Today's devices, services on the Internet are becoming smarter and more secure through the introduction of AI and ML. Gartner published research suggesting that at the end of 2022 more than 80% of Internet of Things projects in corporations will have AI and ML. All devices must be connected to the Internet in order to respond in a timely manner to any situation based on the information gathered.

In the model described, the importance of innovation lies in the ability to quickly acquire information to determine patterns and detect anomalies. All this works with the help of intelligent sensors, additional devices.

Such data includes:

• temperature;
• pressure;
• humidity;
• the cleanliness of the air;
• sound changes;
• vision recognition;
• computer vision.

The intersection between technologies and loT can be found in the smart home, the city, or on wearable devices. The later include smartwatches, bracelets, health monitoring apps, etc. It also covers AR / VR devices, and wireless headphones. Implementation in a smart home will allow automatic control of light, temperature, and electrical appliances. In addition, a machine innovation like this doesn't just do everything automatically but adapts to the habits of the homeowner, which adds more support to users.

AIoT is also being used in smart cities, creating a comfortable environment. The technology keeps an eye on order, safety, and convenience of life. Developments are added to smart transportation, lighting, or energy system. In industry, AI and machine learning simplify the analysis of information that is needed to optimize all activities, supply chains, and logistics.

Business forecasting and analysis

Compared to the methods described above, forecasting and analysis in business using AI is the easiest thing to do. AI and ML make it possible to make highly accurate forecasts. Financial companies are already using technology today to know the demand for currency pairs, based on market conditions, and show people's behavior, and fear levels in real-time. This makes it possible to provide the financial and technical sector with the right amount of supply to meet demand.

The bloom of augmented intelligence

The next AI trend for 2023 is to combine machines and people to enhance cognitive productivity.

By 2023, according to Gartner, 40% of infrastructure and operations teams will start using automation with AI to achieve increased IT productivity. As a result, half of the complex work will be done by machines.

With the help of augmented intelligence, different platforms quickly do information gathering with its structuring by templates. The data is taken from different sources and the company gets a complete picture of the product, its customer, etc.

This AI trend will be great and will grow strongly in 2023 in the financial services, healthcare, travel, and commerce sectors.

IT trends not to expect in 2023

There are several trends capable of shaping the technology market according to ABI Research analysts, as well as trends that are attracting a lot of attention, investment but are less likely to affect the market in 2023.

Analysts suggest that there will be no boom in edge computing, only that it will continue to increase in numbers. The methods of using edge computing and financial dependency are directly related to the 5G network, both privately and publicly. The price loyalty of such services for the development of edge computing has not yet moved into the global phase of reality, so the overall development is planned slower than expected.

Neither are companion robots gaining large-scale adoption. For many years, leading developers and companies were forced to abandon commercial offerings or close their own stores. Only in 2021 investment in such a sector began to flow again and then the potential of AI-powered technology was reconsidered. Much interest was generated by Amazon's Astro robot but despite the potential in 2023, it may not have the breakthrough expected by analysts and industry experts.

The next trend that could not happen in 2023 is the inability to bring back machine sales volumes. Chains of supply cannot close the demand yet due to the lack of semiconductors. The U.S. is actively developing in this direction but there is no quick solution to the problem at this time. ABI Research does not expect to return to $90 million in new car sales until mid-to-late 2023.

In addition, the semiconductor shortage is being addressed until 2023. The main challenges involve additional capacity, inflationary effects and the real demand. The main risks are in the social and political aspects, as a result, there is no opportunity to launch a new production capacity in time.

According to a study by IDC, worldwide spending on AI development in 2022 could reach $432.8 billion, an increase of 19.6% and in 2023 the mark will overcome 500 billion. The main focus at the moment is to create technologies and their implementation in business projects to improve logistics, process technology, and planning.

AI programs in languages, machine-assisted communication, and machine vision are being actively created. The costs of providing these technologies and services for them are growing faster than the costs of software and this trend may continue throughout 2023.

All 5 of the AI trends described are gradually emerging and will continue to evolve in 2023. Other features that can be implemented and added are machine learning in voice and support and digital information regulation. AI and ML help large companies, traders to understand the market sentiment, stress levels, and other factors that work together to help them make quick decisions. AI and machine learning play an important role in managing and supporting the correctness of complex tasks for the success of any activity. Roboticization of processes has shown flawless results, eliminating human error, mistakes, etc. The active and large-scale development of industrial areas further increases the need for trends and developments in artificial intelligence and machine learning.