7 AI Trends To Watch In 2024

Artificial intelligence (AI) is a fast-developing field that has rapidly evolved. This is with breakthroughs and innovations emerging every year. AI technologies integrate into every aspect of our lives, from the smartphones we use to the cars we drive. Based on an article published by Techjury, 35% of companies are currently utilizing AI.

In comparison, 42% of companies consider exploring AI for future implementation. As AI continues to break barriers, it will undoubtedly impact every industry and aspect of our lives. The artificial intelligence market was worth US$ 119.78 billion in 2022. It is anticipated to grow to $1,591.03B by 2030, with a CAGR of 38.1%.

This article will explore seven AI trends to dominate the industry. As we journey down, we expect that AI will continue to:

  • Shape the future of technology.
  • Revolutionize the way we live and work.
  • Point towards sophisticated and more capable systems that can automate tasks.
  • Understand natural language.
  • Learn from data.
  • Drive innovation.
  • Impact businesses, industries, and individuals around the world.

Automation and Robotics

One of the most significant trends in AI is the development of Automation and Robotics. Automation has been around for decades with recent advances in machine learning and robotics. It has made it possible for machines to perform more complex tasks. They are becoming more advanced and capable of performing more complex tasks, such as:

  • Manufacturing.
  • Logistics.
  • Transportation.

According to research, approximately 60,000 mobile robots were sold in 2020, up more than 25% from the previous year. According to analysis, about 2.1 million mobile robots will be shipped by the end of 2025. Almost 860,000 of these robots arriving in 2025 alone. Automated systems can work around the clock, reducing the need for human intervention and increasing productivity.

Additionally, automated systems can perform tasks that are dangerous or impossible for humans to do, such as working in hazardous environments or performing precision surgeries. This year, we can expect to see more sophisticated robotic systems that can work alongside humans in various industries.

It is from manufacturing and logistics to healthcare and hospitality. One area where automation is likely to have a significant impact is transportation. Self-driving cars have developed for years, but we may see them become more mainstream from now on. This innovation has the potential to change how we travel entirely. It could significantly reduce the number of accidents caused by human error.

Natural Language Processing and Natural Language Generation

Natural Language Processing (NLP) and Natural Language Generation (NLG) are critical components of AI. They allow machines to understand and communicate with humans. NLP will enable machines to learn human language and make decisions based on natural language input. While NLG would enable machines to generate human-like language. These technologies are already being used in the following ways:

  • Virtual assistants.
  • Chatbots.
  • Voice assistants.

In 2022, the size of the global natural language processing (NLP) market was $18.1 billion. Market growth is expected at a CAGR of 26.54% from 2022 to 2028. This brings the total value to US$ 74.3 billion. The report notes the increasing demand for NLP applications. Particularly in the healthcare and retail industries, is fueling the market’s expansion.

This year, we expect to see more sophisticated NLP and NLG systems. The intelligence of chatbots and virtual assistants will increase. They can understand the context and generate more complex responses. They are making it easier for customers to get help without talking to a human agent. In healthcare, NLP and NLG systems will help doctors and nurses. Communicating more efficiently improves patient well-being and outcomes.

Machine Learning

This is a subset of AI. It enables machines to enhance performance without explicit programming by learning from data. Machine learning algorithms use statistical techniques. To identify traits in data and use those traits to make predictions and decisions. Machine learning is already used in many industries, including healthcare, finance, and marketing.

Allied Market Research reports the global machine-learning market is expected to grow. This is at a compound annual growth rate of 39.2% from 2020 to 2030. This year, we can expect to see more advanced machine-learning algorithms. It can process and analyze vast amounts of data quickly and accurately.

Advances in machine learning algorithms and hardware will allow machines to process data even faster and more accurately. It makes them more effective at identifying patterns and making predictions. Finance is one area where machine learning will have a significant impact by analyzing financial data. Machine learning algorithms can assist investors in making informed decisions regarding market trends. Furthermore, machine learning can identify financial fraud and other illicit activities.

Virtual Assistants

Virtual assistants have been around for years. Virtual assistants like Siri and Alexa have become increasingly popular in recent years. These AI-powered assistants allow users to access information and perform tasks with minimal effort. Virtual assistants can perform a variety of functions, such as:

  • Setting reminders.
  • Making phone calls.
  • Playing music.
  • Answering some customers’ queries etc.

This year we can expect virtual assistants to become even more ubiquitous and widely adopted. These assistants use NLPand NLG to communicate with users and perform tasks such as:

  • Scheduling appointments.
  • Setting reminders.
  • Answering questions.

It will also become more personalized as it uses machine learning algorithms to learn the preferences and habits of individual users.

Virtual assistants will become an essential tool for businesses and individuals by helping to improve productivity and streamline workflows. In addition, they will become more personalized. They use machine learning to learn more about user preferences and habits.

Blockchain

Blockchain technology can transform the way AI processes and stores data. It is a safe, decentralized ledger that stores and shares data transparently and securely. It is used to create tamper-proof records of transactions. It makes an ideal technology for managing data in industries such as healthcare and finance.

The world’s blockchain market is projected to grow at a compound annual growth rate of 67.3% from 2020 to 2027. The increasing demand for secure and transparent data processing and transactions drives it.

Blockchain will become an important part of the AI landscape. Blockchain can be used to:

  • Safely store and share data between different AI systems.
  • Improving the accuracy and transparency of AI-powered decisions.
  • To guarantee the security and privacy of sensitive data, such as medical records.
  • It can revolutionize many industries, such as the healthcare, supply chain, and financial sectors.

Wearable Technology

The use of wearable technologies has increased significantly. In 2023, this rising tendency is anticipated to continue. Notable devices for this are smartwatches and fitness trackers. They allow users to monitor their health and environment in real time. These devices can track everything from heart rate and sleep patterns to environmental factors like air quality and temperature.

The rising demand for health and fitness monitoring devices is anticipated to fuel the growth of the global wearable technology market. It is believed to grow at a compound annual growth rate of 14.6% from 2023 to 2020 at Grand View Research. Wearable devices will become more accurate and personalized. It uses machine learning algorithms to learn the habits and preferences of individual users.

It can be used in industries such as sports and fitness. By helping athletes and fitness enthusiasts track their progress and achieve their goals. Additionally, wearable devices will integrate more with other AI-powered systems, such as virtual assistants and healthcare applications. It will also significantly impact healthcare, allowing patients to monitor their health. Even more closely and provide doctors with more accurate and timely data.

Edge Computing

Edge computing is a trend in AI. It involves processing data closer to where it is collected rather than sending it to a central system server or data center. As a result, reducing latency improves the speed and efficiency of AI-powered systems. Edge computing is already used in autonomous vehicles and smart factory applications.

The edge computing market is believed to develop at a (CAGR) growth rate of 17.8% from 2020 to 2027. Due to the increasing demand for high-bandwidth applications. Edge computing is used in industries such as manufacturing and logistics by helping to improve efficiency and reduce costs.

From now on, we expect to see more AI systems that use edge computing to process data in real time. Advances in hardware and networking technologies will allow machines to process data even faster and more efficiently. It makes edge computing an even more attractive option for AI-powered systems. Additionally, edge computing will become more integrated with other AI technologies, such as machine learning and natural language processing.

Conclusion

AI has already transformed many aspects of our lives. It ranges from the way we communicate to the way we work. This year, we can expect AI to continue to evolve and improve. It brings even more benefits and opportunities to individuals and businesses. The AI trends discussed in this article are just a few sectors where we expect crucial advancements in the coming years, from automation and robotics to natural language processing and machine learning.

These trends can potentially transform industries such as healthcare, finance, and transportation, and we expect to see more breakthroughs and innovations in the coming years.

As AI continues to improve, it will undoubtedly impact every aspect of our lives. It will be interesting to observe what future advancements and breakthroughs it brings.

About The Author

Scroll to Top
Share via
Copy link
Powered by Social Snap