Artificial Intelligence is an umbrella for innovation and technology. Businesses across the world are looking to plan, invest, and adopt Artificial Intelligence. In fact, AI is improving industrial processes and is helping design and develop smart products. That is why, AI is expected to be one of the most disruptive technologies impacting most industries and businesses. In future as the AI market expands we shall expect a much greater impact. Also, we shall witness the use of AI development in major business processes continues to grow over time. Thus it is important that ever to learn and know about emerging AI trends and technologies in 2023
Well, we all have an understanding of Artificial Intelligence, and most of us have used its products in some way or the other. Thus there is a lot more to AI than just maverick technology disrupting industries. Truly it is making smart devices smarter, data more informative and valuable, and cloud-based tools more effective. Truly AI will disrupt business models, bring in new ways of working, and leverage a complete digital transformation. Thus we believe in the coming time more applications are going to embrace the power of Artificial Intelligence.
But what does this mean for you? In simple words, it means keeping an eye on and observing the latest trends and technologies in Artificial Intelligence. So whether you are an AI developer or a full-stack development company, it is crucial to know and keep up with these emerging trends and technologies in AI so you can also keep pace with your skills.
Here are the top 10 emerging trends and technologies in AI that you must know about in 2023.
Top Emerging AI Trends & Technologies to Know in 2023
AI allows computers and other devices to understand, examine, and adjust to their ecosystem. Therefore the devices can use software algorithms to carry out tasks efficiently, that would otherwise require human involvement. As a result, AI allows machines to recognize their ecosystem, predict, learn, and provide responses on their own. Notably, the emerging AI trends and technologies allow us to contribute more smartly to business processes and activities.
-
Large Language Models (LLM)
A Large Language Model (LLM) is a machine learning model that can carry several natural language processing functions. It includes creating and categorizing text, providing a response to the queries in a conversational way, and language translation. The machine learning model uses deep learning algorithms to process and recognize the natural language. It can also help in understanding difficult textual data, figuring out structures, and correlations between them, and creating new content that is logical, and grammatically correct. Additionally, LLMs can accomplish many language-related tasks including, language translation, examining sentiments, carrying chatbot conversations, and more.
Use Cases:
- Develop conversational chatbots like ChatGPT development.
- Answer customer queries and frequently conversationally asked questions.
- Translating content into different languages.
- Create text for product descriptions, summarize blogs or articles, and so on.
- Categorizing and identifying huge text data for more effective refine text and analysis.
- Observing customer responses from emails, social media posts, and product feedback.
-
Predictive Analysis – Top AI Trends & Technologies
One of the top emerging trends in AI in 2023 is predictive analysis. As the name suggests, ‘predictive analysis’ refers to the ability to predict upcoming events and trends across industries based on statistical data and information. Thus predictive analysis can help in carrying out strategic decisions. The predictive analysis utilizes the data, statistical algorithms, and machine learning techniques to find out the possible outcomes of futuristic events based on historical data. The concept is to analyze what has happened and predict the possible future outcomes. Thus predictive analysis can be highly beneficial in making one-step-ahead decisions and creating data-based strategies. Check our ai tools in 2023.
Use Cases:
- The predictive analysis utilizes statistics and modelling methods to forecast future outcomes.
- The predictive models are highly useful in making weather forecasts, building futuristic video games, translating voice-to-text messages, predicting customer decisions, and building investment portfolios.
- Useful in industries and disciplines. Predictive analysis is useful in making crucial decisions, such as insurance and marketing.
- Financial services can use predictive analysis to look into transactions, trends and patterns.
- Supply chain systematically is used to predict and control inventory levels and prices.
-
Speech Recognition
Speech Recognition is another popular emerging trend and technology in AI that will continue to leave an impact in 2023. Speech recognition understands human speech and translates it into an easy-to-understand computer format. Thus it bridges the gap between humans and computers. The technology recognizes and converts human speech into different languages. With the help of speech recognition computer programs can respond to spoken commands. Thus speech recognition is the technology that allows hands-free control of smart devices and equipment.
Use Cases:
- Enhance safety while driving by enabling voice-activated navigation systems and search abilities.
- Integration of virtual agents especially in mobile devices.
- Speech recognition can be used by customer care executives to figure out common call patterns and their issues.
- Voice-based verification also adds higher levels of security to our daily lives
-
Extended Reality
Extended Reality (XR) consists of all the immersive technologies including Virtual Reality, Augmented Reality, Mixed Reality, and everything in between. These immersive technologies either blend the virtual and real-world or a completely immersive world. It is a significant technological trend right now as it empowers the virtual world in different ways. By creating an immersive experience which is almost like the real world, XR is hugely popular among gamers, medical specialists, retailers, and other industries.
When it comes to extended reality, gaming is one of the major fields that can experience major changes shortly.
Use Cases:
- XR has a huge application in the retail industry. It gives opportunities to customers to try clothes before purchasing.
- Provide training tools to soldiers, healthcare officials, pilots, and others that can be useful.
- Professionals can work remotely and connect to home offices from anywhere.
- Marketing by connecting to customers or sellers through XR.
- Walk through spaces in the real estate business.
- The entertainment industry can have a huge impact through immersive technologies.
-
Robotic Process Automation (RPA)
Similar to Artificial Intelligence and Machine Learning, Robotic Process Automation is another emerging trend/technology that is used for automation. RPA also known as software robotics configures a robot to automate tasks, analyse, and communicate information. Thus the technology helps in automating fully manual or partial business processes that are routine-based or repetitive. This type of automation utilises rule-based programs to carry out business process activities that are high-volume, allowing human resources to focus on tasks that are of higher importance.
As a result, as of 2021, nearly 20% of businesses have started utilising RPA, which has led to a 13% growth in the adoption rate. If you as a techie are looking forward to learning about emerging trends and technologies in AI then RPA is certainly one of them.
Use Cases:
- Automated customer care systems can sort queries quickly and smoothly.
- Invoice processing with RPA can help with timely payments.
- End-to-end sales automation tasks with RPA.
- RPA can automate the payroll system.
- Store, sort and organise customer information.
- RPA can help in processing faster refunds.
- Streamline the recruitment process with RPA.
-
Deep Learning – AI Trends & Technologies to Look Forward
Deep learning is another emerging trend in AI that has been widely used for knowledge discovery and predictive analysis. Deep learning is particularly dependent upon artificial neural networks. In simple words, it is a machine learning technique that trains computers from databases and information, which comes naturally to humans. For example, deep learning is the main technology that allows driverless cars to work, recognise stop signs, follow traffic rules, and so on. With the impact of AI, deep learning has been gaining immense popularity lately. In deep learning, computers learn to perform categorisation tasks straight through images, texts, or sounds. And many times deep learning models can achieve higher levels of accuracy, many times even better than humans. The deep learning models are trained using large labelled data and neural networks that consist of many networks.
Use Cases:
- Deep learning trains computers for face recognition and looks out for content in images.
- Identify speeches, and text to address conversion and processes of natural language.
- Language translation with deep learning.
- Text mining which runs a deep analysis of the text.
- Recommendation engines such as Netflix, etc. run on deep learning.
-
Virtual Assistance & Chatbots
Virtual assistance and chatbots have become very popular applications of Artificial Intelligence and are one of the leading trends in 2023. In fact, ChatGPT and Google Bard are one of the most popular use cases of chatbots powered by AI. These virtual assistants and chatbots are designed to not just understand the basic set of commands but also understand the user’s behavior and intent. As a result, they can provide natural and close-to-human-like answers. Notably, the use of chatbots is prevailing in most industries including retail, eCommerce, healthcare, sales, finance, marketing, and others. You read about ChatGPT vs Google Bard and ai in art.
The emergence of AI-powered virtual assistants is also increasing. Interaction with the virtual assistant allows users to get natural responses while indulging in daily activities. Truly, the utilization of Natural Language Processing (NLP) has increased the functionalities of custom automated solutions.
Use Cases:
- Wearable and non-wearable devices that track health, and provide reports, and real-time feedback.
- Telemedicine is an AI tool that provides quick access to medicines.
- Virtual assistants can manage bank accounts.
- Chatbots can manage digital claims and benefit insurers and investors.
- The majority of HR tasks can be automated through chatbots and virtual assistants.
- Chatbots use machine learning to segment the travel industry.
-
Edge Computing
Edge computing is a disruptive technology which refers to the different networks and devices close to the user. It brings computing as close to the source of data as popular, thereby, lowering latency and the use of bandwidth. In other words, edge computing refers to running lesser processing in the cloud and shifting those processes to local places, like a user’s computer, IoT devices, or an edge server. Thus it allows processing at higher speed, and volume, leading to action-oriented results. In addition, edge computing allows businesses to improve the management and utilization of physical assets, and build new interactions, and human experiences.
Use Cases:
- Since edge computing brings points closer, it eliminates latency.
- Deployment of data servers saves a lot of bandwidth.
- Local storage and local servers reduce congestion.
-
Internet of Things (IoT)
The Internet of Things is certainly the most emerging technology in the decade. These days most devices or things are wifi enabled, which means they can be easily connected to the internet. The Internet of Things is a network of various connected devices. These devices within the network can interact with each other, gather data, and transfer it across the network without any human interference. At present several devices use IoT, from tracking smart devices, remotely monitoring home doors, turning on and off devices, augmented reality glasses, and much more. With such a wide array of applications for IoT devices, it is predicted that by 2030, the use of IoT devices will be nearly USD 29 billion which will benefit iot development company.
Use Cases:
- IoT for read-only remote asset monitoring.
- IoT-based process automation.
- Remote asset monitoring and control.
- The IoT supply chain for vehicle fleet management.
- Track locations with IoT.
- IoT for quality control and proper management.
- IoT for plant and asset performance optimization.
-
Natural Language Processing (NLP)
We cannot mention Artificial Intelligence and not mention NLP in the list of top 10 emerging trends and technologies in AI. Natural Language Processing is an intersecting application of Artificial Intelligence and machine learning. It is mainly the automatic manipulation of natural languages, like speech, text, translators, and voice assistants. Natural language processing makes it possible for computer programs to understand languages similar to humans. Thus it allows computer programs to understand and learn human behavior to perform repetitive tasks seamlessly. For example, checking grammatical errors, summarising, sentiment analysis, machine translations etc. Natural Language Processing can analyse a large set of information and data including social media posts, reports, and statistics, which can be critical to businesses. While NLP can also help machines make more sense, faster, and with greater accuracy.
Use Cases:
- Classify texts.
- Sentiment analysis.
- Text extractions allow you to pull out particular pieces of information from the text.
- Machine translation.
- Analyse structured data.
- Automatically analyze customer feedback.
- Automate customer support tasks.
Final Words: Emerging Trends & Technologies in AI
Artificial Intelligence is certainly one of the most disruptive technologies that continue to leave a greater impact on almost every industry. Recently we have witnessed the hype around ChatGPT which continues to be one of the most talked about applications of AI in 2023. Thus has also led to wider utilization of ChatGPT development across different industries. The applications of AI are already paving the way to disrupt most sectors, and we are truly going to witness more use cases of AI and its trends soon. Thanks to the emergence of AI, most businesses are adopting AI development solutions into the business processes for automation and many other possible use cases.
In this article I have discussed the top 10 leading AI trends and technologies in 2023, that will continue to grow and leave an impact on major industries. What is your point of view on AI? Do you think other AI trends can impact the market? Let me know in the comment section below.