Discover the latest Artificial Intelligence Tech Trends for Business in 2024 and how they’re shaping industries. Explore key insights, innovations, and strategies to stay ahead in the rapidly evolving landscape of AI technology.
We’ve been keeping an eye on AI technology trends since 2018 as a company that uses AI. Here are some general AI trends and AI application trends that will change business in 2024.
Trend Description Impact on Businesses
Generative AI Dominates the Market Generative AI models excel at creating new content, like text, images, code, and music. Businesses can leverage this technology for content creation, design, product development, and marketing campaigns.
LLMs Power Up Virtual Assistants and Chatbots Large Language Models (LLMs) enable more natural and engaging interactions with chatbots and virtual assistants. Improved customer service experience, increased lead generation, and enhanced personalization.
Narrow-Tailored AI Solutions Promote Adoption Businesses are increasingly adopting specialized AI solutions designed for specific tasks and industries. Increased efficiency, cost savings, and improved decision-making in targeted areas.
AI Enhances Security and Surveillance AI-powered systems can detect anomalies, identify threats, and automate security responses. Improved security posture, reduced risk of breaches, and faster response times to incidents.
AI Boosts Real-Time Video Processing AI algorithms enable real-time analysis of video data, facilitating applications like anomaly detection, traffic monitoring, and customer behavior analysis. Enhanced operational efficiency, improved safety measures, and valuable insights from video data.
Explainable AI Gains Importance As AI models become more complex, businesses prioritize explainability to ensure transparency and trust. Increased user confidence, improved regulatory compliance, and better understanding of AI decision-making.
No-Code AI Platforms Empower Businesses User-friendly platforms allow businesses to utilize AI without extensive coding knowledge. Democratizes access to AI for small and medium-sized businesses, fostering innovation and process automation.
Multimodal AI Integrates Diverse Data Sources AI systems can process and understand information from various sources like text, images, audio, and video. Enables richer data analysis, more accurate predictions, and improved decision-making across different contexts.
To reach your business goals, this piece will teach you how to use tools and methods created in areas of AI like Neural Networks, Machine Learning, Computer Vision, Natural Language Processing, and Speech Processing.
The trends we looked at are more useful than futuristic, and small and medium-sized businesses can use them to their advantage. If you need a development team to add AI to your product or make your business processes better, we can help.
In software engineering and AI, we can find good solutions for specific business needs and use AI technology in a way that works best for the product.
Artificial Intelligence Tech Trends for Business in 2024
Generative AI Controls the Market
It is expected that generative artificial intelligence will continue to grow in 2024. This will cause a game-changing shift in the global economy as companies realize its huge potential. Bloomberg Intelligence (BI) study shows that the market for creative AI is about to explode.
In 10 years, it will go from $40 billion in 2022 to $1.3 trillion. Generative AI uses a variety of methods and models, such as diffusion models to create images and transformer-based models to create text.
LLMs are also built on top of transformer designs. These techniques let the system learn from past data and create new data that is very similar to the information that was put in.
As time goes on, more and more companies will start to use advanced generative algorithms because they can reach new levels of capability, usability, and scaling in many areas.
Generative AI has shown its benefits in many areas, such as predicting demand, improving supply chains, and creating new products. Its ability to look at very large numbers, find trends, and give useful information has made things run more smoothly and helped people make better decisions.
Read more: How to Make Money with AI in 2024
One example is Generative Adversarial Networks (GANs), which are popular because they are mostly used for fun. FaceApp, which was made for the Western market, and ZAO, which was made for the Eastern market, are two well-known examples.
When generative AI was used in healthcare, it led to big changes in both patient care and practical efficiency, especially when it came to managing medical supplies and keeping track of medical tools.
It’s the same with customer service. Natural Language Processing (NLP) technology can help make internet searches, spell-checkers, and voice helpers more user-friendly.
Generative AI For Developing Software
Generative AI is a key part of making code solutions for site builders and AI platforms that don’t need any code. Automated code generation speeds up the development process, making it easier for more people who don’t know a lot about coding to create complex AI solutions.
Generative AI solutions come with pre-built AI site makers and algorithms, which makes AI creation more open and easy for everyone. There is a wide range of site builders, from simple ones with pictures and text that are made automatically and unique color schemes to more complicated ones with AI web crawlers that are trained to do specific tasks.
People want no-code AI tools when they don’t need to be able to change the way the goods they make very much. These choices are often used by businesses to help computer programs find and sort pictures, items, poses, sounds, and more.
Some of the most well-known settings are Google Cloud Auto ML, Google ML Kit, Runaway AI, CreateML, and MakeML. The plan below will help you get your business ready to use AI tools that don’t require you to write any code.
Generated AI also plays a big role in integrating application programming interface (API) ends, which makes it easier for developers to make complex apps. It is expected that software development kits and APIs will get better in 2024.
This will allow developers to improve pre-made AI models by using AI apps like RAG as a service. By adding intelligent helpers and summary tools that give access to up-to-date business information, this customization will let companies get the most out of AI’s output.
LLMS Turn on Virtual Helpers and Chatbots
There is more talk about both LLMs and AI in the media and everyday life thanks to ChatGPT. A lot of us are already using ChatGPT when we need to in our daily lives. Large Language Models (LLMs) can help with answering customer questions, figuring out how people feel about things, helping human workers, and finding trends in customer behavior when they are used in a structured way in business settings.
A lot of people use digital helpers that are built on LLMs, and this is often their first experience with AI. One thing that makes these AI solutions stand out is that they can connect with people on a human level.
For example, a robot that is powered by AI does more than just follow set orders. It focuses on understanding what customers want and how they act. These tools make it easier to communicate at a level that is very close to talking to a person in person. This makes sure that important information is sent in a way that is easy for the customer.
Chatbots are being used more and more in fields like healthcare, banking, marketing and sales, travel and leisure, and more. This makes it much less necessary for people to do manual work.
A medical robot, for instance, can easily help a patient make an appointment with their doctor, answer frequently asked questions, and tell them when it’s time to take their medicine and work out.
Because of how fast life is these days, it’s easy to see why AI-powered virtual helpers are so popular. Talking to AI helpers is a good way to get information without taking time away from other things you need to do. In the end, improvements in Natural Language Processing (NLP) and speech recognition have made personalized automatic solutions much more useful. For instance, the NLP-based Question Generation system shown in the next movie keeps the safe verification process from making mistakes.
Increased Adoption of AI is Facilitated by Task-specific AI solutions
Narrow AI is a term for AI systems that are specifically made for doing specific, well-defined jobs or uses. These systems are great at doing certain tasks within a limited range, which encourages businesses at all levels to use AI.
AI is generally flexible, but narrow AI solutions are better for specific business goals and easier to make, especially if you don’t have a lot of money.
We expect the use of more specific AI products to grow in 2024. That being said, ChatGPT is a great general AI helper, but it probably won’t be the best choice for every job. This means that by 2024, there should be AI platforms made just for researchers, writing generation tools made just for writers, modelling platforms made just for designers, and other specialized apps.
In the future, AI solutions will be improved to handle specific use cases, either by using a unique model or a process that is built around it. Companies can become stars in the next era of technology by becoming the best at one thing and then adding more products to their line. In this case, an initial offering that is more limited and specific is more likely to do well.
AI Makes Surveillance and Security Better
New technologies based on artificial intelligence have made it possible for security systems to reach a higher level of quality. Face and voice recognition, human pose estimates, and automatic picture analysis can now be used together with video security for biometric identification.
AI-based security and tracking systems let customers and companies work with more precise settings and find things that need to be dealt with when they show up. Video recording and analysis software help keep public and private areas safe by finding possible threats in places with many people.
Automated identification of theft and dangerous behavior can quickly call the police, which could save lives.
AI-powered apps can now tell a person’s age, gender, and mental state just by listening to their voice. Biometric face recognition is also an important part of keeping things safe in general.
Furthermore, it is important to note that hackers and dishonest users have access to a wide range of technologies. Spoofing attacks, in which someone pretends to be someone else to get illegal benefits, happen all the time.
For this, they might use harmful programs, fake pictures, or personal information that has been stolen. It’s important to keep in mind that a lot of Internet methods don’t have ways to check the source of a request.
That’s why software should have strong and safe identity verification features to make sure that user encounters are real and safe. So, even in 2024, people will still want to work on making new, improved anti-spoofing methods.
AI Accelerates Real-time Video Processing
In the past few years, the live-streaming market has grown a lot. This is due to general internet access, improvements in video-streaming technologies, the popularity of smartphones and other mobile devices, and the rise of social media platforms.
The CMI Team did a study on the market and found that the global Live Streaming Market will grow at a CAGR of 28% from 2023 to 2032. It is expected to be worth USD 256.56 billion by 2032.
For real-time video streams to work well, data transfer must be correct and video processing delay must be kept to a minimum. Data flow handling is one of the most important parts of this process that uses artificial intelligence.
A modern real-time video processing system includes a neural network model that has already been taught, methods for implementing user scenarios, and cloud infrastructure. This connection is a must for real-time streaming to work quickly.
Improvements to algorithms and parallelization of processes can speed up video processing. If you want to quickly handle high-quality videos, the pipeline design is the best choice. It also lets you add effects like face recognition and blurs.
AI blurs and removes backgrounds in real-time video by building a model that tells the difference between the person in the frame and the background. We need a neural network to do this job.
Read more: Artificial Intelligence in Fintech
You can use one of the models that are already out there, like BodyPix, MediaPipe, or PixelLib. Next, you need to connect the model you chose to the right framework and set up the best way to run it using WebAssembly, WebGL, or WebGPU.
More Top AI Tech Trends for Business in 2024
The next part will go into more detail about how artificial intelligence is changing in different fields. Let’s look at how AI trends are changing and affecting different industries, looking at the new technologies, uses, and effects in each one’s specific setting.
AI Makes Healthcare Diagnosis More Accurate
The newest AI technologies have completely changed how healthcare apps are made. Recent changes in the healthcare field point to the following places where AI could be used to great effect:
- Wearable and non-wearable health gadgets for individuals that track important health indicators in real-time and give personalized feedback, acting as personal health coaches.
- The use of digital twins and AI to automate and customize drug and vaccine development research and testing.
- Improvements in AI-based solutions for IoMT, making medical tools more useful, and the creation of “Software as a Medical Device” (SaMD) to get the most out of medical devices.
- Using AI to separate parts of medical images like MRI and CT scans makes the study of anatomy data more efficient.
Diagnostics is another area of healthcare where AI has a lot of potential. Researchers and medical professionals used AI to find many types of diseases, like cancer, diabetic blindness, and EKG abnormalities, and to figure out what factors increase the chance of heart disease.
Take the study that was done in South Korea as an example. It compared how doctors and AI diagnosed breast cancer. The AI-based diagnosis was 90% more likely to find breast cancer masses than doctors were to do so (78% vs. 90%). Also, AI was better than doctors (74% vs. 91%) at finding early breast cancer.
As with Alzheimer’s disease, dementia is a healthcare problem because its signs come and go and are hard to pin down. The use of artificial intelligence to help solve this problem has led to the creation of speech-processing models.
These models make it possible to find communication and logic problems that show how likely someone is to get this disease.
Three areas of artificial intelligence are linked to using AI to diagnose dementia: Natural Language Processing (NLP), Machine Learning (ML), and Neutron Networks. These can be used to both find dementia early and track how it gets worse over time.
For early identification, neuropsychological testing can even be done on recorded telephone conversations, and classification models help keep an eye on how the patient’s state changes.
Using the newest AI technologies has led to the creation of new ways to diagnose cancer using AI, which gives doctors full and varied knowledge. It takes a lot of time and work to do the hand review because experts use whole slide imaging (WSI), which has a lot of disorganized data. The issue with inspection by hand can be successfully fixed with AI.
The Human Pose Estimation (HPE) system is another use of AI. HPE is a computer vision job that tries to find and exactly follow important body parts. It is very important to find these spots when looking for motion patterns, specific joint positions, or the general pose.
HPE can be used for many things, such as detecting body movements, making tools for correcting posture, supervising exercise, and AI-powered fitness advice. Users can do different workouts and give and receive real-time feedback thanks to human pose estimates and natural language processing tools.
AI-powered Visual Inspection in Manufacturing
A revolutionary trend in manufacturing is AI-driven visual inspection, which uses AI technologies to improve quality control and inspection processes in industrial settings. Computer vision, machine learning, and other AI techniques are used together in this method to simplify and improve the inspection of goods, parts, or processes.
AI-powered eye inspection is used to check whether parts are ready to be put together and to find problems on the moving belt. Automation of research and decision-making will be the key to making it easier for manufacturing companies to find flaws.
Using data from cameras and IoT monitors, AI software can figure out what kind of problems there are with parts or finished goods.
By using computer vision powered by AI, it is easy to find and take back faulty goods, which helps meet production needs and maintain high-quality standards. This makes sure that the production processes run smoothly with few interruptions.
AI Gets Better In Retail
AI data analytics helps business owners make decisions that are better, faster, and easier to understand. Businesses can make more accurate predictions, make decisions faster, come up with better marketing strategies, improve the efficiency of their supply chains, and make customers happier with their purchases thanks to AI-powered demand forecasts. This all leads to total organizational excellence and market competitiveness.
McKinsey research shows that companies that use AI to manage their supply chains before others have seen 1.5 per cent lower logistics costs, 35 per cent lower inventory levels, and a 65 per cent rise in service levels compared to companies that started using AI later.
In the past few years, AI has been used to change many things in the business field. Traditional delays in stores can be fixed, and customers will be happier and save more time with self-checkout, which is made possible by automating cash machines with computer vision.
With the help of the newest AI technologies, there is a wide range of automation solutions that can be used to make shopping better. These range from partially automated systems like vending machines to fully automated “grab-and-go” stores.
The growth and popularity of virtual changing room technology in stores is another trend that needs to be mentioned. This cutting-edge virtual fitting solution uses AI, picture processing, and machine learning to produce an accurate reflection of how clothes fit and look on users with a range of body types. With this new technology, buyers can try on clothes from the comfort of their own homes, so they can see how the clothes will look before they buy them.
Approaches that work well in shopping can also work well in dining. Innovations focus on the main steps of a digital purchase, such as figuring out who the buyer is and keeping track of what they do, recognizing the product, making sure the purchase is real, and paying for it.
Applications of AI in Marketing
Artificial intelligence is getting better at making content, which is a great example of progress in the field that this piece talks about. Generative AI is the field that studies and develops this area.
Natural Language Processing (NLP) is the field that studies and develops methods for making up text. This area of artificial intelligence is all about making models that make search engines better, help business apps write text, and help robots get better.
AI smart search and product suggestions are linked to another trend. By using AI to look at old data, it is possible to guess how performance will be in the future based on many factors.
More importantly, looking at what people like best can help you give them ideas for items they might like. AI can also help businesses make site search results more relevant to each customer by looking at their past search records, how they use the platform, and the features of the product.
AI is also making marketing tools better. It has almost everything, from social media posts to emails that are sent automatically. This new technology could make it possible to make changes more quickly, run more micro-campaigns, target smaller groups, and do other things.
More people are using marketing tools driven by AI, which could change what people expect. People may start to expect ads that are quicker, have better segmentation, and even more hyper-personalized material.
Applications of AI in Fintech
The use of AI in Fintech has led to several interesting trends that have changed the face of the business.
With AI in Fintech, financial companies can improve their security and stop scams before they happen. AI-powered algorithms make it easier to spot scams by analyzing transactions in real-time to find and stop questionable activities.
Overall, this makes the financial industry safer and makes it easier for managers at all levels to make decisions. A biometric identity that is supported by AI is becoming more common in Fintech to make sure that users are who they say they are. Voice identification, palm reading, and facial recognition all make banking operations safer.
Credit scores and screening are being changed by intelligent document processing that is driven by AI systems. AI helps make better loan choices by looking at a wider range of data from non-traditional sources.
This leads to a more accurate risk assessment. With AI, it’s easier to deal with a lot of paperwork. To make changes to regulations, financial officials have to handle a huge number of compliance papers by hand.
To do this, they need skilled workers from various business areas. The OCR technology can make these tasks a lot easier by handling document management for payments, accepting receipts, and adding new clients.
In the Fintech business, AI is also used to make legal compliance and reporting easier. Automated systems make sure that complicated financial rules are followed, which cuts down on mistakes and boosts efficiency.
Fobots in Fintech
Fintech companies are using robots and virtual helpers powered by AI more and more to improve how they connect with customers. These tools give you personalized help, make customer service easier, and answer your financial questions.
AI can also help people make decisions about their money. Financial apps that use AI can help you plan your finances. These tools give users personalized advice and help with planning and investing suggestions by looking at their spending habits and financial goals.
In automated investing, AI programs are used a lot to make quick business choices based on data. These programs look at news, market trends, and other pieces of information to figure out the best times to make trades.
Smart planners, which are backed by AI, give automatic financial advice based on algorithms. These tools look at market trends, client tastes, and risk profiles to make investment plans that are both specific and cost-effective.
Taking into account the use cases we talked about earlier, we expect the area of artificial intelligence to keep making progress. Solutions for analysis and predictions like chatbots, helpers, NLP tools, robots, and devices are already commonplace, and this trend is only going to get stronger. Also, two topics—AI’s ability to be explained and AI’s morals—are likely to get a lot of attention soon.
Artificial Intelligence that Can Explain
In the past few years, AI has mostly been about scaling—exploring what’s possible by using a lot of data and computer power to train these models. But as these models are used in the real world, the most important question comes up: why? Why do the results that these models give you make sense?
Explainable AI (XAI) tries to make AI technologies easier for users, lawmakers, and other important people to understand so that people are more likely to trust, accept, and use them. Its uses are wide and include many areas where making choices has important results.
In the field of banking, for example, XAI can explain how credit scores are calculated for people who want to borrow money. In healthcare, it can help both doctors and patients understand the decisions made by medical tools that are driven by AI.
Ethics and Rules for AI
Regulatory and legal requirements are growing in many areas, such as banking, healthcare, and the auto industry. This makes it harder to use AI. The goal of these rules is to make sure that use is fair, accountable, and moral.
Realizing how important it is for AI systems to be open and answerable, governments and governing bodies are taking steps to stop biases and unfair results, making sure that AI is used responsibly.
As the use of AI grows, there will be more and more rules in this area. As an example, creative AI like Chat-GPT has certain requirements. These include having to say that the content was made by AI, building protections into the model to stop it from making illegal content, and giving brief descriptions of the protected data used for training when posting. Because of this, companies should be ready to change quickly.
Even though AI is still seen as a new “magic pill” for startups, more and more big companies are starting to use it to stay competitive and meet changing customer needs.
Many businesses, both new and old, don’t have a clear plan for how to use artificial intelligence successfully, though. With AI product advising services, the gap between business and technology could be bridged, making it easier for AI solutions to be really useful.
As we navigate the evolving landscape of Artificial Intelligence Tech Trends for Business in 2024, organizations must embrace innovation, adaptability, and responsible stewardship. By harnessing the transformative power of AI technologies and staying attuned to emerging trends and developments, businesses can unlock new opportunities, drive sustainable growth, and chart a course toward a prosperous and inclusive future.
