Top 5 AI Trends Transforming the Business World in 2024-2025

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Alex Shatalov Data Scientist & ML Engineer

In recent years, we all have seen how capable AI is. 2024 is the high time to use these capabilities in full. 

Artificial intelligence advancements are fast and numerous, so you may feel lost in this storm of progress. If so, we highlighted five main AI trends you should keep an eye on this year and illustrated them with successful market cases. But first, let us talk numbers.

The Five AI Stats You Should Know in 2024

What exactly do we mean when saying AI is booming right now? The hype around artificial intelligence trends in business is real, and it is not just our fantasy. Let’s have a look.

• AI market size will reach 306 billion USD in 2024, adding 27% to the previous year.
• The total number of artificial intelligence users will extend to 314 million people, growing by 24% year-to-year.
• By 2030, AI will contribute 15.7 trillion USD to the global economy. It is more than China’s and India’s current contributions combined. 
• 55% of businesses report they use AI in one or more functions. 
• 57% of workers believe artificial intelligence will change the way they work. 

Key AI Trends to Watch in 2024-2025

Smart technologies progress so fast that you can easily lose your focus. We have chosen five main AI trends you should not miss in the upcoming year and illustrated them with cases from our portfolio. 

These trends are likely to change business operations in the years to come.

Trend 1: Generative AI Goes Mainstream

In 2023, big tech introduced game-changing AI tools that transformed how we work and find information, as these advanced systems used generative AI that can autonomously produce new and diverse content, based on patterns learned from existing data.

In 2024, machine learning generative models are reaching new heights. More and more businesses will adopt creative AI tools to streamline creative processes, optimize costs, and increase productivity by up to 40%. Step by step, generative AI applications become one of the top AI trends in business and our mandatory co-pilots for creative tasks.

Generative AI can in fact help your business in many ways.

Generative AI refers to a class of AI techniques and models that are created to generate new data or content that is similar to, but not necessarily identical to, existing data. Such systems can create new information based on patterns and knowledge learned from large datasets, such as text, images, audio, and more.

Exploring MLOps Use Cases: 8 Real-World Examples and Applications Click to read

Why choose Generative AI for your business?

Content Generation and Customer Engagement: Generate personalized content (text, images, music, video) and recommendations to increase customer engagement and loyalty.

Cost Efficiency: Automate repetitive tasks, reducing operational costs and freeing up resources for strategic initiatives.

Adaptability and Customization: Develop fine-tuned or customized solutions for specific business needs to adapt the technology to your unique requirements.

Competitive Advantage: Use generative AI to explore novel ideas, create unique offerings, giving your business a competitive edge through innovation.

Find out how much it costs to build an AI app Click to read

Resource Optimization: Complement human capabilities with generative AI, optimizing resource allocation and increasing overall productivity.

Data-Driven Insights: Utilize generative AI for in-depth data analysis, providing actionable insights for informed decision-making.

Personalization and Customer Satisfaction: Tailor products, services, and marketing efforts to individual customer preferences to higher customer satisfaction and conversion rates.

Our Generative AI consulting services are designed to optimize operational efficiency and drive innovation across various industry sectors.

Market Example: AI-Powered Banking Digital Assistant for a UK Commercial Bank

Our client, a leading UK commercial bank, sought to revolutionize its digital services by leveraging advanced AI technologies. The project aimed to enhance operational efficiency, automate routine tasks, and elevate the overall customer experience through the development of a financial digital assistant.

We built smart AI software to automate routine tasks in banking operations and developed secure on-premise software for searching and filtering sensitive information.

Eager to learn how your business can thrive with gen AI? Let's find out together! Schedule your call with CHI engineers

The implementation of AI chatbot and smart filtering attracted and engaged new customers, enhancing user experience. Project success translated into an impressive 33% revenue surge in FY2022, highlighting the positive impact on the client’s financial performance.

Read this case study in full via the link.

Trend 2: AI Chatbots Speak Out

Powered by intelligent tech, chatbots rapidly advance from basic client service providers to proactive virtual assistants. Today, they can understand natural speech, foresee questions, and make recommendations, becoming one of the key AI trends for businesses. AI chatbot security is also critical in their development, as businesses aim to protect user data and ensure secure interactions.

In 2024, the global chatbot market will grow with a 25.9% CAGR and reach 8.43 billion USD. We will witness the omnichannel presence of AI chatbots, further integration with voice assistants and smart devices, and even better personalization. 

Beyond Conversations: Exploring ChatGPT Capabilities in Business Read more

Why choose AI chatbots for your business?

24/7 Availability: Provide round-the-clock customer support, ensuring that your customers receive assistance and information at any time, regardless of time zones or business hours.

Cost Efficiency: Operate routine and repetitive inquiries, reducing the workload on human agents. This leads to cost savings by optimizing labor resources and allowing human agents to focus on more complex tasks.

Quick Response Times: Provide instant responses to customer queries, eliminating long wait times and improving the overall customer experience.

Scalability: Handle multiple conversations simultaneously, making them highly scalable. As your business grows, chatbots can efficiently manage increased customer interactions without a proportional increase in costs.

Data Collection and Analysis: Collect valuable customer data during interactions to gain insights into customer preferences, behaviors, and common issues.

Multichannel Support: Integrate across multiple communication channels, including websites, social media, and messaging apps, providing a seamless and unified customer support experience.

Improved Customer Engagement: Provide interactive and personalized experiences and contribute to increased customer engagement, fostering a positive relationship between the customer and your brand.

Market Example: Interactive AI Chatbot in a Mobile App

This chatbot works in the form of an animanted character, significantly boosting user engagement.

Modern artificial intelligence chatbots are smart enough to build up an emotional connection (yes, it has gone that far) with human users, which creates unique opportunities for brands in various niches.

Our client, a telecom company, decided to revive customer relations and deliver a new mobile app with an AI chatbot in the form of a cute animated mascot. The character can inform customers about the company’s services, respond to their queries, and tell a joke. Generative AI development was instrumental in creating this chatbot, allowing it to learn and adapt based on user interactions, enhancing its ability to engage meaningfully. As any other chatbot, this one learns a lot and continuously broadens its vocabulary with new words and even can change its behavior.

The audience warmly welcomed such an interactive innovation. Now, the chatbot processes 30% more queries at much lower operation costs. And customer conversion rates are projected to grow by at least 8%.

Read this case study in full via the link.

One More Market Example: AI Voice Assistant in a Geosocial Networking App

This app allows users to combine their online and offline activities thanks to geolocation features.

Another exciting innovation is chatbots with voice recognition functions. In 2024, 8.4 billion digital voice assistants are expected to be in use, and they all need an intelligent part behind them. 

Our client decided to launch a new geosocial networking platform employing a GPT-powered voice assistant. The chatbot recommends venues and events and responds to user queries. It understands English and Vietnamese and can translate street signs and names. This convenient interactive experience is particularly helpful for use on the go. 

Read this case study in full via the link.

Trend 3: Facial Recognition Systems Become More Powerful

With face recognition technology reaching near-perfect accuracy, its global market is expected to grow by over 5.7 billion USD next year, adding about 14%. Facial recognition software development is advancing rapidly to meet the increasing demand for more sophisticated applications.

So now, facial recognition software is in high demand in many security-focused industries like banking, healthcare, and retail. But it is surely not the limit. In 2024, more breathtaking tech applications will appear on the market. Think of passport-free airport security controls, contactless payments, or street security solutions.

Why choose facial recognition software for your business?

Security: Enhance access control and ensure a secure environment by using facial recognition for authentication.

Convenience: Simplify authentication processes for customers without the need for physical cards or passwords.

Fraud Prevention: Use facial recognition to verify customer identities during transactions, reducing the risk of fraud.

Improved Marking: Gather valuable insights on customer demographics and behavior to tailor marketing strategies and enhance product placement.

Navigating the Nuances: Ensuring Accuracy in Facial Recognition Read more

Personalized Customer Experience: Make your business services more personalized and offer them based on customer preferences and profiles.

Time and Attendance Tracking: Streamline time tracking and attendance monitoring, cutting administrative overhead.

Data Analytics: Get data for analyzing customer behavior, foot traffic, and other metrics, aiding informed business decisions.

Market Example: Face Recognition System for Photographers

Such a solution helps detect specific children on photos.

Our client takes professional photos in schools and kindergartens, which means nearly a thousand photos daily. Then, parents have to filter photos of their kids. Imagine how challenging it is with this number of images! So, the client decided to call smart tech for help.

Our team researched, designed, and developed a facial recognition system that can find all photos of a certain child. This is how it works:

• A photographer uploads all the photos to the cloud;
• Parents find and check a couple of photos with their kids;
• The system finds the rest of the kid’s photos in no time. 

The provided solution can now detect and recognize faces of different sizes and at various angles, distorted with emotions and partly overlapped. It is enough to streamline photographers’ creative work and save parents’ time.

Read this case study in full via the link.

Trend 4: Machine Learning Boosts Business Automation

​As technologies evolve, AI business automation systems are becoming powerful enough to deal with complex operations. At the same time, ready-made AI models allow engineers to build more affordable solutions for startups and small businesses. Automation can now enter any door.

Why choose Machine learning automation for your business?

That’s what you can gain after implementing machine learning solutions.

Data-Driven Decision-Making: Machine learning aids informed decisions by analyzing data, identifying patterns, and providing insights.

Cost Reduction: Automation through machine learning cuts costs by minimizing manual labor and enhancing operational efficiency.

Personalized Customer Experiences: Machine learning customizes products, services, and marketing based on individual preferences, boosting customer satisfaction.

Predictive Analytics: Machine learning forecasts trends, customer behavior, and market changes for proactive responses.

Process Optimization: ML optimizes processes like supply chain management, inventory control, and resource allocation, improving efficiency.

Fraud Detection and Security: Machine learning detects anomalies and patterns associated with fraudulent activities, enhancing security.

Competitive Advantage: Implementing ML gives businesses a competitive edge through innovation, data-driven strategies, and quick adaptation to market changes.

Market Example: AI Automation Solution for Logistics

Every international logistic operation usually goes with a package of 10-25 different documents. It takes many hours to find, identify, and process these papers, bringing huge operational costs to the table. Our client, a logistics company from Canada, decided to eliminate this issue with a robotic process automation (RPA) solution.

CHI developers created a tool that uses machine learning, natural language processing, computer vision, Generative AI and optical character recognition (OCR) technologies. What a powerful mix! By removing even one technology from the equation, we would not be able to achieve the desired software quality.

Do you want to make sure that your business will benefit from machine learning solutions? We'll explain the details to you. Talk to our experts

The system does the following:

• enables users to upload PDF files;
• identifies a document category (invoice, bill of lading, proof of delivery, etc.);
• extracts information from documents;
• recognizes signatures and logos of counterparties and reads QR codes;
• learns to distinguish unknown document types and fields.

It is another long-awaited innovation saving hours of human work and, of course, accelerating several operations at once.

Read this case study in full via the link.

One More Market Example: Parcel Tracking Tool

Automation solutions are usually good at sorting parcels. But not always. The problems occur when a tracking code is mechanically damaged, or there is not enough lighting on a sorting station. In such cases, a system cannot see tracking codes well. So, our client, a delivery company, came to us with the idea of an AI tool that could scan codes in unfavorable conditions and maximize the chance for successful delivery.

Our engineers trained a custom neural network to read bar codes on parcels correctly, even if there were some mechanical damages. This innovation is crucial for optimizing postal services while the e-commerce market is growing exponentially every year.

Read this case study in full via the link.

Trend 5: AI-Powered Mobile Applications Are On the Rise

AI intensively goes mobile because of emerging advancements in hardware and software. Powerful mobile chips, developed 5G networks, and stronger edge computing enable users to utilize intelligent tech on the go. So in 2024, more apps will contain generative AI features, and we will see more mobile solutions for content generation, healthcare, and AR/VR experiences.

AI in mobile apps boosts profitability by improving user experience, optimizing app performance, automating marketing, ensuring efficient customer support, efficient resource allocation, and fostering innovation.

Startup Ideas Based on AI Mobile App Development Read more

How can you improve applications with AI?

• Automate repetitive and time-consuming tasks, allowing your application to perform actions without constant manual intervention. 
• Analyze user behavior and preferences, offering personalized content, recommendations, and experiences. 
• Optimize processes, resource allocation, and decision-making, leading to more efficient operations and better utilization of resources.
• Enhance the user interface, making interactions more intuitive, seamless, and user-friendly.
• Process large datasets to identify trends and patterns, enabling predictive analytics.
• Scale to handle increasing amounts of user interactions and data, ensuring your application can grow alongside your user base.

Market Example: Mobile AI Assistant for a Cosmetic Retailer

This is a great recommendation tool for online shoppers.

Our client, a leading cosmetic retailer in North America, decided to arm their customers with an in-pocket AI mobile assistant. This is what it means in terms of features:

• Recommendation system: An advanced algorithm analyzes a customer’s face with computer vision and suggests makeup products and colors;
• Virtual try-on for makeup products: A revolutionary AR/VR feature lets customers test new styles and try on makeup products online and in-store;
• Trend analysis feature scans makeup trends on social media platforms and suggests what will work in every particular case;
• A GPT-based chatbot communicates with shoppers, informs them about promotions and discounts, shares tips, and tracks orders. This is just one example of the transformative potential of Generative AI in retail.

This blend of AI technologies has put the app’s user experience to a whole new level. Think of it as an ideal customer service that you always have by your side. What customer would say no to it?

Read this case sudy in full via the link.

Conclusion

Artificial intelligence has proved it is not just a whirlwind trend but a solid background for future business growth and new opportunities. 2024 is the year of employing generative AI, particularly intelligent chatbots, and enjoying improved face recognition. We also expect AI to find its way to every pocket and open the doors of automation to more businesses. Will it be yours?

It is time to use the benefits of current AI trends to make your business more productive and, of course, successful. If you are looking for a partner to share the road to a new business milestone in generative AI development, we are ready to join. Contact us to make AI trends work for your advantage. 

About the author

Alex Shatalov Data Scientist & ML Engineer

Alex is a Data Scientist & ML Engineer with an NLP specialization. He is passionate about AI-related technologies, fond of science, and participated in many international scientific conferences.