Whether you’re about to start developing a new IT product or plan to expand an existing solution, keeping up with the latest software development trends is vital. Learning what users expect to see in software can help you provide desirable functionality, ideally before your competitors do. And knowing which technologies are on the rise can help you choose the best tools for making your solutions work even better and releasing them faster.

Since every technology takes at least a couple of years to evolve and show results, many tech trends remain the same for years in a row. Examples include progressive web apps, low-code development, the blockchain, AR/VR, and microservices. For this article, we decided to consider technologies that seem the most promising in the near future. Our choices are based on our own market research, leading global tech conferences, communication with clients and partners, and tech community gatherings.

In this article, we take a closer look at five rising trends among technologies that have been on everyone’s lips for the last few years but promise to become even more popular in 2025. This post will be interesting for software project leaders looking for ways to enhance the competitiveness of their solutions.

1. Integrating AI to accelerate software development

Artificial intelligence is already widely used in software development for multiple purposes, assisting businesses in delivering efficient and competitive products. For example, you can implement AI technologies to personalize the user experience, automate repetitive tasks, and help your customers enhance business operations.

Apart from those use cases, AI trends for 2025 include using generative AI to assist IT engineers. In 2023, a McKinsey study showed that GenAI can help software developers complete coding tasks up to twice as fast. Gartner predicts that 75% of enterprise software engineers will use AI coding assistants by 2028.

Common examples of generative AI tools for IT engineers are GitHub Copilot, AlphaCode, OpenAI Codex, GPT-4, and Amazon CodeWhisperer. Developers can also use custom-made or third-party large language models for assisted coding, as well as external APIs like DALL-E for image generation.

Integrating AI into software developers’ workflows can help your team:

• Streamline routine tasks like generating test scripts, wireframes, code snippets, and documentation
• Synthesize data for regression testing and prototyping, reducing the need to use sensitive real-world data
• Review code and suggest optimizations
• Translate code to other programming languages
• Automatically test and debug code

By saving developers’ time, AI assistants can lower the cost of software development in the long run. Also, using AI can help to shorten a product’s time to market, improve code quality, reduce the number of bugs, and enhance the overall user experience.

However, your team must also be aware of limitations:

• AI assistants can’t fully replace human expertise
• They sometimes lead to leaks of sensitive data and intellectual property
• They might show inaccurate results along with data bias

2. Leveling up cybersecurity measures

Another trend for 2025 is putting extra effort into ensuring the security of software products, services, and infrastructure. A few examples of threats to expect are software vulnerabilities, common types of attacks like DLL injections and ransomware, and GenAI-driven cyber attacks. Taking measures to prevent and mitigate cyber attacks makes organizations and businesses increase spending on cybersecurity protection. Gartner predicts a 15% increase on security software spending in 2025.

You can use a rich variety of mechanisms to safeguard your software. However, the following trends can help you ensure security by design:

• Secure SDLC. A secure software development lifecycle is a complex approach that embeds security practices at every stage of development, from planning and design to deployment and maintenance. Its primary goal is to identify and mitigate security vulnerabilities early in the development process.
  
• DevSecOps. The DevSecOps (development, security, operations) approach extends DevOps principles by integrating security into the CI/CD pipeline. It promotes a culture where security is a shared responsibility among development, operations, and security teams. DevSecOps is crucial when you want to implement strong protection mechanisms without slowing down development or delaying releases.
  
• Zero trust approach. Regardless of whether a request to access data, devices, or apps originates from inside or outside the organization’s network perimeter, it’s crucial to verify it before allowing it. Core principles of zero trust include explicit verification, least privilege access, micro-segmentation, and continuous monitoring.
  
• Security testing and audits. One of the best ways to improve your software protection is by testing it. Practices like security testing, penetration testing, and security audits can help you identify a solution’s vulnerabilities and fix them before malicious actors get a chance to exploit them.

By carefully choosing and implementing proven security tactics and mechanisms, you can significantly enhance your solution’s protection. From the business perspective, this reduces security, financial, and reputational risks.

However, your team must continuously maintain and update all security measures to ensure their efficient work. It’s also crucial to make sure that those measures don’t worsen the user experience by interrupting processes and regularly asking for too many verification steps.

3. Using high-performance languages like Rust and Go

Programming languages evolve with time, being enhanced with new capabilities and advantages. For example, Python has become a great choice for software solutions that require extensive and secure API integration capabilities. And C++ has a reputation for helping to deliver products with rich scalability.

Whether your project requires building a new solution from scratch or adding new functionality to an existing one, it makes sense to assess which programming languages your team is familiar with. Here’s why you should keep an eye on trends in programming languages:

• The bigger the community around a language, the more helpful the tips and open-source solutions. More community support can potentially help your team more quickly overcome challenges during software development.
• A programming language’s popularity often leads to the creation of more helpful third-party tools. Your team can integrate those tools into your project, extending your product’s capabilities and accelerating its time to market.

Although popular languages like Python, C/C++, and JavaScript remain in leading positions in the TIOBE Index (as of November 2024), languages like Rust and Go are continually improving their ratings and have made it into the top 15.

Rust has been voted the most beloved language in a few StackOverflow surveys for a reason. Software engineers often mention that this is a memory-safe language, meaning it reduces memory-related and security risks. Moreover, Rust is praised for its speed, security, and performance. Project leaders often choose this language because software written in Rust consumes less energy than the same solution written in JavaScript or C#. And thanks to interoperability features, Rust can be relatively easily added to projects written in other programming languages.

Go was built for projects related to networking and infrastructure but is now used for a variety of applications, from cloud-based apps and DevOps to AI and robotics. Go is supported by a rich ecosystem of libraries and tools, which makes it relatively easy for your team to enhance your software with additional functionality. Moreover, this language is highly portable, helping developers build cross-platform applications.

4. Enabling IoT technologies to provide comprehensive solutions

Another of today’s top trends in software development is the rise of IoT technologies in different projects and industries. According to the State of IoT Summer 2024 report, there were 16.6 billion connected IoT devices by the end of 2023, expected to grow to 18.8 billion by the end of 2024.

With rising interest in devices and wearables, it’s no surprise that we should expect further demand for skilled IoT developers. There’s a need for specialists who are able to build scalable and secure applications that can manage the influx of data from IoT devices, as well as for engineers who can build custom firmware for those devices. Many businesses whose projects involve connections with

IoT devices and embedded systems strive to deliver efficient IoT software to achieve a strong competitive advantage.

Let’s briefly overview the main areas where IoT promises to help businesses offer connected products and improve operational efficiency in 2025:

1. Industrial IoT. IIoT covers the integration of smart devices within industries like manufacturing, agriculture, energy, and logistics. The main goal of IIoT platforms is to help businesses within specific industries collect, process, and use data faster and more efficiently. Whether you build custom software for your business or create commercial industrial solutions, implementing IIoT principles during software development can enhance operational efficiency, automate processes, and facilitate real-time data analysis for software users.

2. Healthcare and telemedicine. Leveraging wearable sensors, smart health monitors, and other smart devices helps healthcare organizations improve diagnostics, ensure remote patient monitoring, and even accelerate drug research. But to efficiently gather, analyse, and use data, medical organizations require reliable software solutions. Having already been a trend for a few years, healthcare IoT is expected to keep evolving in 2025, enhanced with AI, AR/VR, and big data analysis.

3. Connected cars and vehicle systems. Since the automotive industry is going through a massive shift to software-defined vehicles, there’s demand for software systems that support telematics and IoT devices. If your project is related to the automotive industry, make sure to enable IoT technologies for efficient data processing and the ability to communicate with other software systems.

4. Internet of Behaviours. IoB is a technology that aims to address how data can be interpreted from a psychological and sociological perspective and how to use these understandings to influence or change human behaviours for various purposes, from commercial interests to public policies. Despite its complexity and ethical implications, you can already consider applying IoB technology if you’re working on healthcare, digital marketing, or insurance software. For example, IoB can improve SMM solutions by providing advanced advertisement personalization. In vehicle insurance, IoB driver monitoring data can help insurance companies correctly identify who was at fault in an accident.

5. Preparing for Quantum Computing

Quantum computing techniques combine mechanics, physics, and computing and are expected to allow researchers to solve certain types of problems faster than with traditional computers. Slowly but gradually, this technology is moving beyond university walls to the first stages of real-world adoption in software development. Potentially, quantum computing can assist in solving practical tasks like drug research, cryptography enhancement, and complex dataset analysis.

Different organizations are investing in quantum computing research, striving to overcome the challenges of applying quantum commuting to real-life tasks. For example, JPMorgan is already researching quantum algorithms and applications to address business use cases in finance, AI, optimization, and cryptography. And Airbus is exploring a number of quantum technologies and partnering with external researchers to address complex flight physics challenges.

Moreover, leading tech giants have already presented specialized programming languages and tools for developing and running quantum algorithms, such as Q# from Microsoft, Qiskit from IBM, and Cirq from Google. The global quantum computing software market reached USD 779.2 million in 2023 and is projected to continue growing according to a 2023 report by Component.

Software development companies can start preparing for quantum computing algorithms, exploring potential use cases and getting familiar with potential challenges. This will help your team evaluate whether adopting quantum computing would be truly beneficial for your business.

The most promising use cases for quantum computing in software development include:

• Accelerating the work of ML models, allowing them to learn faster, analyse complex datasets better, and extract patterns more efficiently. In this way, software providers can expect to improve processes like image recognition and natural language processing.
• Running simulations to study atomic and molecular interactions. This could be used in healthcare and pharmaceutical software, accelerating drug research and providing faster time to market for new products.
• Enhancing cybersecurity with advanced cryptographic algorithms that could withstand emerging types of attacks, including ones launched with quantum computers.
• Improving data analysis with cutting-edge computational mechanisms, leading to better classification accuracy and identification of hidden patterns. This could allow software solutions to offer data-driven insights, more accurate predictions, and enhanced decision-making capabilities. Quantum computing could be used in financial modelling, marketing, and other areas requiring data analysis.

The biggest expected business benefit of using quantum computing in software development is a significant enhancement in software competitiveness thanks to fast calculations and innovation-driven features.

Things you should consider when think about implementing quantum computing include:

• Research time. Your team will need time to get familiar with the technology, define relevant use cases, and prototype a solution.
  
  
• Managing expectations. Your research might not show enough business value to your project to continue with quantum computing implementation.
  
  
• Mitigating quantum threats. Malicious actors tend to leverage the newest technologies to advance their attacks, and we can expect them to try doing the same with quantum computing techniques. To prepare for that, consider adopting principles of cryptography agility, enabling your software to switch between different cryptographic algorithms with minimal impact on operations.