Marc Andreessen rightly said, “Software is eating the world.” In every industry vertical, software development is changing the lives of people, and we expect to be fast and proactive with technological progress. Enterprise Software dominates the market, with a projected market volume of $292 billion in 2024. The revenue is expected to show an annual growth rate of 5.27%, resulting in a market volume of $858.10 billion by 2028.
The growth showcase software development is literally driven by Moore’s law, wherein innovation and evolution are part and parcel of the journey. Every other year, we get to see new languages, changing trends, software architecture, methodologies, containers, etc. Start-ups to leading enterprises need to remain aware of trends that they can consider during development.
Hence, in this blog, revolutionary trends in software development are summarized, enabling businesses to build modernized, high-quality software that performs to the notch. Explore the latest trends to stay aligned with the current market inclinations and surprise the world with innovative software.
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The software development landscape is changing with the technological progress and emergence of new technologies such as AI, AR, VR, IoT, ML, and others that are transforming the world. Developers are using these technologies at scale to build incredible software solutions.
OpenAI, as a leader in AI research and technology, has developed powerful tools and models that are reshaping how software is designed, developed, and maintained. OpenAI’s models, like GPT-5 and Codex, generate code based on natural language descriptions that streamline software development. Developers can describe what they want, and AI can generate the code, reducing development time and lowering the barrier to entry for coding.
OpenAI models are also used to review code for errors, security vulnerabilities, and best practices. The suggestions for improvements and optimizations help write more robust and efficient code. The AI-powered interfaces allow developers to interact with software systems using natural language commands and queries. It simplifies the process of configuring and managing complex software systems.
When you want to translate code from one programming language to another or porting applications to different platforms, the technology makes it easier. In the same vein, rapid prototyping, document generation, bug detection and its resolution, and code reusability get the upper hand. OpenAI’s estimated revenue in 2024 is $1 billion, largely attributed to ChatGPT+ subscriptions, which are predicted to grow 5 times by the end of 2024.
Human augmentation is one of the future trends in software engineering. It’s about the integration of technology into the human body or cognitive processes to enhance or extend human capabilities. This trend has profound implications for software development and engineering, as it creates new opportunities and challenges for various domains, from healthcare to entertainment.
Wearable technology, brain-computer interfaces, AI-powered software, AR/VR technology, and cybersecurity are leveraged at scale to deliver safe and amazing human augmentation experiences. However, it requires a deep understanding of user needs, ethical considerations, and the integration of advanced technologies to deliver meaningful and responsible augmentations.
The Internet of Things is transforming the IT industry by connecting physical devices, objects, and sensors to the Internet, enabling them to collect and exchange data. It generates massive volumes of data from connected devices that are processed and analyzed to derive insights. It involves edge computing, where data processing occurs closer to the data source, that is, on the device or at the edge of the network.
IoT applications can handle a growing number of connected devices that help design scalable architectures and accommodate device expansion without compromising performance. Well, security is the biggest concern, but encryption, access controls, and device authentication help to protect IoT ecosystems from cyber threats. Software engineers can remotely update device firmware to patch vulnerabilities, improve performance, and add new features without requiring physical intervention.
The Internet of Things demands devices to be innovative. These devices won’t conquer the world, as information without processing means nothing. Intelligent devices are equipped with sensors. These cloud-based applications are used for processing data in two ways- interpretation and transmission. Thus, This trend of software systems is looking promising in many ways.
Non-fungible tokens (NFTs) have emerged as a prominent trend within the blockchain and cryptocurrency space. NFTs are digital assets that represent ownership or proof of authenticity of unique items, such as digital art, collectibles, virtual real estate, and more. As NFTs are built on blockchain platforms, such as Ethereum, that allow NFT companies to build smart contracts and decentralized applications (dApps) to create, manage, and trade NFTs securely.
It promotes interoperability between different platforms and marketplaces that allow NFTs to be bought, sold, and used across various ecosystems. These features have made NFTs find great use across gaming, art and entertainment, digital wallets, finance, real estate, and other industries. According to Statista, the non-fungible token (NFT) market is expected to reach $2,378 million in revenue in 2024 and expected to grow at a compound annual growth rate (CAGR) of 9.10% from 2024 to 2028, reaching a projected total amount of $3,369 million by 2028.
TensorFlow is one of the leading open-source machine learning frameworks developed by Google to provide a robust ecosystem for building and deploying AI and ML models. The futuristic trend is known for its deep learning capabilities. Skilled software developers leverage TensorFlow’s extensive library of pre-built neural network layers and models for tasks like image recognition, natural language processing, and speech recognition.
TensorFlow is designed to work seamlessly on both CPUs and GPUs, making it suitable for training and deploying machine learning models at scale. Artificial Intelligence developers can distribute workloads across multiple devices or clusters for faster training and inference. TensorFlow Lite allows the use of TensorFlow to deploy AI models on smartphones, IoT devices, and embedded systems. It also features TensorBoard, which helps to monitor and visualize machine learning experiments, model training, and performance metrics.
Predictive analytics is gaining traction with the increasing availability of data and the desire to make data-driven decisions. It involves using historical and real-time data, along with statistical algorithms and machine learning models, to predict future outcomes, trends, and behaviors. It allows big data analysts to make predictions with data integration and management, ML model deployment, feature engineering, continuous model training, and scalability.
A plethora of features that enable accurate predictions help big data engineers build recommendation systems, demand forecasting systems in the supply chain, early diagnosis in healthcare, churn prediction in e-commerce, and risk assessment in the financial industry.
The Internet of Behavior, an extension of the Internet of Things is expected to lean towards personalization by gathering data from devices and behavioral analysis of people interacting with devices and applications. The interconnection of devices generates many data points, and they can see their errors, getting visual recommendations for better customer service. This trend encompasses various devices from phones to vehicles, exercise reloads, credit cards, to almost everything else connected to the Internet.
As IoB aims at understanding data better and using it to construct new software from the viewpoint of human psychology, it is all set to become a compelling new marketing platform for tech organizations. IoB’s primary goal is to record, comprehend, analyze, and respond to all forms of human behavior in a way that allows people to be interpreted and tracked using developing technology advancements in machine learning.
The global Internet of Behaviors (IoB) market size is expected to surpass around $3592.6 billion by 2032, poised to grow at a compound annual growth rate (CAGR) of 24.97% from 2023 to 2032.
Blockchain is simply a cloud-based system to store information. Due to the successful adaptations and hype of cryptocurrencies like Bitcoin, Ethereum, and Dogecoin. Founded in 1991, blockchain acts as an open-source database and an underlying network of cryptocurrencies.
From business minds to crypto enthusiasts, blockchain is a solution to all problems related to intelligent data transfer and security concerns. On a blockchain network, anything of virtual value can be traded, tracked, and traced. The popular trend reduces costs as well as risks. Primarily, blockchain is a decentralized structure, and its usage depends upon decentralized technologies in web servers, digital marketing, cryptocurrencies, property records, voting, and banking.
As countries have started to experiment with central bank digital currencies (CBDCs), there will be an increased interest in digitalization and tokenization, and central banks will expand into retail and wholesale CBDCs. It is expected that adjacent technologies will combine with blockchain to create next-level solutions. As far as technology and marketing benefits are concerned, blockchain is definitely the trend of the past, present, and future, as it will be used by 3.9% of the global population in 2024. When we go region-wise usage, 160 million Asian people and nearly 1 million Oceanian people use blockchain technology.
Among all software development trends, Artificial Intelligence and Machine Learning are the most revolutionary. The number of AI solutions developed for the IT industry is constantly increasing.
Whether cloud solutions or high-complexity projects, AI and ML are expected to play significant roles. Artificial Intelligence is considered a considerable growth driver. It has brought layers of problem-solving opportunities in businesses.
The future of artificial intelligence is expected to boost robotics, proactive healthcare, disease mapping, intelligent assistance, driving cars, financial investing, travel, chat tools, natural language processing (NLP), marketing, and social media monitoring. There are already battles going on among nations about the most powerful AI tools. It will be interesting to see what the future has in store for software development, with artificial intelligence as one of the top trends.
Virtual Reality (VR) and Augmented Reality (AR) are among the most renowned trends, especially for gamers. The increasing acceptance and responsiveness of AR and VR are leading us to another dimension of interactivity. It is expected to consolidate and come in two forms: Standalone units and Tethered systems.
The technological advancements and enhancements brought with virtual reality attract consumers and industrialists, and investors are sensing a bright future. The adoption of AR and VR will lead in domains such as healthcare, retail, media, entertainment, automotive, military, defense, aerospace, and transportation. Among commercial applications, AR-based applications are in the highest demand.
As a result of the increased use of mobile devices and the Internet, virtual and augmented reality growth is most expected in mobile gaming and applications. According to market researchers, VR and AR will be at the center of digitalization, and the market will grow exponentially in the years to come. The market revenue is expected to reach $170 billion by 2025, growing at a CAGR of 48% each year.
It’s a catch-all term for emerging technologies such as AR, VR, MR, and everything in between. It’s used for transforming businesses of different industry verticals by replicating the imaginary world over the real world. XR is the future of mobile computing, similar to smartphones of today, that’s creating boundless immersive experiences combining realistic visuals with edge cloud processing, 5G, and on-device processing.
According to Mordor Intelligence, the extended reality (XR) market is expected to reach $105.58 billion in 2024 and $472.39 billion by 2029, which is growing at a compound annual growth rate (CAGR) of 34.94% from 2024 to 2029. The amazing growth led to its increased usage in software development, enabling customers to interact with the real world irrespective of the place they are.
The computing world is witnessing notable advancements in different areas, be it cloud computing, quantum computing, platform as a service, and infrastructure as code, making software development manageable and cost-efficient.
Big data means large chunks of structured, semi-structured, and unstructured data that play a critical role in a business. This data is collected by organizations and is analyzed for further analytical insights that contribute to making better business decisions.
It aims at processing and presenting it by using a set of special tools and sets to make it understandable for users. Businesses understand the significance of big data and are taking advantage of it. Big data can work miracles by taking into account the subject knowledge of a particular business and applying it to the proper sphere.
The advancements of big data are in making strategic decisions, increasing revenue growth, increasing the efficiency of the product, and attaining accuracy in the respective field. These are leading to incredible growth results.
Cloud computing is simply the delivery of computing services over the network- the cloud that includes storage, servers, analytics, networks, and databases. With cloud computing, you get easy access to technology services. Also, there is no need to buy, host, and maintain physical data servers and centers. The entire world is going to move towards cloud migration sooner or later. Currently, more than 80% of small to big-scale organizations are shifting to the cloud, and the number is expected to go beyond 90% by 2024.
Amazon is the biggest public cloud provider right now and the number of cloud computing-based corporations will continue to grow. It is also expected that the trend for multi-computing and hybrid computing will play a major role in the IT market.
It is no secret that quantum computers can process information millions of times faster than traditional computers. Classic computers use bits to store information with just zero or one state. While quantum computers store information in quantum bits known as ‘qubits’, allowing subatomic particles to exist in more than two states simultaneously.
In fields such as material science, agriculture, pharmaceuticals, chemistry, and crypto, quantum computing has proved to be a game-changer. The possible applications of quantum computing in the future are optimization, big data analytics, material science, and machine learning.
Quantum computers are expected to disrupt current technologies and solve previously unapproachable problems by creating feasible solutions. The market of quantum computing is expected to reach more than $70 billion in upcoming years.
PaaS is an amalgamation of web development platforms with an environment in the cloud. As a product is developed, it provides consumers with all necessary tools, such as operating systems, middleware, QA, databases, etc. PaaS reduces the significance of distance and allows customers to control the deployed software applications.
PaaS is definitely one of the most emerging technological trends influencing the entire process structure. With the remote working system getting in trend the programming team members can feasibly work remotely by using the platform as a service. It offers comforting opportunities for exchanging messages and distributing duties among the team.
Working remotely has never been easier with PaaS. The global trend of outsourcing teams is just getting started. New features and advances are already knocking on doors, and a lot of new functions are yet expected as PaaS is contributing to the decentralized structure of outsourcing teams.
Cloud-native technologies are becoming popular for building scalable software in modern work environments such as hybrid cloud, private cloud, or public cloud. They enable software developers to design and operate cloud-developed workloads and avail of the cloud computing model. Businesses are considering cloud-native technologies for accelerating agile software development that facilitates transitioning strategic ideas into full-fledged solution development at speed.
The cloud-native stacks like- DevOps allow developers to insert code for production and use CI/CD for software testing. Built-in scalability of cloud-native technologies enables considering technologies for any software requirements without additional infrastructure design.
Managing computer data centers without physical hardware is the name of the IaC process. Infrastructure as code automates IT infrastructure management using different machine-readable configuration files. The software infrastructure-driven approach frees up the developers from managing and analyzing resources automatically.
The main DevOps approach when used along with continuous delivery, the management gets faster as opposed to manual operations. The entire infrastructure is coded that enable the same version control and automated testing. Also, it ends up relying on the system administrator.
The programming languages leveraged for software development play a vital role in introducing advanced functionalities to the software. Staying current with changes in programming languages helps businesses to keep up with changes for the best results.
The emergence of new programming languages continually shapes the way software developers write code and build applications. New programming languages often come with innovative features, improved performance, and specific use cases that cater to evolving software development needs. New languages for software programming allow experienced developers to experiment and explore novel paradigms, solve specific problems, and push the boundaries of what can be achieved in code.
New programming languages and technology stacks are concise, readable, support parallelism and concurrency, optimized for performance, prioritize security, are interoperable, provide a range of libraries, and enable advanced technology leverage to contribute to the ever-evolving field of software development.
Python is a well-known programming language that has been used for photographing a black hole to machine learning, data processing, and data analysis. Because of its convenience and simplicity, it is one of the most popular programming languages. The buzzing trend is mounting up, with more than 14% of all Stack Overflow queries tagged as ‘python.’
It is mainly used for software development, app development, game development, system administration, web development, and scientific computing. Python doesn’t have issues like a lack of documentation and supporting programming languages or tools. In fact, it supports different cross-platforms such as Oss, Linux, Windows, and Mac flawlessly. Along with being simple to use and write code, it is extremely convenient.
Launched in 1991, Python has seen continuous growth, especially in the 21st century. The growth rate of Python was not easy to achieve and now the popularity is unstoppable. In the upcoming times of artificial intelligence and machine learning, Python will have a huge role, and a shining future is ahead for it in the new edge technologies.
Web 3.0, known as the Semantic Web or Decentralized Web, aims to revolutionize the way information is organized, shared, and accessed on the Internet. Web 3.0 builds upon the foundations of the traditional web (Web 1.0) and the social web (Web 2.0) by introducing new technologies and paradigms. In Web 3.0, data is structured and tagged with semantic metadata, allowing computers to understand the meaning and context of information. Software developers enable semantic data integration using RDF and OWL technologies.
It also promotes the linked data concept, which allows developers to create linked data sets and design APIs that enable data to be easily linked and retrieved across the web. Embracing decentralization, the Web 3.0 software development trend allows developers to build decentralized applications and protocols like blockchain and distributed ledger technology to create trustful, peer-to-peer networking.
Companies can give their users a streamlined experience without building separate apps for specific operating systems with progressive web apps. Progressive Web Apps (PWAs) can operate on any platform that uses a web browser. They are built using languages like CSS, JavaScript, and HTML. PWAs improve customer engagement while enabling cost savings.
Recently, Forbes redesigned their mobile website resulting in a reduced load time from 3 seconds to 12 seconds to now 0.8 seconds. It also resulted in users spending more time on the site with a 43% increase, more ad views with a 20% increase, and more content engagement from readers with an increase of 100%. It shows the huge benefits of PWAs, especially in user retention and conversion rates.
With a low-code or no-code development approach, automated code reviews, legacy system modernization, and DevSecOps, software development is getting simplified, automated, and affordable.
DevSecOps represents the integration of security practices into the DevOps (Development and Operations) process. It aims to make security an integral part of the software development life cycle rather than a separate and isolated phase. It promotes a “shift-left” approach to security, where security considerations are introduced early in the development process, even before the code is written. This proactive approach reduces the likelihood of security vulnerabilities making their way into the final product.
Automation is a key component of DevSecOps that involves automating security testing processes such as Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), and Interactive Application Security Testing (IAST). It facilitates continuous security scanning and rapid feedback to software developers. The continuous monitoring of applications and infrastructure for vulnerabilities enables teams to detect and respond to security incidents in real-time.
With the emergence of FinOps (Financial Operations) and GreenOps (Sustainable Operations) trends, the future of the software industry reflects the growing importance of financial efficiency and environmental sustainability in software development and IT operations.
FinOps focuses on optimizing the costs associated with cloud computing and IT infrastructure. FinOps best practices enable identifying cost-saving opportunities, monitoring usage, and implementing budget controls. The use of showback and chargeback enables allocating the cost of IT resources transparently among different stakeholders, which encourages accountability.
GreenOps focuses on reducing the environmental impact of IT operations and software development by optimizing data centers and infrastructure for energy efficiency. It includes using renewable energy sources, improving cooling systems, and reducing hardware waste. GreenOps also promotes sustainable coding practices, such as optimizing code for energy efficiency and reducing resource-intensive processes.
Outsourcing is emerging as a top software development trend that’s shaping the future of software engineering. Businesses are looking beyond traditional outsourcing destinations to find specialized skills in emerging technology hubs worldwide. IT outsourcing service providers specialize in niche areas of software development technologies, such as Artificial Intelligence (AI), Machine Learning (ML), Blockchain, Cybersecurity, and Augmented Reality (AR)/Virtual Reality (VR).
Accelerated use of DevOps and agile methodology, strict adherence to data security and compliance standards, facilitation of managed services, option for the hybrid model, and AI automation ensure successful outsourcing partnerships. This trend is the future of software development.
Automated code review leverages AI and ML in software development to improve the efficiency and effectiveness of code quality assessments. Automated code review tools analyze code against a set of predefined coding standards, best practices, and style guidelines. They identify issues such as code smells, redundancy, and potential bugs that are instantly reported as feedback, helping software coders write cleaner and more maintainable code.
It ensures code consistency across the project by enforcing naming conventions, indentation styles, and other coding standards. They scan various security vulnerabilities earlier to prevent data breaches and cyberattacks. The code assessment for performance bottlenecks and suggestions for improvements enable performance optimization.
The reduced code review time allows software developers to focus on more complex aspects of code while leaving routine checks to automated tools. Repeating patterns across code reviews are harnessed by intelligent methods to prioritize, comment on, and improve contributions automatically. Recent statistics have found that 84% of the companies have a defined code review process in place out of which 36% of the companies state that automated code reviews are the best way to improve code quality.
The trend of replacing legacy systems is driven by the need to modernize outdated technology stacks and adapt to changing business requirements. Legacy systems, while functional, often lack the agility, scalability, and features required in today’s fast-paced digital landscape. Replacing them involves migrating to a modern tech stack, such as cloud-native architectures and microservices that offer improved performance, security, and maintainability.
When migrated to cloud-based infrastructure, businesses enjoy scalability, flexibility, and cost-efficiency benefits. API-first approach helps seamless integration of legacy systems with modern systems to foster interoperability. The modernization of legacy systems helps revamp user experience and allows software product developers to innovate with new technology integration capabilities.
With growing environmental concerns, software developers are looking for eco-friendly solutions, sustainable software development practices such as green computing, or using the best refactoring practices. The solutions encourage energy-efficient coding practices that minimize server processing, improve performance, and a lot more.
The code is streamlined with software optimization, leading to minimum energy usage, and data processing between systems is reduced with integrations preventing unnecessary data usage. Limiting data storage and tenure till when it’s stored in the system, followed by small-sized data usage, reduces storage and processing needs. Continuous refactoring ensures software remains up-to-date by removing unnecessary features.
Eliminating the reliance on third-party components consuming large resources improves software performance. Also, the hosting services selection must be based on green practices they follow for sustainable development.
The need for software developers has increased rapidly in the past years, so it has outpaced their availability and created a huge gap in supply and demand. It makes low code/no code (LCNC) programming an essential asset for businesses to proceed with feasibility. It helps to create databases and other applications to support agile operations with no prior development training.
The LCNC initiative has gained momentum in the market, mainly in web development like Bubble. It has also paved its way in other areas, such as No-code app development, No-code AI, and No-code machine learning. With lots of mergers, acquisitions, and innovations in LCNC, it is predicted that it will be one of the hotly anticipated fields in the tech world.
One of the principal goals of software development is fighting crackers and hackers. As both hackers and security providers are constantly coming up with innovative technologies to outsmart each other, the cybersecurity sector is moving faster and faster.
The primary reason for data breaches is human error, but the amalgamation of automation and integrated AI with cybersecurity brings tremendous changes. These hybrid security systems detect new attacks and instantly notify admins of any data leak or information leakage.
With the introduction of 5G, data breaches and software bugs are knocking on the door. It is where cybersecurity enters with effective strategies and agile processes. It is expected that software companies will spend more than ever on security assets in the coming years. The top cybersecurity users will be political and industrial sectors and high-profile data-handling companies.
Google built the open-source system to automate software deployment, scaling, and management by grouping containers into logical units. The open-source nature allows developers to avail of hybrid, public, or on-premise infrastructure that enables effortless movement of workloads.
With automated rollouts and rollbacks, Kubernetes applies changes to software applications or their configuration while consistently observing software performance to ensure not all instances are killed simultaneously. When anything goes wrong, changes are rollbacked by Kubernetes, which is quite helpful in the ecosystem of deployment solutions.
For using an unknown service discovery mechanism to modify software applications, Kubernetes provides a single DNS system for a set of Pods and Pods with their IP address that further helps with load balancing.
Software development architecture serves as a foundation for the entire software development process. Different types of infrastructure, architecture, and others make software development resilient.
Distributed infrastructure is one of the latest software development trends that’s driven by the need for scalable, resilient, and highly available systems. It’s changing the way software solutions are developed, deployed, and managed with microservice architecture, containerization, serverless computing, edge computing, and hybrid environments.
Data replication and sharding in distributed databases, fault tolerance, monitoring and observability tools, and security in every layer of distributed infrastructure bring a major shift in software product engineering. However, businesses should be careful with cost management, which requires monitoring resource usage and optimizing the infrastructure to avoid overprovisioning and controlling costs.
Microservice architecture is a prominent trend that involves decoupling services from each other so that they can be developed and maintained independently. Software engineers design services with clear boundaries, well-defined APIs, and minimal dependencies on other services. It facilitates scaling individual services based on their specific resource demands, ensuring efficient resource utilization and cost-effectiveness.
Fault isolation is a key benefit of microservices. When one service fails, it doesn’t necessarily impact the entire system, allowing the design of a resilient software solution with redundancy and failover mechanisms implementation. Each microservice is built using a different technology and deployed independently.
Microservice architecture has become a preferred choice in large-scale enterprise app development. Nevertheless, microservice application design is way more complex than a monolithic application, which goes by one size fits all. Microservices require a set of some of the best practices and design patterns.
The software architecture that has gained a lot of popularity in the past couple of years is serverless architecture. With the groundbreaking AWS Lambda service, Amazon has set the tech world in motion. It introduced a service where the developer has to write the code while the service provider can manage the server. Although criticized by some and appraised by others, software architectures are breaking new tech grounds. It is expected that by the end of 2024, Microservices, Monolith, and serverless architecture will coexist, whether it is for small-scale development or large-scale enterprises where SOA was initially used.
Real-time streaming is gaining popularity day by day. Enterprises are shifting away from the traditional way of Lambda architecture to the more feasible option of Real-time stream processing frameworks. However, in this case, two types of frameworks exist. First is Spark streaming and the other is Apache Flink, led by a Micro-batched-based platform and low latency stream processing platform.
However, Apache Flink edged out Spark streaming when it comes to handling real-time screening situations such as anomaly detection, fraud detection, Ad-hoc analysis of live data, and rule-based altering. Apache Flink is the apparent solution among Hyper-scale cloud providers as it has unmatched capabilities and power in real-time stream processing.
The world is standing at the cusp of the digital revolution, where considering the latest software development trend is all-important to stand high in the competition. Undeniably, the trends are helping businesses to enhance processes, workflow, and operations at scale. However, these software development trends evolve faster than expected, which makes it essential for businesses to be proactive and embrace the trend instantly before the competitor does.
If you are unsure about predicting which trend of software development will help your businesses create a future, connect with the top software development company it will help you know which trend enables software to stay current in the market and stay with you from discovery workshops to final development.
An enthusiastic Operations Manager at TopDevelopers.co, coordinating and managing the technical and functional areas. She is an adventure lover, passionate traveler, an admirer of nature, who believes that a cup of coffee is the prime source to feel rejuvenated. Researching and writing about technology keeps her boosted and enhances her professional journeying.