Looking Ahead – Technology Trends for 2025

Trends in software development

In today’s fast-paced digital landscape, software development is no longer just about writing code. It’s about embracing innovation, adapting to new technologies, and continuously evolving to meet the demands of the market. The tools, methodologies, and frameworks that developers rely on are changing at a rapid pace, and staying up-to-date with these advancements is essential for success.

Here are 15 such trends in software development to watch for:

1. AI-Augmented Software Development

Beyond integrating AI to enhance the capabilities of software or apps to offer more value to your users, AI in software development is changing how we build this software and apps in the first place. Here is how:

• Supporting DevOps workflows with AI-powered automation resulting in AIOps
• Utilizing GenAI tools in the requirements planning phase
• Implementing AI coding assistants or copilots in software creation
• Leveraging large language models and GenAI models across the software development lifecycle (SDLC)
• Integrating AI tools into the developer’s toolkit to provide intelligent, real-time feedback and suggestions
• Using AI to facilitate design-to-code
• Automating testing using AI-powered testing tools

2. Platform Engineering

According to Gartner, By 2026, 80% of software engineering organizations are expected to establish platform teams. These teams would serve as internal providers of reusable services, components, and tools to streamline application delivery.

Closely related to optimizing Developer Experience (DevEx), platform engineering provides self-service portals that internal development teams can use to reduce cognitive load. These tools empower developers to create, update, and deploy software faster than ever.

Here are some trending platform engineering use cases to consider adopting:

• Platform as a Product
• GitOps Workflow Automation
• Container Visualization
• Platform Orchestration
• SaaSification of Products and Platforms

This leads us to another important trend in software development: Developer Experience.

3. AI-Empowered Applications

In recent years, while the availability of data increased, much of it could not be used to its full potential. Now, this data can be leveraged to create AI and ML models that automate various functions by embedding intelligence directly into software.

Here are some key trends in embedding AI and ML models into AI-powered software:

• Recommendation Engines
• Robotic Process Automation (RPA)
• AI as a Service (AIaaS) Integration
• Generative AI Integration
• Chatbots and Virtual Assistants
• AI-Powered Data Analysis
• AI Integration in IoT Solutions
• AI Governance Functions
• Data-Enhanced Applications with Embedded AI and ML

There’s even more to these AI trends, including digital twins, shadow AI, AI hallucination policies, API-driven AI, and more. To dive deeper read our blog on the top AI trends.

4. Developer Experience (DevEx)

DevEx not only directly impacts developer productivity and software time-to-market but also plays a crucial role in developer retention. This is why Gartner forecasts that, by 2027, organizations that implement formal developer experience (DevEx) initiatives will be twice as likely to retain their developers compared to current levels.

However, only 44% of developers believe that leaders are fully aware of the issues contributing to a poor developer experience. This presents an opportunity for organizations to address these gaps by incorporating AI tools, reevaluating productivity metrics, promoting developer autonomy through platform engineering, and more.

5. Digital Immune System (DIS)

Reducing downtime is a critical priority for most companies with business-critical systems. By 2025, organizations investing in digital immunity are expected to improve customer satisfaction by reducing downtime by 80%.

Downtime can stem from various issues, including security breaches, glitches, bugs, and more. Regardless of the cause, its impact can lead to customer dissatisfaction and significant costs. For example, on April 5, 2022, 775 Atlassian customers lost access to their products, with some experiencing outages that lasted up to 14 days. Similarly, a software bug caused Equifax to provide inaccurate credit information for nearly three weeks, while Tesla had to recall 59,000 vehicles due to a software glitch.

These challenges can be minimized with a robust Digital Immune System (DIS). A DIS integrates best practices and technologies across development, design, testing, and more to reduce system failures and improve reliability.

Here are the six pillars for building a strong DIS:

• AI-augmented Testing
• Chaos Engineering
• Observability
• Site Reliability Engineering (SRE)
• Auto-remediation
• Software Supply Chain Security

6. Immersive-reality Technologies

Following Apple’s launch of its new AR headset, the Apple Vision Pro, several companies have begun leveraging the technology to offer consumers a more immersive product experience. This trend is being explored across various industries, from automotive to entertainment.

For example, Porsche has partnered with Meta to use its Quest 3 MR headsets for event presentations and vehicle walkthroughs. Meanwhile, Disney acquired a $1.5 billion stake in Epic Games and announced a collaboration to build a new virtual entertainment universe.

The immersive technologies on the rise include:

• Augmented Reality (AR)
• Virtual Reality (VR)
• Mixed Reality (MR)
• Spatial Computing
• On-body and Off-body Sensors
• Location Mapping Software

7. Cloud Computing

We’ve already experienced the benefits of using cloud computing in terms of scalability, flexibility, cost, and more. As cloud technology continues to evolve, it will further empower us to reimagine its potential.

Here are the cloud computing trends you need to watch for:

• Enterprises adopting AI as a service (AIaaS)
• Edge computing integrating with the cloud
• Hybrid and multi-cloud strategies
• Sustainable cloud solutions
• Serverless computing
• Quantum computing becoming widely accessible through the cloud
• GenAI changing how we create, deploy, and use cloud services
• Supercloud emerging as the ultimate data fabric

To explore these trends and more in detail, read our blog on Cloud Computing Trends.

8. Machine Learning Operations (MLOps)

Inspired by DevOps and the increasing use of ML models in software, MLOps is a popular approach to simplify ML lifecycle management.

Born at the intersection of DevOps, data engineering, and machine learning, this set of practices fosters collaboration and communication between data scientists and operations teams. MLOps can be applied across all stages of the lifecycle, from data gathering to model development, deployment, and monitoring.

Key use cases of MLOps include:

• Continuous integration/deployment (CI/CD)
• Data management & governance in MLOps
• Automated testing & validation
• Real-time model monitoring and alerting
• Scalability & resource management in MLOps

9. Expansion of the IoT

The Internet of Things (IoT) is transforming how we connect with and interact with the world around us. As the number of interconnected devices continues to rise, IoT’s potential to reshape industries is expanding. Coupled with other emerging technologies, IoT software is evolving rapidly, driving innovation across sectors.

Key IoT trends in software to watch:

• Edge Computing in IoT
• 5G Connectivity for IoT
• IoT in Healthcare
• AI Integration in IoT Devices
• Digital Twins for Predictive Maintenance
• Blockchain for Enhanced Security in IoT

10. Increased Investment in Progressive Web Apps

Faster, more reliable, and more engaging web experiences that mimic native apps are becoming the new standard. As businesses increasingly invest in Progressive Web Apps (PWAs) to deliver seamless cross-device experiences without the overhead of traditional mobile apps, industries are seeing notable benefits.

PWAs typically drive a 68% increase in traffic, use significantly less device storage — 25 times less than native apps — and load up to 15 times faster, making them a preferred choice for businesses and users alike. Major tech giants like Apple and Google are also endorsing PWA support, further solidifying their importance in the digital landscape.

11. DevSecOps

Ensuring efficiency in addressing software security issues is an essential part of the software development process. DevSecOps is a set of tools and processes that empower development teams to integrate security practices into every aspect of the software development lifecycle (SDLC).

Derived from development, security, and operations, it extends DevOps by embedding security and enhancing cybersecurity throughout the process. 

However, when it comes to the difference between DevOps and DevSecOps, the two differ significantly in terms of their key objectives. For DevOps, the focus is on development efficiency, while for DevSecOps, it is on integrating security into every aspect of the Software Development Life Cycle (SDLC).

Some key DevSecOps trends in software development include:

• ML integration in DevSecOps
• Use of AI co-pilots
• Integration of AI-driven security in DevSecOps
• Pushing DevSecOps into the ETL pipeline
• Embedding security controls and automated testing in the CI/CD pipeline
• Use of policy as code, specifically Open Policy Agent
• Merging model-based systems engineering with DevSecOps
• Prioritizing containerization in deployments
• Integrating quantum computing with DevSecOps

12. Microservice Architecture

By breaking down complex applications into smaller, independent services, microservice architecture enables organizations to develop, deploy, and scale software more quickly and efficiently. This approach has reshaped the software development landscape, offering businesses greater flexibility and scalability than ever before.

The core features of microservices — modularity, scalability, and fault tolerance — are driving their adoption across industries such as finance, retail, and healthcare. This model helps businesses manage complexity, as each microservice can be built, updated, and maintained independently, resulting in faster development cycles and more agile operations.

Here are some key trends in microservices architecture:

• Creating synergy between agile and microservices
• Integration of AI and microservices
• Adoption of service meshes for managing microservices
• Use of serverless architecture

Content Credit
Samar Patel