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This could be the year that technology makes a truly revolutionary leap.
The primary catalyst is artificial intelligence (AI). AI is a through line among the many expert predictions for 2025. Does this mean that AI has finally reached a suitable maturity level? It has certainly become an integral part of many companies' design and development plans. If one prominent consultancy’s predictions come true, 25% of AI-enabled companies will have piloted or proofed some form of so-called agentic AI by year’s end.
By 2027, that share of adoption may double.
AI encompasses many different applications, use cases, and organizational considerations. But it’s not alone on our list of top technology trends in 2025.
AI’s rise to prominence gained speed and became fully mainstream in 2024. That momentum is set to continue in 2025. Perhaps the most important shift in AI in recent years has been the democratization of processing power. Machine learning algorithms and the large datasets to train them are more accessible and affordable than ever.
AI’s rapid evolution continues in 2025, with businesses integrating AI into products and workflows more seamlessly than ever. The democratization of machine learning—thanks to platforms like Google Cloud AI, AWS AI, and OpenAI’s API—has made it accessible to companies of all sizes.
However, cost remains a key concern. A recent IBM report projects an 89% increase in computing costs by 2025, with 70% of executives attributing this to generative AI adoption. Beyond cost, organizations must also navigate AI governance, security, and energy efficiency challenges.
Generative AI is changing how software engineers work, streamlining workflows and automating repetitive tasks. Tools like GitHub Copilot, Tabnine, and Replit Ghostwriter assist with:
Herein lies another important consideration: as large as the promise of generative AI might be, it’s still about the people. Consider the entire development lifecycle, for example. Faster coding is just one part of the potential gains that generative AI might deliver. In addition, track and assess performance. Tie generative AI initiatives to actual metrics, so you can assess what’s working and what’s not. Finally, adjust and adapt the relevant roles. Don’t overlook the people asked to learn and adopt new technology, such as generative AI.
Beyond code generation, LLMs support knowledge retrieval, operational automation, and business intelligence. A major shift in 2025 is the move toward open-weight models like Meta’s Llama 3 and Mistral AI. Unlike proprietary AI services that process data externally, these models allow businesses to fine-tune and deploy AI entirely in-house.
This gives organizations more control over sensitive data and enables them to train AI assistants that are tailored to their industry, workflows, and customer needs. Instead of relying on a generic AI model, companies can build AI-powered tools that understand their specific terminology, compliance requirements, and operational challenges, offering greater control over data privacy.
A review of engineers' preferred programming languages, as tracked by the TIOBE Index, reveals that both existing and emerging languages play a prominent role:
Python was named TIOBE's "Programming Language of the Year 2024," marking its fourth consecutive year in this position since 2021. It achieved a significant increase of 9.3% in ratings over the past year, bringing its current rating to 23.28%. This surge is attributed to Python's widespread adoption in fields such as AI, data science, and machine learning. Its simplicity and extensive library support continue to make it a preferred choice among developers across various industries.
C++ has surpassed Java and C to secure the second position in the index, with a rating of 10.29%. This ascent is largely due to its robust performance in system-level programming and game development. Conversely, the C language has experienced a decline in popularity, now ranking fourth with an 8.86% rating. This decrease is primarily because C is being replaced by C++ in many embedded software systems.
Go has entered the top 10, now ranking seventh with a 2.61% rating. Its rise is linked to its growing use in cloud computing and microservices architectures, reflecting the industry's shift toward modular and efficient development practices. Additionally, Rust has climbed to the 14th position with a 1.16% rating. Despite its steep learning curve, Rust is valued for its memory safety and performance, making it increasingly popular in system-level programming and embedded systems.
As Rust and Go gain traction, companies investing in high-performance, scalable applications may increasingly adopt these languages for modern architectures.
PHP has exited the top 10, now ranking 13th with a 1.38% rating, reflecting its decreasing popularity in recent years. Kotlin has also seen a decline, falling out of the top 20 in 2024 and failing to achieve its much anticipated breakthrough.
The ways in which engineers build applications are changing and evolving, too. Philosophically, companies are becoming less likely to build large-scale applications that offer a long list of features. The new trend involves creating modular, interconnected micro apps that can combine in different ways as the situation demands.
Engineers have been gravitating toward new approaches to app building, including the use of micro frontends and serverless architectures. This new focus ties into the rise of the Go programming language, which is the language of choice for micro-framework and no-framework concepts.
The move toward modularity has been ongoing over the last few years. This trend is joined by an overall more democratized approach to software development. Related trends include no-code and low-code component development, allowing more team members to take a hands-on approach to development without a coding-intensive background.Building out a network of components rather than creating large apps is a resilient, future-proof approach to development. Organizations have put these principles into action for years now, and can now be confident that it's a reliable way to create mission-critical products.
The Internet of Things (IoT) is evolving rapidly, and 2025 marks a significant shift as IoT merges with AI to create what’s being called the Internet of Behaviors (IoB). This isn’t just about connecting devices anymore—it’s about making those devices smarter and more intuitive, capable of analyzing and responding to user behaviors in real time. For engineering and product teams, IoB offers opportunities to design systems that are not only innovative but deeply user-centric.
Key technologies driving this evolution, like edge computing and beacon technology, are reshaping how IoT systems are built and operate.
Edge computing is empowering IoT devices to process data closer to where it’s generated, reducing latency and enabling real-time decision-making. This is particularly valuable for time-sensitive applications, such as predictive maintenance, energy optimization, and real-time system adjustments in smart buildings. For engineering teams, edge computing offers the added benefit of reduced reliance on cloud infrastructure and enhanced security through localized data processing.
Beacon technology is adding precision and context to IoT ecosystems. In industries like retail, logistics, and healthcare, beacons enable hyper-localized tracking and interaction, offering unprecedented levels of personalization. For example, a smart building could use beacons to monitor foot traffic and adjust lighting or HVAC systems in real time, balancing user comfort with energy efficiency. When integrated with AI, these technologies go beyond simple automation, delivering experiences that adapt dynamically to user patterns and preferences.
For product teams, IoB presents an opportunity to rethink how value is delivered to users. The focus is shifting toward systems that feel proactive—devices that don’t just react but anticipate needs based on behavioral insights. Success in this space means building scalable, modular solutions that balance technical robustness with seamless, personalized experiences.
As IoB continues to mature, it’s opening doors for organizations to differentiate their offerings, whether in smart homes, industrial IoT, or connected healthcare. For our clients, this is a chance to work with engineering and design teams that understand how to turn cutting-edge technology into meaningful, impactful products that resonate with users.
With global sustainability goals becoming more pressing, businesses are rethinking their development practices to reduce energy consumption and minimize environmental impact. Consider this: of the 64% of companies increasing their budget to deepen their use of generative AI, 34% say that sustainability is a key driver of those expected budget increases.
Every line of inefficient code adds up. Applications that demand excessive computing power drive up cloud costs, slow performance, and increase energy consumption. AI development, in particular, relies on vast datasets and high-performance computing, which require massive server resources. As businesses integrate AI into their workflows, they are rethinking their architectures to improve efficiency.
Many are turning to edge computing to reduce the energy demands of centralized cloud processing, cutting down on latency, bandwidth usage, and overall power consumption. Meanwhile, cloud providers are introducing sustainability dashboards to help teams track and minimize their energy footprint, making workload optimization a more data-driven process.
Sustainability also means rethinking product lifecycles. Instead of continuously building from scratch, companies are shifting to modular architectures. It reduces resource waste and infrastructure costs but also prevents the accumulation of technical debt—which, over time, slows down development and increases maintenance burdens.
For end users, sustainability is felt too—in battery life, app speed, and overall responsiveness. Optimized software loads faster, consumes less power, and runs smoother on any device. Features like low-power modes, dynamic resource allocation, and lightweight applications are becoming part of good product design, not just sustainability efforts.
Aligning with sustainability isn’t just about compliance—it’s a competitive advantage. Products that incorporate energy-saving features or offer low-resource modes appeal to eco-conscious consumers and can differentiate in saturated markets. Ultimately, sustainability is becoming a shared priority across engineering, design, and product development, pushing teams to innovate smarter, leaner, and greener solutions.
While it's valuable to learn about the leading tech trends as 2025 begins, it's also worth acknowledging that new, unexpected concepts can and will emerge as the year goes on. Today's technology landscape is moving faster than ever before. In the past, major new themes could take a decade to reach maturity; today, new ideas can take hold in as little as a year.
To keep your organization competitive, be ready to study and engage with each new development as it emerges. In some cases, this will mean investing time and resources; in others, it will involve showing caution and avoiding trends that don't apply to your core mission.
Working with consultants or third-party design and engineering partners is one way to ensure your new products reflect state-of-the-art practices. Experts can help your internal stakeholders engage with emerging trends, not just adopting new ideas because they're popular, but truly putting them to valuable use.
At Transcenda, we’ve helped companies navigate emerging trends—whether it’s integrating AI into product workflows, adopting modular development approaches, or designing more sustainable digital experiences. Let’s discuss how these trends can shape your next product—contact us to learn more.
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