Beyond the hype: Tech trends that will define 2025

Predicting the technology trends that will have the most impact in 2025 isn’t easy. In the tech sector, where advancements happen at lightning speed, looking too far ahead can be challenging.

Even so, our teams have identified 10 key tech trends that we shouldn’t lose sight of in the coming months. Undoubtedly, AI will remain a strong bet, continuing to surprise us both at the enterprise level and as end users.

But it’s not all about AI. We’ll also see trends pushing toward sustainability, accessibility, and even more human-centric leadership, adapted to the digital landscape.

Here are the 10 trends we’re focusing on for 2025. Some already surprised us last year, and we know there are many more out there that didn’t make this list.

1. Voice and video in AI

Generative AI for video and voice is emerging as one of the most transformative technologies. Tools like Synthesia and Descript already enable the creation of avatars that speak multiple languages or automatically transform text into video, revolutionizing multimedia content creation.

This is particularly valuable for small businesses that, without large production budgets, can create customized advertising campaigns quickly and at a low cost.

By 2025, the use of voice generation models such as VALL-E or NaturalSpeech 2 will not only allow the creation of hyper-realistic synthetic voices but also the ability to clone voices with just a few seconds of audio. This technology will play a crucial role in multimedia production for marketing, education, and even in the creation of personalized virtual assistants.

In education, for example, AI will enable the creation of educational videos tailored to individual learning needs, with the possibility of real-time interaction using AI-generated avatars.

2. Accessibility: developing inclusive applications

When we talk about accessibility, web applications often come to mind automatically. This makes sense: the front-end world has been working for years to ensure websites are accessible, paving the way for everything that followed.

With the rise of mobile devices, more and more users have grown accustomed to having one of these “gadgets” in their pockets and using them intensively.

For this reason, mobile app development must also prioritize efforts to ensure that our applications are usable by everyone. Moreover, we face an additional challenge: we are limited by the small screen size of these devices and, often, the inability to incorporate all the necessary hardware without compromising their mobile essence.

In 2023, 57% of all internet traffic came from mobile devices, according to Statista. This trend has been steadily increasing in recent years.

Mobile devices can become a powerful ally for users with disabilities if we meet accessibility standards. But their contribution doesn’t stop there: by providing these users with a mobile phone they can take anywhere, we are offering them an incredible tool to make their daily lives more manageable.

3. From digital native to AI native: the new era of AI in business

Although artificial intelligence has been around for several decades, its real and productive application in business and for consumers has been gradual.

The impressive advancements showcased by major AI players-whether through flashy demonstrations or in-depth research articles-often remained as laboratory material, needing further maturity before being stable and applicable to the real world.

However, that wait is coming to an end. AI has now matured to the point of being considered stable in solving a wide range of problems.

If we add to this the revolution of LLMs (popularized by ChatGPT), we find ourselves in a scenario where complex and costly AI systems are no longer required to develop applications-solutions that, until recently, were accessible only to a select few.

What does it mean to be “AI Native”?

An AI Native application is one that, from its very conception, is designed with AI as a central and indispensable component-such that the application could not exist without it. This is not about adding a superficial AI layer to an existing product but about building a digital solution where this technology serves as the driving force behind all its functionalities.

It’s a time of change: the “Digital Native” generation will gradually give way to the “AI Native” generation. And so, we must adapt yet again-without having fully adjusted to the last wave of transformation.

4. GreenOps: leading the shift toward a sustainable future

In a society increasingly aware of its environmental impact, businesses are becoming more committed to finding innovative ways to operate sustainably without compromising their growth. This is where GreenOps comes into play-a practice designed to revolutionize the way we currently manage our cloud infrastructures.

GreenOps goes beyond simply reducing the carbon footprint. It’s about intelligently optimizing cloud resources by leveraging clean and efficient technologies to enhance performance, reduce consumption, and contribute to a more sustainable future.

Implementing GreenOps is no easy task and requires a holistic approach involving the entire organization. From IT teams tasked with evaluating the current infrastructure and adopting new technologies and practices, to finance and procurement departments managing costs and ensuring compliance with emerging regulations-such as sustainability reporting requirements-every part of the organization has a role to play.

Adopting FinOps as a starting point is critical to laying the groundwork for GreenOps. By gaining visibility and control over cloud spending and consumption, businesses can identify areas with the highest energy usage and take action to optimize them.

The adoption of GreenOps represents a unique opportunity to lead the transition toward a greener future. Organizations that integrate this practice into their business strategy can make a significant impact, growing responsibly and sustainably, strengthening their market position, and attracting an increasingly discerning audience.

5. Evidence-Driven transformation

The immediacy and scarcity of conscious moments for observation and reflection are causing us to drown in trends and make decisions based on perceptions and emotions.

Yes, transformation is essential both to survive and to gain a competitive advantage. Yet, I wonder: what happens if our change strategy pivots too quickly? What if we fail to establish habits? What if we focus on “doing” instead of “being”? We have information, but is there real learning? I dare say no.

For decades, we have immersed ourselves in transformation processes, yet we remain the same. Now, we find ourselves at the peak of Artificial Intelligence, but so too has it been with Robotic Process Automation (RPA), Big Data, the Cloud, microservices, the Metaverse, augmented reality, electric cars, the shift from Human Resources to People departments, HR Analytics, servant leadership, remote work, open-space offices… and countless other trends. Too often, we adopt these changes with a “prêt-à-porter” mindset, without truly understanding their positive or negative impact.

For this reason, it is crucial to drive evidence-based transformations, moving away from sunk-cost decisions and toward objective facts and results. This means focusing not only on what we are doing but also on how we are doing it, how we behave, and how we impact others.

6. Humanistic systemic leadership

Humanistic Systemic Leadership is based on the premise that people do not act in isolation; they are systems within broader systems such as teams, organizations, and societies. Through this approach, understanding individuals as part of a connected whole allows for a more comprehensive and profound view of their values, behaviors, expectations, and needs.

This leadership places the individual at the center-not as just another resource or stakeholder within an organizational structure, but as a whole human being whose motivations and emotions influence collective efficiency and impact.

The key to leadership in 2025 lies precisely in the ability to understand how people communicate and relate to one another, both in professional and personal environments.

We must foster environments that build and nurture healthy relationships and solid interpersonal networks to guide teams toward balanced and collaborative growth.

7. Industry cloud platforms

Industry Cloud Platforms are cloud-based solutions specifically designed to meet the unique needs of particular sectors or industries. These platforms combine cloud services with applications, data, and advanced technologies (such as AI, ML, and analytics) tailored to the challenges, regulations, and requirements of each specific industry.

Gartner predicts that by 2027, more than 70% of companies will use Industry Cloud Platforms (ICP) to accelerate their business initiatives, compared to just 15% in 2023.

• Industry-Specific customization: For each industry (e.g., healthcare, manufacturing, finance, retail), ICPs offer tools and solutions tailored to workflows, regulations, and sector-specific needs.
• Integration of advanced technologies: Through the use of Artificial Intelligence (AI), Machine Learning (ML), data analytics, Internet of Things (IoT), and automation, these platforms deliver advanced solutions such as demand forecasting, operational optimization, and enhanced customer experience.
• Cloud services and scalability: Built on cloud infrastructure, they are highly scalable and can adapt to evolving business needs.
• Ecosystem of solutions: These platforms typically include applications and tools that integrate with other cloud services or third-party solutions, creating a collaborative ecosystem that streamlines operations.
• Regulatory compliance: Designed for specific industries, they feature built-in tools to comply with sector-specific regulations and standards, such as data privacy rules (e.g., HIPAA in healthcare or GDPR in Europe) and quality standards.

In the market, there are vendors offering platforms for various companies and businesses driving the development of their own platforms. Examples from the first group include Salesforce Industry Clouds, Google Cloud for Retail, or Microsoft Cloud for Healthcare.

Successful company implementations include Siemens MindSphere (for IoT and manufacturing), Volkswagen (automotive sector), Johnson & Johnson — Industry Cloud (healthcare), Coca-Cola Intelligent Industry Cloud (retail), and Lloyds Banking Group — Industry Cloud (financial services).

Industry Cloud Platforms are set to become a key tool for transforming entire industries, enhancing efficiency, customizing services, and improving companies’ ability to adapt to ever-changing market demands.

8. Agentic AI

AI has evolved significantly, progressing from basic automation tools to advanced generative models like Large Language Models (LLMs). However, a new paradigm called Agentic AI is emerging, promising to revolutionize AI’s role by enabling systems to autonomously manage complex tasks.

Agentic AI refers to artificial intelligence systems with a high degree of autonomy, capable of making decisions, planning actions and learning from experiences without constant human intervention. These systems can adapt to new data, interact with external tools and databases, and improve over time through continuous learning.

The benefits include increased flexibility, accuracy in complex tasks, real-time interactions, and enhanced user experiences, as they can autonomously manage multi-step processes.

Despite its potential, Agentic AI faces significant challenges. Ethical considerations are paramount, and there are concerns about the accuracy and reliability of the information provided. Additionally, its widespread adoption could impact the labor market, displacing certain roles and increasing the need for workforce reskilling.

Several leading companies are already adopting Agentic AI in their operations. Salesforce, in collaboration with Google, has developed Agentforce, which enables AI agents to autonomously manage sales and customer support interactions.

Microsoft has introduced Copilot agents within Dynamics 365 and Microsoft 365 to automate tasks in tools like Teams and Office. ServiceNow and Oracle are also integrating advanced AI agents into their platforms to optimize business processes and improve operational efficiency.

9. WebAssembly (WASM)

The evolution of the web has enabled browsers to support complex applications that once required desktop programs, thanks to advanced technologies like WebAssembly (WASM).

WASM has significantly improved web application performance by bringing execution closer to the client hardware, enabling popular tools like Google Earth, Figma, and TensorFlow to run smoothly within the browser. This standard, supported by the W3C WebAssembly Community Group, is compatible with current browsers, solidifying its use in the web environment.

The true shift in WASM’s usage happens on the server side with the introduction of WASI (WebAssembly System Interface). Unlike browsers, WASM modules on servers do not require a full virtual environment.

Instead, they rely on a WASI-compatible runtime that translates WebAssembly into machine code. This allows applications to run in a secure and optimized environment, achieving near-native performance without depending on CPU architecture or the operating system.

Thanks to WASI, it is now possible to integrate WASM modules into container ecosystems, where they can be managed similarly to traditional containers. Tools like runwasi, crun, and youki have simplified this integration, unlocking new opportunities to leverage WASM in environments previously dominated by conventional containers. This expands the possibilities for virtualization and application deployment.

The integration of WASM and WASI in platforms like Kubernetes highlights the potential of this ecosystem in cloud environments. This combination is being driven by companies like the CNCF, Microsoft, and OKTA, which are promoting the use of WASM in managed containers.

This is paving the way for a more flexible, universal, and high-performance infrastructure for both the web and cloud computing services.

10. Drag-and-Drop solutions for Generative AI

Drag-and-drop solutions focus on democratizing access to advanced generative AI tools, enabling professionals with limited technical expertise to leverage this technology’s capabilities. Platforms like RunwayML, Lobe AI, Google Vertex AI (Dataflow CX), and Microsoft Copilot Studio are current examples that provide intuitive graphical interfaces, simplifying the creation and customization of AI models without extensive coding.

By 2025, these platforms are expected to evolve with more advanced features, such as the integration of complete enterprise workflows, enhanced model customization, and options to deploy applications directly from the cloud or on-premise solutions.

For instance, tools like Helicone.ai allow users to collaboratively manage prompts and models, optimizing AI for specific tasks without requiring deep knowledge of data science. This will enable businesses to use AI for tailored solutions in areas such as customer support, marketing, or content creation, simply by dragging and dropping components within a visual interface.

In e-commerce, a concrete example would be using these platforms to configure personalized recommendations that analyze consumer behavior in real time, improving the shopping experience and optimizing sales without relying on specialized development teams.

Originally published at https://en.paradigmadigital.com.