Gartener's 2026 Tech Trends: How Companies Must Adapt π

These platforms are particularly important in sectors that require large amounts of data and complex calculations, such as the pharmaceutical or automotive industries.
Multi-agent systemsThese technology approaches consist of specialized AI agents that work together to automate complex workflows. This distributed approach helps teams combine human expertise with AI logic to be more efficient and responsive. Therefore, lower delivery costs and new automations in industries like logistics and customer service are expected. ππΌ
Multi-agent systems offer numerous advantages:
β **Scalability**: They can be easily adapted to changing requirements. β **Flexibility**: Different agents can be programmed for different tasks.
β **Efficiency**: By distributing tasks, processes are accelerated and optimized.
Companies that implement these systems can significantly improve their operations and gain competitive advantages.
Domain-specific language models (DSLMs)Generic language models often fail at industry-specific tasks. This is where DSLMs come in! These customized AI models improve accuracy and reduce error rates. Gartner expects that by 2028, more than half of enterprise AI models will be industry-specific. π
Advantages of DSLMs:
β **Higher accuracy**: Specially trained models better understand industry-specific terminology. β **Better performance**: Faster and more accurate responses to complex queries.
β **Adaptability**: Easily adaptable to new requirements and data sources.
These models are particularly useful in areas such as healthcare, finance, and law, where precise communication and data analysis are critical.
Security platforms with AIAs AI systems boom, more companies are adopting security systems that leverage AI. Gartner predicts that by 2028, over 50% of companies will use these technologies to enforce internal policies and prevent data loss. π‘οΈπ₯οΈ
Features of AI-driven security platforms:
β **Threat Detection**: Real-time detection of security threats and anomalies. β **Automated Responses**: Immediate action to defend against attacks.
β **Proactive security**: Predicting potential threats based on data analytics.
These platforms help companies protect their IT infrastructure while meeting compliance requirements.
AI-native development platformsThese platforms use generative AI to accelerate software development. Gartner predicts that by 2030, 80% of large software teams will become smaller, AI-powered teams. This means faster application delivery and lower development costs. π
Advantages of AI-native development platforms:
β **Accelerated development cycles**: Faster creation and implementation of software solutions. β **Cost reduction**: Less personnel costs and more efficient use of resources.
β **Innovation**: Enables the development of complex and innovative applications.
These platforms are particularly relevant for companies that want to remain competitive in the fast-moving tech industry.
Challenges and further considerationsAlthough the trends mentioned are promising, companies face various challenges:
β **Integration complexity**: New architectures such as multi-agent systems require robust data and multi-cloud orchestration. πΈοΈ β **Governance and trust**: The explainability and provenance of decisions by AI models are crucial. π β **Evolution of security**: AI-powered security requires new capabilities and continuous monitoring. π β **Resources**: Collaboration between IT, operations, and engineering teams will be equally important. π€
β **Costs**: The implementation of new technologies may initially require high investments, which are, however, offset by efficiency gains in the long term.
Companies must proactively address these challenges in order to fully exploit the benefits of new technologies.
Geo-patriation and digital provenanceTwo major trends concern geopolitical and compliance aspects. Digital provenance tools will help companies confirm the source and integrity of software and AI content. π‘ Tracking workloads to sovereign clouds will also become popular as companies reassess their geopolitical exposure. π
Important aspects:
β **Compliance**: Compliance with regional and international regulations. β **Security**: Ensuring that data and applications run in trusted environments. β **Transparency**: Traceability of the origin of software and data.
β **Flexibility**: Use of cloud services that meet geopolitical requirements.
These trends are particularly relevant for global companies that operate their data and applications in different regions.
Sustainability and Green IT π±Another important trend that shouldn't be overlooked in the tech trends for 2026 is sustainability. Companies are increasingly turning to environmentally friendly technologies to reduce their carbon footprint and operate more sustainably.
Measures to promote sustainability:
β **Energy-efficient data centers**: Use of renewable energy and optimization of energy consumption. β **Green Software Engineering**: Development of software solutions that use resources efficiently. β **Recycling and upcycling of hardware**: Extending the lifespan of devices and efficient disposal of electronic waste.
β **Sustainable supply chains**: Ensuring that entire supply chains are environmentally friendly.
Sustainability is increasingly viewed as an important success factor not only by the environment but also by customers and investors.
Remote work and digital collaboration π‘πΌThe pandemic has demonstrated the importance of flexible working models. Remote work will remain a central component of corporate structures in 2026. Digital collaboration technologies are being further developed to ensure seamless communication and productivity.
Key technologies and trends:
β **Virtual Reality (VR) and Augmented Reality (AR)**: Enable immersive meetings and training. β **Cloud-based platforms**: For easy access to work tools and documents from anywhere.
β **AI-powered tools**: Support project management and automation of routine tasks.
These developments help teams work effectively and flexibly, regardless of their location.
Artificial Intelligence and Ethics π€βοΈAs AI adoption in businesses increases, ethical use is also becoming increasingly important. Companies must ensure that their AI systems are deployed transparently, fairly, and responsibly.
Important aspects of AI ethics:
β **Transparency**: Disclosure of how AI decisions are made. β **Fairness**: Avoiding bias and discrimination in AI models. β **Responsibility**: Clear responsibilities for the decisions of AI systems.
β **Data protection**: Ensuring the privacy and security of the data used.
These ethical considerations are crucial to maintaining public and customer trust in AI technologies.
ConclusionGartner's tech trends for 2026 make it clear: technology is inextricably linked to business leadership, resilience, and HR strategy. It will be about implementing new platforms while remaining accountable and transparent. CIOs are challenged to find solutions to adapt to rapid change. π―
Companies that identify emerging tech trends early and leverage them strategically will have a clear competitive advantage. Whether through the use of AI supercomputing, the implementation of multi-agent systems, or a focus on sustainable technologies β the opportunities are diverse and promising.
Stay tuned for what 2026 will bring! πΆοΈπ²
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