Complete Guide to the Main IT Trends for 2026

The IT industry moves fast, yet the past two years have changed the sector’s trajectory. AI has matured. Cyberattacks increased. Compliance requirements expanded. Remote teams have become the norm for product companies of all sizes. European firms advanced industry standards, while US companies adopted new engineering practices. As a result, 2026 arrives with new IT trends, which we’ll cover in this guide.

1. AI-native product development becomes the default

AI-native development reshapes how companies build software. Teams use AI throughout the feature lifecycle: planning, coding, testing, documentation, and quality control. This shift began in 2024, accelerated in 2025, and stabilized as a mainstream practice in 2026.

According to the 2025 GitHub Octoverse report, ~80% of new GitHub users activate GitHub Copilot within their first week, and more than 1.1M public repositories now include an LLM SDK, a 178% year-over-year increase. These patterns align with current IT technology trends that emphasize automation at scale.

AI coding assistants no longer support simple prompts but work inside IDEs, CI pipelines, and documentation platforms. They map legacy code, explain complex components, produce refactoring plans, and track code consistency.

This IT trend matters because companies compete on speed. Teams that adopt AI-native workflows build features faster, improve code quality, and reduce onboarding time. New hires learn the system through AI tools that explain architecture, test cases, and dependencies. Established teams reduce repetitive tasks and focus on strategic work.

AI also becomes part of product strategy. Gartner reports that 40% of enterprise apps will feature task-specific AI agents by 2026. This turns AI from an optional feature into a core requirement. Companies that ignore it lose competitiveness because users expect more innovative interfaces, predictive systems, and automated suggestions.

2. Agentic automation reshapes engineering and operations

Agentic automation will expand quickly in 2026. This trend in IT refers to AI agents capable of performing multistep tasks without continuous human oversight.

Forrester reports that next year, enterprise software will shift from supporting human workers to working side-by-side with AI agents. Companies will need to decide how much of their processes they want these agents to run autonomously.

Agentic tools perform tasks such as:

• Preparing pull requests.
• Generating documentation.
• Writing test cases.
• Running performance reviews on code.
• Planning sprint tasks.
• Summarizing incidents.
• Mapping API dependencies.
• Checking compliance rules.

This matters for global engineering teams because it reduces bottlenecks. Distributed teams often lose time when work depends on a specific person. AI agents remove these delays. Teams close tickets faster, run QA cycles more frequently, and maintain cleaner codebases.

European companies adopt agentic workflows rapidly because the EU invests in automation standards and fosters a strong research ecosystem. As a result, European engineering practices often serve as the benchmark for distributed teams that collaborate across borders.

3. Cloud cost control becomes a strategic priority

Cloud costs increase every year. For example, quarterly data from early 2025 indicate a ~21% year-over-year increase in cloud-infrastructure spending. Companies realize that uncontrolled cloud usage slows growth. As a result, FinOps shifts from a specialist niche to a core engineering requirement in 2026, reflecting broader trends in the IT industry toward financial accountability.

FinOps works when teams take responsibility for cost decisions. Engineers select more efficient architectures. Product managers review usage patterns. Companies build dashboards to track cost allocation by team or feature. Platforms such as Datadog, AWS Cost Explorer, and GCP Billing are evolving into strategic planning tools rather than accounting utilities.

This is crucial for global companies because cloud cost control improves predictability. A clear picture of cost drivers helps budget planning and supports long-term product decisions. It also influences architecture. Companies prefer:

• Serverless components for low-workload scenarios.
• Containers for predictable workloads.
• Edge computing for latency-sensitive applications.

European teams follow FinOps practices aggressively because local businesses operate under tighter financial frameworks and prefer predictable, controlled costs.

4. Platform engineering becomes the new engineering backbone

Platform engineering will continue to rise in 2026. The approach focuses on creating internal developer platforms that simplify infrastructure, accelerate deployments, and standardize workflows.

By 2026, 80% of large software engineering organizations will establish platform engineering teams as internal providers of reusable services, components, and tools for application delivery, according to Gartner. Companies that adopt this approach reduce deployment time, improve reliability, and offer consistent tooling across teams.

An internal platform usually offers:

• CI/CD automation.
• Testing frameworks.
• Code quality tools.
• Container orchestration.
• Monitoring dashboards.
• Templates for microservices.
• Security controls.
• Environments for development, staging, and production.

This is important because modern products require stable, repeatable processes. Distributed teams lose time when they manually configure tools. A strong platform removes friction. It also supports AI workflows because AI agents perform better in structured environments.

European companies lead this trend because many scale-ups have built their growth strategy on platform engineering practices. These companies now influence the broader market.

5. Cyber resilience becomes a priority for every company

Cyberattacks grow in frequency and complexity. Ransomware groups innovate faster than many security teams. Supply chain attacks rise. Identity-based attacks dominate cloud environments. These trends in IT security demonstrate why companies will shift from static cybersecurity to continuous cyber resilience in 2026.

According to IBM Security, the global average time to identify and contain a breach in 2025 was 241 days. Companies cannot rely on traditional methods. They build layered defense systems with automated detection, threat intelligence feeds, identity isolation, and zero-trust access.

Cyber insurance also changes. Insurers demand evidence of resilience. They check MFA enforcement, cloud access controls, incident playbooks, monitoring systems, and backup strategies. Companies that lack these controls pay higher premiums.

This trend influences distributed engineering teams. Remote work expands the attack surface. Engineers connect from different networks and devices. Companies are introducing stricter identity rules, standardized devices, isolated environments, and automated policy checks.

6. Privacy-preserving technology becomes a product requirement

Regulation grows every year. The EU, UK, US, and other regions are increasing pressure on companies to store and process data responsibly. In 2025, at least 144 countries had data privacy laws.

In 2026, products must support:

• Data minimization.
• Controlled access.
• Audit logs.
• Encryption at rest and in transit.
• Privacy-preserving analytics.
• Anonymization for training AI models.

Companies adopt tools such as confidential computing, secure enclaves, and differential privacy. Cloud providers are expanding their privacy features in response to rapidly increasing demand.

This influences engineering architecture. Teams design systems with privacy controls from the start, rather than adding them later. They create automated workflows that track access rights and centralize data governance.

The European digital ecosystem strongly drives this trend. Many companies want to align with GDPR standards. As a result, privacy design becomes a competitive advantage rather than a compliance checkbox.

7. Digital sovereignty initiatives shape technical decisions in Europe

European governments continue to invest in local cloud systems, open data frameworks, and AI governance programs. These initiatives shape the technology landscape for global companies operating in or hiring in Europe.

For example:

• GAIA-X continues its expansion as an EU-backed framework for secure, transparent cloud ecosystems.
• The EU AI Act enters into force in stages, with key obligations for high-risk AI systems applying from 2026 and full enforcement phased in by 2027. This directly shapes how AI products are designed and deployed.
• New guidelines from the European Data Protection Board shape AI data management rules.
• European cloud vendors are expanding as companies seek compliant hosting options.

This is essential for companies hiring remote talent from Europe because European engineers adhere to stricter technical standards. Their approach to privacy, security, and compliance influences architecture discussions and product decisions, shaping current IT industry trends globally.

It also matters for US companies that serve European users. Technical systems must follow new rules. These rules influence model training, analytics workflows, and automated decision-making.

8. Clean architecture and modular systems replace legacy monoliths

Legacy systems slow companies down. They limit experimentation, hide dependencies, and increase maintenance costs. As AI automation grows, teams need cleaner structures. As a result, 2026 will show strong interest in modular systems, microservices, and service contracts.

Engineers prefer modular designs because they reduce complexity and simplify onboarding. Companies migrate from legacy monoliths toward:

• Domain-oriented services.
• Event-driven architecture.
• Modular codebases.
• Shared libraries with strict versioning.
• Clear boundaries between components.

AI tools also work better with modular systems. They understand dependencies, track service contracts, and analyze smaller components. This improves the accuracy of code suggestions and automated refactoring.

Companies with distributed teams benefit even more. Modular systems enable parallel work, shorter code-review cycles, and clearer ownership.

9. Low-code and no-code tools move into core workflows

Low-code platforms are increasingly used to build internal tools, automate processes, develop dashboards, and design workflows.

This gives teams the ability to:

• Build internal dashboards fast.
• Automate manual tasks.
• Create prototypes.
• Support operations.
• Enable non-technical teams to handle simple workflows.

Engineering teams supervise these tools to maintain quality and security. The trend is essential for companies that seek faster feedback cycles, stronger collaboration, and improved reporting systems.

Remote teams benefit as well. Low-code helps standardize operations across countries and ensures consistency across teams.

10. Digital twin adoption grows in manufacturing, logistics, and infrastructure

Digital twins move into mainstream adoption. These systems offer virtual representations of real-world assets. They help companies run simulations, track performance, and adjust operations. This development represents one of the key manufacturing IT trends reshaping industrial operations.

Additionally, digital twins influence software development, as these systems require strong integration, real-time data processing, and stable pipelines. Cloud providers now offer digital twin platforms to support these workloads. Engineering teams need skills in IoT, data modeling, and simulation tools.

European industries are adopting digital twins extensively, driven by robust manufacturing ecosystems in Germany, France, Italy, and the Nordic countries. This raises demand for engineers who understand simulation tools and can build stable data pipelines.

11. Green IT becomes a measurable engineering priority

Sustainable technology moves from a marketing angle into a strategic engineering requirement. Companies track energy usage, carbon footprint, and resource consumption because customers and regulators expect transparency. This reflects recent trends in IT toward environmental responsibility.

Many large companies now include environmental metrics in their IT strategy, and a growing number are redesigning parts of their infrastructure to reduce emissions.

Engineering teams adjust:

• Choose a more efficient architecture.
• Optimize storage and compute usage.
• Use serverless patterns for short workloads.
• Move workloads to regions with lower carbon emissions.
• Design lighter models and smaller data pipelines.

This impacts procurement decisions and cloud strategy. It also influences AI strategy because large model training requires significant energy.

European companies lead the trend because EU regulations encourage environmental transparency across industries.

12. Remote engineering teams follow new collaboration standards

Stack Overflow reports that roughly 50% of developers work remotely or in a hybrid arrangement. And in 2026, remote work remains a stable model. Companies refine their workflows and adopt more explicit rules for distributed engineering teams.

Remote teams follow new standards:

• Clear documentation.
• Structured feedback cycles.
• Meeting-limits.
• Async-first planning.
• Shared dashboards.
• Fixed collaboration windows for cross-time-zone work.
• Standardized onboarding through AI tools.

This trend is significant for global companies that recruit from Europe. European engineers often work in time zones that overlap with those of US teams. Clear standards help maintain code quality, delivery speed, and communication.

When companies hire engineers in 2026, they seek specialists who work effectively in distributed environments and adapt quickly to AI-native workflows. Practical knowledge of cloud systems, privacy regulations, secure coding, and platform tooling becomes more important than geographic location.

13. Data engineering becomes more important than ever

AI models require clean, accurate, and well-structured data. As a result, companies invest heavily in data engineering. This includes pipelines, governance, modeling, streaming, storage, and quality checks. Among current trends in IT, data engineering stands out as foundational to AI success.

More than 80% of AI project failures occur due to data issues. Companies now build data teams that support AI features, analytics dashboards, and automation workflows.

Modern data engineering includes:

• Real-time streaming systems.
• High-performance warehouses.
• Secure access rules.
• Event pipelines.
• Schema evolution.
• Monitoring tools.
• Metadata tracking.
• Lineage systems.

European companies are driving this trend because privacy rules require strict data governance.

14. The rise of industry-specific AI systems

General-purpose AI is well-suited to a broad range of tasks. Industry-specific AI performs better on operational tasks within regulated environments. In 2026, companies will adopt AI systems designed for:

• Healthcare.
• Finance.
• Manufacturing.
• Logistics.
• Insurance.
• Energy.
• Telecommunications.

Industry-specific AI models outperform general models on specialized tasks. Companies integrate domain models into workflows such as diagnosis support, risk analysis, scheduling optimization, and fraud detection.

This affects engineering teams, as they require skills in integration, data preparation, and compliance.

15. Companies invest in secure AI development

AI introduces new security risks. Models learn from data and can leak information if misconfigured. Attackers can influence training data, manipulate prompts, or exploit vulnerabilities inside AI-powered features.

The European Union Agency for Cybersecurity warns that AI introduces new attack surfaces that companies must explicitly secure. As a result, companies adopt:

• AI model monitoring.
• Prompt-level security.
• Data validation.
• Secure training environments.
• Access control.
• Audit logs for AI decisions.
• Red-teaming for model safety.

These requirements influence the engineering structure. Companies create new roles such as AI application security specialists and ML reliability engineers.

16. The global demand for engineering talent remains strong

This is the only section that touches hiring. It avoids salary talk, region recommendations, and offline services.

The demand for experienced engineers remains high in 2026. AI-native work requires strong engineering fundamentals. Companies seek developers who understand cloud systems, write clean code, adhere to secure practices, and work effectively in distributed teams. Understanding current IT technology trends is essential for career advancement.

European countries face a substantial shortage of skilled developers, and companies across the US and EU continue to look for specialists who deliver high-quality work in remote environments. Engineers with strong expertise in cloud, AI, data, and security skills have more opportunities, as companies seek stability in AI-driven workflows.

For companies that hire globally, Europe remains an attractive region due to its strong engineering education, modern tech culture, and time-zone alignment with both the US East Coast and the UK.

17. AI governance becomes a strategic concern for product leaders

AI governance covers rules, transparency, and accountability. The EU AI Act influences global standards and creates a model for other regions.

The act requires:

• Transparency for AI decisions.
• Human oversight for high-impact systems.
• Strict controls for sensitive data.
• Clear documentation.
• Risk classification.

Companies adopt internal governance systems to track how AI influences the product. They create documentation for model behavior, testing, and auditing.

In conclusion, AI governance shapes engineering work. Developers need clear instructions. Product managers track risk categories. Companies design systems that explain decisions. AI features must align with compliance frameworks.

18. Multi-cloud strategies grow in popularity

Companies adopt multi-cloud systems to reduce risk and avoid vendor lock-in. 85% of organizations report using more than one public cloud provider, and adoption is projected to grow in 2026. This represents one of the most significant trends in IT as companies distribute workloads across AWS, Azure, GCP, and regional providers.

Multi-cloud provides:

• Better uptime.
• Flexibility.
• Improved compliance.
• Optimized performance.
• Cost control.

Engineering teams must understand multiple environments. They build abstraction layers, simplify deployment, and monitor distributed workloads.

19. Product analytics becomes more important than ever

In 2026, companies focus on evidence-based decisions. AI tools support product analytics by generating insights, summarizing patterns, and identifying anomalies.

Modern analytics systems provide:

• Automatic funnel analysis.
• Retention insights.
• Event heatmaps.
• A/B test summaries.
• User segmentation.
• Forecasting tools.

Companies integrate these systems into product development workflows. Data informs feature decisions, pricing strategies, and customer experience.

20. API-first ecosystems expand across industries

APIs remain essential for integration, automation, and product innovation. Companies adopt API-first strategies to develop modular products that integrate seamlessly with partners, tools, and internal systems.

The 2025 Postman API Report shows 82% of organizations surveyed have adopted some form of “API-first” strategy. This means they prioritize APIs early in development, rather than treating them as afterthoughts. Engineering teams design APIs with clear contracts, stable documentation, and predictable behavior. They use versioning, monitoring, and automated tests to maintain reliability.

API-first design supports AI workflows, remote teams, low-code tools, and platform engineering practices. It helps companies scale without complexity.

21. IT outsourcing trends: Nearshoring, automation, and risk management

IT outsourcing shifts from pure cost arbitrage toward access to skills, resilience, and automation. Industry summaries of IT outsourcing trends emphasize several patterns:

• Increased AI and automation within outsourced services.
• A greater focus on cloud-based outsourcing.
• A shift toward multivendor strategies rather than reliance on a single large provider. 

Nearshoring in Eastern Europe continues as a strong theme. Market overviews for 2025 describe Eastern Europe as a mature outsourcing region with a large engineering talent pool and significantly lower salary levels than in the US. This keeps demand for development and support services high in countries such as Poland, Ukraine, Romania, and Bulgaria. 

At the same time, consulting analyses indicate that organizations are increasingly outsourcing infrastructure, application development, and, most importantly, cybersecurity. 

Contracts change accordingly. Buyers expect clear SLAs, security guarantees, and compliance support rather than simple staff augmentation. Providers that combine strong security practices, transparent governance, and experience with AI-enabled tooling become more attractive than purely low-cost vendors.

22. Trends in healthcare IT: AI, telehealth, and digital health platforms

Healthcare IT moves from experimentation to scaled digital operations. Health IT analysts describe a sector in which emerging trends in IT for healthcare, including AI, telehealth, and remote patient monitoring, remain central themes. Reports on AI adoption in hospitals show that AI is now embedded in many US and European hospitals for risk prediction, clinical documentation assistance, workflow optimization, and imaging support, rather than isolated pilots.

Telemedicine and remote monitoring also remain essential. OECD guidance and telemedicine market studies describe telehealth as a mainstream channel for follow-up visits, chronic disease management, and triage, supported by connected devices and patient apps.

In parallel, digital-health benchmarks such as the CHIME Digital Health Most Wired 2025 report highlight a shift from basic technology rollout toward integration, governance, and measurable impact: health systems invest in data platforms, EHR integration, cybersecurity, and accountability structures for digital tools.

For engineering teams, healthcare IT trends translate into demand for skills in interoperable data standards, secure cloud architectures, AI integration with EHRs, and regulated-environment development. Privacy, safety, and auditability remain as crucial as pure functionality.

23. IT service management trends: AI-enhanced ITSM and value focus

IT service management trends focus on AI, governance, and value. Market analyses of ITSM tools show increasing budgets for automation and AI/ML pilots inside service operations.

Gartner’s Magic Quadrant for AI Applications in IT Service Management and related commentary describe an emerging category of tools that apply AI to ticket triage, virtual agents, incident correlation, and “zero-touch” service desk ambitions. 

For IT organizations, this means that ITSM work increasingly overlaps with AIOps, observability, and experience management. Teams need skills in process design, AI-assisted workflows, data quality for ITSM platforms, and communication with business stakeholders about value delivered, not just ticket volumes.

Final thoughts on IT trends for 2026

The main IT trends of 2026 show clear patterns. AI becomes central to product development, with cyber resilience and privacy shaping engineering decisions. Platform engineering supports consistency. Data quality influences AI quality. Remote work stabilizes. European regulations influence global practices.

Companies that embrace these trends build better products, reduce risk, and move faster. Companies that ignore them risk losing their competitive edge, as customers expect more intelligent systems, safer experiences, and more reliable tools.

If your team plans to add engineers in 2026, and you want the process to stay predictable and straightforward, DNA325 helps you reach experienced specialists from across Europe. You receive shortlists, structured sourcing, and coordinated interviews so you can focus on building your product while we handle the search process.

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