This shift is happening at a rapid pace. Gartner’s 2026 technology trends highlight developments such as AI native development platforms, AI supercomputing platforms, confidential computing, multiagent systems, domain specific language models, physical AI, preemptive cybersecurity, digital provenance, AI security platforms, and geopatriation.
For businesses, however, keeping up with every emerging technology is not the goal. The more important question is which technologies can address real business challenges and support long term growth.
Here are some of the technology trends businesses should be watching in 2026.
1. AI Is Moving From Experimentation to Business Operations
Artificial intelligence is no longer limited to research teams or isolated experiments. Organizations are increasingly integrating AI into everyday business functions such as customer service, software development, knowledge management, marketing, analytics, and operations.
McKinsey’s 2025 State of AI research found that 88% of respondents reported regular AI use in at least one business function. At the same time, most organizations were still in the experimentation or pilot stage when it came to scaling AI across the enterprise.
This creates an important opportunity for businesses.
Instead of asking, “Should we use AI?” organizations are increasingly asking:
- Where can AI create measurable value?
- Which processes are suitable for automation?
- What data does AI need to work effectively?
- How can AI be introduced without compromising security or customer trust?
- How can AI solutions scale beyond a single pilot project?
The organizations that benefit most from AI will likely be those that connect technology adoption to specific business outcomes rather than adopting AI simply because it is trending.
2. AI Agents Are Changing How Work Gets Done
One of the most significant developments in AI is the rise of AI agents.
Unlike traditional AI tools that primarily respond to individual prompts, AI agents can be designed to plan and execute multiple steps within a workflow. This makes them particularly relevant to business processes that involve repetitive tasks, decision points, information retrieval, and coordination between systems.
McKinsey’s 2025 research found that 62% of respondents said their organizations were at least experimenting with AI agents, while 23% reported that their organizations were already scaling an agentic AI system somewhere in the enterprise.
This does not mean every business needs an AI agent immediately.
The more practical approach is to identify workflows where agents could provide meaningful value. Examples may include:
- Customer support and service desk workflows
- Internal knowledge retrieval
- Document processing
- Research and reporting
- Software development assistance
- Workflow coordination
- Data analysis and business intelligence
As these systems mature, organizations will also need clear governance, access controls, monitoring, and human oversight.
3. AI Native Software Development Is Emerging
AI is also changing how software is designed and developed.
AI native development platforms are becoming an important technology trend as development teams explore how generative AI can support coding, testing, documentation, debugging, and other parts of the software development lifecycle.
Gartner identifies AI native development platforms as one of its top strategic technology trends for 2026 and predicts that AI native development will contribute to changes in the structure and size of software engineering teams over the coming years.
The goal is not simply to replace developers with AI.
Instead, AI can become part of the development workflow, allowing teams to spend more time on architecture, business logic, user experience, security, and problem solving.
For organizations investing in custom software, this trend could contribute to faster development cycles while still requiring strong engineering practices, testing, security controls, and human review.
4. Domain Specific AI Is Becoming More Important
General purpose AI models are powerful, but businesses often need solutions that understand their particular industry, processes, terminology, regulations, and data.
This is where domain specific AI becomes increasingly relevant.
Gartner lists domain specific language models among its top strategic technology trends for 2026. These models are designed around particular industries or use cases, potentially helping organizations achieve greater relevance and accuracy for specialized tasks.
For example, an organization may benefit more from an AI system designed around its operational data and workflows than from a general purpose chatbot.
This reflects a broader shift in enterprise AI. The value of AI is increasingly connected to how well it fits the organization’s actual business environment.
5. Cybersecurity Is Becoming More Proactive
As businesses adopt more AI, cloud services, connected applications, and digital workflows, their technology environments also become more complex.
Cybersecurity therefore needs to evolve alongside digital transformation.
Gartner’s 2026 trends include preemptive cybersecurity and AI security platforms, reflecting a shift toward identifying and addressing threats before they cause significant damage. Digital provenance is another emerging area, focused on verifying the origin and integrity of software, data, and AI generated content.
For businesses, cybersecurity should not be treated as something added after a system has already been built.
Security considerations can be incorporated into areas such as:
- Application architecture
- Data management
- Identity and access management
- Cloud infrastructure
- AI governance
- Software development
- Third party integrations
Building security into technology decisions from the beginning can help organizations reduce unnecessary risk as their digital environments expand.
6. Cloud and Computing Infrastructure Are Evolving
The growth of AI is also increasing demand for computing infrastructure capable of supporting larger and more complex workloads.
Gartner’s 2026 technology trends include AI supercomputing platforms and confidential computing. AI supercomputing focuses on the infrastructure required to support demanding AI and data workloads, while confidential computing focuses on protecting sensitive data while it is being processed.
This highlights an important point for businesses: technology strategy is not only about applications.
The underlying infrastructure matters too.
Organizations need to consider performance, scalability, security, integration, cost, and data requirements when selecting or modernizing their technology environments.
7. Physical AI Is Bringing Intelligence Into the Real World
AI is also expanding beyond software.
Physical AI refers to systems that can sense, interpret, and act in the physical world. Gartner identifies physical AI as one of its strategic technology trends for 2026, with applications involving robotics, drones, smart equipment, and other intelligent machines.
While the adoption of physical AI will vary significantly by industry, the broader trend is important because it demonstrates how AI is increasingly becoming part of operational environments.
For sectors such as manufacturing, logistics, agriculture, healthcare, and other industries involving physical processes, this could open new possibilities for automation and intelligent decision making.
8. The Technology Skills Gap Is Becoming a Business Issue
Technology adoption is not only about systems and infrastructure. Organizations also need people who understand how to implement, manage, evaluate, and use these technologies effectively.
The World Economic Forum’s Future of Jobs Report 2025 identifies AI and big data, networks and cybersecurity, and technological literacy among the fastest growing skill areas through 2030. The report also emphasizes the continued importance of human capabilities such as analytical thinking, creativity, resilience, and adaptability.
This means businesses may need to approach digital transformation from both a technology and workforce perspective.
Investing in new platforms without developing the skills required to use them effectively can limit the value of that investment.
What Should Businesses Do Next?
The pace of technology development can make it tempting to chase every new trend. But successful technology adoption is rarely about adopting everything at once.
Instead, businesses can start by connecting technology decisions to their most important objectives.
Start With the Business Problem
Identify the processes, customer experiences, or operational challenges that need improvement before selecting a technology.
Evaluate the Data
AI and analytics initiatives depend heavily on the quality, availability, security, and governance of organizational data.
Build for Scalability
Technology investments should support future growth rather than solving only today’s requirements.
Prioritize Security
Security, privacy, governance, and access controls should be considered throughout the technology lifecycle.
Invest in People
Teams need the knowledge and skills to use new technologies effectively. Continuous learning and upskilling will become increasingly important as technology evolves.
Measure Business Outcomes
Technology adoption should ultimately be connected to measurable results such as improved efficiency, better customer experiences, faster processes, reduced operational costs, or new revenue opportunities.
The Bigger Picture
The technology trends shaping 2026 point toward a broader transformation in how organizations build and operate digital systems.
AI is becoming more embedded in business processes. Software development is becoming increasingly AI assisted. Cybersecurity is becoming more proactive. Cloud and computing infrastructure are evolving to support increasingly demanding workloads. At the same time, organizations are recognizing that technology adoption must be supported by the right data, people, processes, and governance.
The opportunity is not simply to adopt the newest technology.
It is to determine where technology can create meaningful and sustainable business value.
For organizations planning their next stage of digital transformation, the right technology strategy starts with understanding the business challenge, evaluating the available options, and building a solution that can evolve with the organization.
Ready to explore how emerging technologies can support your business goals?
Explore Solutions Resource’s technology solutions or connect with our team to discuss your digital transformation priorities.
By
By
By
