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Recently, Gartner announced their Top 10 Strategic Technology Trends for 2025. Gartner, Inc. is a highly respected technological research and consulting firm based in Stamford, Connecticut, that conducts and publishes research on technology and technology trends.

It’s interesting to note there is a decided evolution from more traditional growth in digital and computing capabilities to more sophisticated systems that blur the boundaries between human and machine intelligence. The leading trends for 2025 have as much to do with ethically and responsibly managing new technologies as they do in creating them.

Here are the Top 10 Technology Trends for 2025:

10. Neurological enhancement

Also known as neuroenhancement. This refers to the practice of using scientific methods to improve cognitive functions in healthy individuals, essentially boosting brain performance beyond what is considered normal. It involves directly manipulating the nervous system through drugs, brain stimulation, implants, or other interventions. It aims to enhance abilities like memory, decision-making, attention/focus, and learning capacity. 

Elon Musk and his Neuralink company are pioneering this field, developing implants that allow individuals to control devices with their thoughts.

9. Polyfunctional robots

Polyfunctional robots are machines that can perform multiple tasks, as opposed to task-specific robots, which are designed to perform a single task over and over again. Polyfunctional robots can also learn and adapt to new situations.

Applications for polyfunctional robots can include cleaning, cooking, homework assistance, financial and bookkeeping functions, and physical infrastructure inspection.

8. Spatial computing

Spatial computing technology combines input from the physical world with digital data in real time. It allows users to interact with computers in a more immersive way. It’s typically accessed via a headset, goggles, or smartphone.

Spatial computing includes augmented reality (AP), virtual reality (VR), mixed reality, extended reality, and more. Examples of spatial computing applications include immersive gaming and entertainment experiences, healthcare training, and modeling factory processes.

7. Hybrid computing

Hybrid computing refers to either a hybrid computer or a hybrid cloud.

A hybrid computer combines the features of both analog and digital computers. Hybrid computers are used for tasks that require both types of processing, such as scientific research, weather forecasting, and flight simulations. 

A hybrid cloud is an IT infrastructure design that combines a company’s internal IT resources with third-party cloud provider infrastructure and services. Hybrid clouds allow users to store data and run applications across multiple environments. Benefits of hybrid cloud computing include scalability, security, cost, control, and speed. 

6. Energy-efficient computing

Computers, and AI applications in particular, require a huge amount of energy to operate efficiently and at productive levels of speed. Energy-efficient computing has become instrumental to addressing the growing need for massive amounts of energy and concern over the environmental impact of data centers and AI workloads.

5. Ambient invisible intelligence

Ambient invisible intelligence is the combination and integration of sensing technologies into everyday environments, operating without user intervention. It uses a combination of sensors, processors, actuators, and AI to collect, share, process, and respond to data.

Ambient invisible intelligence aims to create smart, intuitive environments that anticipate and respond to user needs without requiring direct interaction.

The most obvious example may be smart homes and home environmental management and security systems. Other applications include medication management, food and supply chain management, and retail inventory management.

4. Postquantum cryptography (PQC)

Quantum attacks are cyberattacks that use quantum computers to break encryption methods and steal data.

Quantum computers use quantum physics to perform calculations faster and more efficiently than traditional computers. Quantum computers can work on millions of computations at once, while a desktop PC works on one. They are often used in cyberattacks to break encryption methods.

Post-quantum cryptography (PQC) (a.k.a. quantum-resistant or quantum-safe cryptography) is a new generation of cryptographic algorithms that are designed to protect against attacks from quantum computers.

3. Disinformation security

It’s no secret that there are a lot of efforts on the Internet to intentionally spread false information. These malicious activities are designed to manipulate public opinion, undermine trust, and even cause outright harm. Disinformation security refers to the combination of strategies, tools, and practices used to protect against the intentional spread of false information.

Disinformation security technology seeks to ensure the integrity of information, identify false information, verify authenticity, and prevent impersonation.

2. AI governance platforms

AI governance platforms seek to address the growing need for responsible implementation of AI in whatever form it takes. AI governance platforms endeavor to help ensure AI implementations are reliable, transparent, fair, accountable, and meet safety and ethical standards. According to Gartner, “These technology solutions have the capability to create, manage and enforce policies for responsible AI use, explain how AI systems work and provide transparency to build trust and accountability.”

Top 10 #1: Agentic AI

Gartner named agentic AI as the number one trend in it’s top 10 tech trends for 2025.

Agentic AI refers to software programs (also referred to as agents) that can make decisions, plan and take actions independently, learn from interactions, and make choices to achieve specific goals defined by a human. These systems combine AI capabilities with memory, planning, environmental sensing, safety guidelines, and other inputs to autonomously complete tasks, which could boost productivity and improve efficiency.

Unlike traditional AI, agentic AI can consider various factors and make choices without direct human intervention.

This technology is primarily shifting from query-and-response systems to autonomous machine agents capable of performing enterprise-related tasks without human guidance. Examples of existing and potential agentic AI applications include customer service chatbots, supply chain optimization, financial investment bots, and self-driving cars.