Potential Impact of Gartner’s 2025 Ten Technology Trends on Manufacturing
The technological landscape is shifting at an unprecedented pace, with innovations redefining how industries operate, connect, and evolve. Gartner’s strategic technology trends for 2025 showcase the tools shaping the near future, from AI-driven autonomy to sustainable computing paradigms. For manufacturers, these trends represent more than just possibilities—they are an urgent call to action to drive efficiency, resilience, and innovation.
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Manufacturing has always been at the forefront of industrial transformation, from the steam engine to automation. But today’s advancements have opened doors to unprecedented synergy between human ingenuity and machine intelligence. Below, we explore Gartner’s 10 technology trends and their implications for manufacturing by 2025 and 2030.
1. Agentic AI
Agentic AI refers to autonomous systems that proactively make decisions and execute tasks without requiring step-by-step user input. This new generation of AI expands on current automation by offering flexibility and initiative.
Impact on Manufacturing:
2025: High – Expect rapid adoption in areas like supply chain optimization and predictive maintenance, where autonomous decisions can reduce downtime and inefficiencies.
2030: Very High – Factories may leverage fully autonomous AI agents for dynamic production planning, seamlessly integrating with IoT and MES systems to execute changes in real-time.
2. AI Governance Platforms
These platforms ensure AI systems are used responsibly, ethically, and in compliance with regulations, providing transparency and risk management.
Impact on Manufacturing:
2025: Medium – Early adoption to address concerns in highly regulated sectors (e.g., pharmaceuticals) where auditability and compliance are paramount.
2030: High – Widespread integration as AI governance becomes essential for maintaining stakeholder trust and avoiding liabilities across diverse manufacturing operations.
3. Disinformation Security
Technologies to combat misinformation, such as deepfake detection, protect organizations from reputational harm and operational disruptions.
Impact on Manufacturing:
2025: Low – Limited immediate impact as most threats are external and not yet pervasive in manufacturing.
2030: Medium – As manufacturing becomes more interconnected, disinformation targeting supply chains or product quality could require robust countermeasures.
4. New Frontiers of Computing
Innovations like quantum computing and low-cost sensors are creating new computational capabilities, revolutionizing problem-solving in industries.
Impact on Manufacturing:
2025: Medium – Quantum computing’s potential is mostly theoretical but could emerge in material science or process optimization. Low-cost sensors will likely see earlier adoption for real-time tracking.
2030: Very High – Widespread adoption of quantum-enhanced algorithms and smart sensors will reshape manufacturing through unparalleled precision and efficiency gains.
5. Energy-Efficient Computing
IT systems are being redesigned for sustainability, reducing carbon footprints with greener architectures and energy-efficient hardware.
Impact on Manufacturing:
2025: Medium – Manufacturers will seek low-carbon IT solutions for smart factories to meet emerging sustainability mandates.
2030: High – Sustainability will drive the wholesale transformation of data centers and production systems, powered by renewable energy and optimized compute infrastructure.
6. Hybrid Computing
A paradigm combining quantum, neuromorphic, and other specialized computing forms, tailored to solve diverse problems collaboratively.
Impact on Manufacturing:
2025: Low – Initial experimental phases limit tangible benefits, though promising pilots may arise in R&D-intensive sectors.
2030: High – Hybrid systems will enable advanced simulations for production scenarios, helping manufacturers address complex challenges with reduced costs and lead times.
7. Human-Machine Synergy
Integrating humans and machines through spatial computing, augmented reality (AR), and collaborative robotics for seamless interactions.
Impact on Manufacturing:
2025: High – AR-enhanced training and polyfunctional robots will enhance worker productivity and safety.
2030: Very High – The manufacturing floor may evolve into a collaborative space where humans and intelligent machines work symbiotically to achieve unprecedented efficiency.
8. Polyfunctional Robots
Robots capable of performing multiple tasks, adapting dynamically to changing requirements without extensive reprogramming.
Impact on Manufacturing:
2025: Medium – Useful in high-mix, low-volume production environments to reduce retooling times.
2030: Very High – Polyfunctional robots will dominate factories, providing unparalleled flexibility and lowering the cost of production shifts.
9. Neurological Enhancement
Technologies like brain-machine interfaces (BMIs) enhance human cognitive abilities, boosting productivity and precision in complex tasks.
Impact on Manufacturing:
2025: Low – Adoption will be limited to niche areas like high-stakes assembly or design work.
2030: Medium – Enhanced operators using BMIs could revolutionize high-skill tasks, from advanced welding to CAD design.
10. Sustainable Technology
A focus on environmental responsibility through innovations that minimize waste and optimize resource use.
Impact on Manufacturing:
2025: Medium – Adoption of circular economy practices and renewable energy in facilities will gain traction.
2030: Very High – Sustainability will become a core tenet, with every aspect of manufacturing optimized for energy efficiency and waste reduction.
A Production-Centric View
The transformative potential of emerging technologies in manufacturing lies in their shared characteristics: autonomy, real-time adaptability, enhanced efficiency, and sustainability. Across the board, these trends emphasize the ability to make smarter, faster decisions based on interconnected systems and vast streams of data. For manufacturers, the challenge isn’t just identifying which technologies to adopt but determining how to evaluate their value, implement them effectively, and prepare operations for long-term success. These innovations are not just tools—they are enablers of entirely new ways to approach production.
To explore how these technologies can benefit your manufacturing operations, consider these steps:
Identify Testbeds: Select specific, low-risk areas within your operations—such as maintenance, inventory management, or quality control—where new technologies can be tested without significant disruptions.
Define Metrics for ROI: Evaluate the value of these technologies based on more than financial return. Include metrics such as operational efficiency, time savings, scalability, and sustainability impact.
Engage Stakeholders Early: Bring in cross-functional teams to assess technological alignment with broader organizational goals and gain buy-in from key decision-makers.
Iterate and Refine: Conduct pilot programs, gather data, and make iterative improvements to the implementation process, ensuring scalability for wider adoption.
Preparation is key because while the specifics of some trends may evolve, the technologies themselves are rapidly advancing and becoming more accessible. Success in this evolving landscape depends on a strong infrastructure focused on connectivity, visibility, and control. Connectivity ensures that all systems—machines, sensors, software, and people—communicate seamlessly. Visibility provides real-time insights into production performance and operations, while control allows manufacturers to act on these insights dynamically. Achieving these capabilities requires a foundation built on solid data architecture and a robust Manufacturing Execution System (MES).
For example, consider how Agentic AI could revolutionize production workflows when integrated with MES. An agentic AI system, capable of autonomous decision-making, could analyze sensor data from IoT devices to predict machine failures or identify process bottlenecks. Through MES, this AI system could initiate maintenance workflows, adjust production schedules, or even reroute materials to optimize output—all in real-time and without human intervention. The MES acts as the bridge, turning the AI’s insights into actionable changes on the shop floor while maintaining traceability and compliance.
Similarly, polyfunctional robots could be seamlessly integrated into MES to handle dynamic task assignments. MES would ensure that these robots are deployed where needed most, coordinating their operations with other machinery and human workers. For example, in a high-mix, low-volume production line, MES could use data on order volumes and deadlines to direct robots to switch between assembly, packaging, or inspection tasks as priorities shift. This level of orchestration ensures that robots work as part of a cohesive, flexible production system rather than isolated units.
Trends like energy-efficient computing and sustainable technologies also highlight the need for an interconnected production ecosystem. Energy consumption data from machines, gathered by IoT sensors and analyzed by MES, could inform decisions about when and where to run high-energy processes. By aligning this data with broader sustainability goals, MES can help manufacturers balance operational efficiency with environmental responsibility.
Ultimately, the role of MES is to enable full integration across the production environment, ensuring that every system and technology works together harmoniously. By providing the connectivity, visibility, and control required to leverage these trends, MES turns cutting-edge technologies into practical, scalable solutions. A well-optimized MES not only prepares manufacturers for today’s innovations but also creates a resilient foundation ready to adapt to future advancements. As technologies like hybrid computing, ambient intelligence, and neurological enhancements continue to evolve, manufacturers with strong MES frameworks will be best positioned to capitalize on their potential.
References:
Gartner - 2025 Strategic Technology Trends: https://www.gartner.com/document-reader/document/5850447
