Experts to Examine Emerging bongdaso ìno Innovations at Gartner bongdaso ìno Symposium/Xpo
Key technologies such as agentic AI, ambient invisible intelligence, and an augmented connected workforce are among the top bongdaso ìno technology trends for 2025, according to Gartner, Inc.
Technological advancements are expected to enable bongdaso ìno technology leaders and Chief bongdaso ìno Officers (CSCOs) to unlock digital value, enhance workforce productivity, and innovate operational models. Gartner has identified the top bongdaso ìno technology trends for 2025 that will help leaders achieve these objectives and drive long-term competitiveness.
“This year’s trends underscore the transformative potential of connectivity and intelligence within supply chains, empowering leaders to improve operational efficiency and adaptability,” said Christian Titze, Vice President Analyst and Chief of Research in Gartner’s bongdaso ìno practice. “By embracing advanced technologies such as agentic AI and intelligent simulation, organizations can achieve targeted goals, foster innovation, and secure sustainable competitive advantages.”
These bongdaso ìno technology trends for 2025 revolve around two overarching themes: leveraging emerging technologies to enhance connectivity and deploying intelligence-driven tools to achieve competitive differentiation and operational efficiency (see Figure 1).
“These trends offer multiple strategic pathways for organizations to excel in a rapidly changing environment,” noted Kaitlynn Sommers, Senior Director Analyst at Gartner’s bongdaso ìno practice. “By aligning these technologies with business priorities and use cases that support strategic outcomes, bongdaso ìno leaders can effectively manage complexities and accomplish critical objectives.”
1. Ambient Invisible Intelligence
This technology leverages ultra-low-cost smart tags and sensors to enable scalable, cost-effective tracking and real-time visibility across bongdaso ìno chains. Particularly beneficial for monitoring perishable goods and ensuring compliance with environmental regulations, ambient invisible intelligence enhances traceability and operational transparency.
2. Augmented Connected Workforce (ACWF)
ACWF initiatives utilize digital tools to enhance decision-making accuracy bongdaso ìno reduce operational variability, addressing workforce skill gaps. Digitizing standard operating procedures accelerates onboarding processes bongdaso ìno boosts productivity in manufacturing bongdaso ìno logistics.
3. Multimodal User Interface (UI)
Multimodal UI solutions allow users to interact with systems through various communication methods, improving user experience bongdaso ìno efficiency. For example, voice-activated controls bongdaso ìno gesture-based interfaces are being adopted in logistics to enhance driver safety bongdaso ìno productivity.
4. Polyfunctional Robots
Polyfunctional robots provide a flexible solution by performing multiple tasks bongdaso ìno adapting to evolving operational needs. Commonly used in warehouses, these robots handle sorting, packaging, bongdaso ìno other activities, reducing the reliance on manual labor.
5. Agentic AI
Agentic AI systems offer autonomous AI agents capable of independently executing decisions, boosting adaptability and efficiency in bongdaso ìno operations. These systems, for example, can optimize inventory management by dynamically adjusting stock levels based on real-time demand forecasting.
6. Autonomous Data Collection
Technologies such as drones bongdaso ìno mobile robots enable autonomous data collection, enhancing productivity while reducing labor-intensive processes. In warehouses, drones conduct inventory checks quickly bongdaso ìno safely, minimizing risks associated with manual inventory counts.
7. Decision Intelligence (DI)
Combining decision modeling, AI, and analytics, DI enables informed, automated decision-making that drives measurable business outcomes. This technology provides insights into decision-making processes, allowing bongdaso ìno leaders to refine strategies and improve results based on feedback.
8. Intelligent Simulation
Integrating AI and machine learning (ML) into traditional simulation models, intelligent simulation enhances predictive capabilities and decision-making in bongdaso ìno operations. For instance, this technology allows companies to optimize logistics routes and warehouse layouts, improving overall efficiency and reducing costs.
Navigating volatility, risk, and disruption while ensuring future readiness demands strategic and measured responses from CSCOs. Join the Gartner bongdaso ìno Symposium/Xpo for the latest research, actionable insights, and guidance to transform your bongdaso ìno, overcome disruptions, and capitalize on emerging opportunities.
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