AI to robotics: The growing convergence trend reshaping technology

AI, robotics, spatial intelligence and omni computing are converging to create smarter healthcare, manufacturing and energy systems

Much like consumers buy vehicles or furniture based on their needs, technology works best when clever combinations are applied with context. There is so much emphasis on artificial intelligence (AI) that people tend to forget that no technology is an island. Solutions are achieved when technologies converge to solve a specific problem.

 

A recent report on technological convergence by the World Economic Forum (WEF) and Capgemini highlights a growing trend. “Technology combinations have been shaping industries for years, but the pace and breadth of possibilities have expanded. Eight powerful domains — AI, omni computing, engineering biology, robotics, advanced materials, spatial intelligence, quantum and next-generation energy — are combining to create an opportunity no singular innovation could,” it says. “Convergence isn’t just a shopping list of accumulating domains; it’s a cohesive operating model. Combinatorial technologies need to be coordinated effectively to unlock capabilities that feel like step changes, not increments.”

 

A good example of this convergence can be seen in cognitive robotic systems for health care, according to the report. These systems integrate intelligent perception, reasoning, adaptive decision-making and task execution to support clinicians and enhance patient care in a more context-aware and efficient way. In this suite of technology, robotics, AI, spatial intelligence, advanced materials and omni computing come together.

 

The suite could be developed as robots have become affordable and capable while new materials enabled smaller and safer instruments. This allows precise manipulation even in confined spaces. At the same time, AI and spatial computing provide a richer understanding of the operative field by identifying anatomy, tracking instruments, flagging anomalies and revealing subsurface structures before the first incision in telesurgery. Such improvements are supported by expanding omni computing capacity that makes real-time guidance technically feasible. The combined progress across domains signals a shift from isolated innovations towards integrated and intelligent surgical solutions.

 

Omni-Cloud computing is a distributed model that enables organisations to manage, deploy and run applications anywhere and everywhere. It offers a breadth of coverage, greater flexibility and reduced latency — capabilities essential for delivering superior user experiences and optimising resource distribution. This mix-and-match Cloud service helps companies to connect different applications and audiences, placing them closer to users to improve their experience. This means mixing Clouds for different jobs, such as Amazon for websites, Azure for data analysis and Google for other tasks.

 

Another example of expanding use of tech suites is digital twins for advanced manufacturing, says the WEF report. Digital twin ecosystems in manufacturing are real-time virtual representations of assets and processes that mirror physical operations to optimise operations, predict failures and improve efficiency. Digital twins were once limited by fragmented data, immature spatial models and experimental AI, limiting them to basic visualisation and planning. Multiple capabilities are advancing in parallel and beginning to converge. Sharp advances in AI have unlocked the ability to simulate thousands of scenarios, learn from real-world conditions and automatically optimise design and process decisions. Such advancements have transformed digital twins from slow and passive models into rapid, real-time systems.

 

A power grid must manage renewable energy transmission, distribution and storage. Progress in omni computing and AI gives operators real-time visibility into grid conditions and the ability to optimise charge, discharge and power flows across multiple value streams. Spatial intelligence enables the simulation of infrastructure impacts and the strategic placement of assets to deliver the greatest system benefit. Together, these advances are shifting the grid from a reactive, centralised system into an adaptive, real-time network that continuously balances energy across distributed resources. As technology evolves, companies may have to curate their own suite of converged options.

The writer is an economic analyst and author