Edge computing has rapidly emerged as a transformative force in the digital era, fundamentally reshaping how enterprises handle, assess and utilise data. As the proliferation of connected devices picks up pace and 5G networks become ubiquitous, edge computing is influencing every industry by challenging the notion that cloud-based computer processing must happen near data centres to be efficient.

A look at the broad spectrum of edge computing applications across major enterprise verticals…

Healthcare and pharmaceuticals sector

The healthcare sector is undergoing a digital transformation. It generates vast amounts of data from patient records, diag­nostic equipment and wearable devices. Traditional cloud-based solutions often struggle with the real-time demands of modern healthcare, where delays can impact patient outcomes. Edge computing addresses these challenges. Processing data at the edge enables faster analysis of medical data, supporting quicker diagnoses and treatment decisions. Edge devices facilitate real-time artificial intelligence (AI) analytics in operating rooms, improving surgical precision and outcomes. Some hospitals are also using edge capabilities for services like ePharmacy and nurse handovers. A case in point is Manipal Hospital, which is leveraging advanced technologies like AI and edge computing. The hospital has reportedly brought down its ePharmacy order processing time from 15 minutes to less than five minutes and curtailed nurse handover durations from 90 minutes to just 20 minutes. Parallelly, patients can be monitored at home using edge-enabled devices, reducing the need for hospital visits and enabling timely interventions. Edge devices are also critical for detecting critical diseases like sepsis and skin cancer. Edge computing ensures that sensitive health data remains local, minimising the risk of breaches during data transmission.

Meanwhile, the adoption of edge computing supports the industry’s shift towards Pharma 4.0, facilitating digital compliance, paperless operations and enhanced data integrity to meet stringent regulatory requirements. Additionally, edge computing offers benefits like improved security, scalability and lower total cost of ownership, while supporting advanced techno­logies such as AI, machine learning (ML) and augmented reality (AR)/virtual reality for maintenance and training. As pharmaceutical companies strive to innovate and remain competitive, integrating edge compu­ting into their digital transformation strategies is becoming essential to achieve greater agility, compliance and productivity.

Banking and financial services

The financial sector, known for its strict regulations and the need to safeguard sensitive information, faces unique challenges due to concerns over data privacy and compliance, especially when data must remain within national borders. Another key challenge is protecting this sector from cyber threats. In August 2024, nearly 300 small local banks in India had to temporarily shut down their payment systems due to a ransomware attack on a technological service provider.

Edge computing addresses these issues by enabling localised processing and storage of sensitive financial data, significantly reducing regulatory risks and the potential for data breaches. With real-time analytics at the edge, financial institutions can deliver more personalised customer experiences, such as instant loan approvals and rapid fraud detection. Additionally, edge computing supports continuous monitoring of financial operations, allowing banks to identify anomalies and manage risks proactively. It can also assist banks in safeguarding consumers from problems at the transaction site, such as at ATMs fitted with CCTV cameras. Further, by processing data closer to its source, financial organisations can accelerate their digital transformation initiatives while upholding the highest standards of security and regulatory compliance.

Retail

Retailers are increasingly using edge computing to improve both in-store and online shopping experiences, as the ability to process data in real time is essential in today’s fast changing retail landscape. With edge-powered technologies, stores can offer features like interactive mirrors, automated checkouts and smart shelves, all of which contribute to a more seamless and engaging shopping experience. Real-time data collected from sensors and cameras helps retailers track and replenish inventory dynamically, reducing the chances of running out of stock. Edge solutions also provide the scalability and flexibility needed to quickly respond to shifting market trends and customer expectations.

Many large retail chains are adopting enterprise edge strategies, centralising data storage while deploying a consistent app­lication environment across all locations. Amazon, for instance, is reportedly exploring edge computing, piloting these solutions at its Amazon Fresh and Go stores through their Dash Carts and their “Just Walk Out” technology. The Dash Carts use an array of sensors and cameras powered by edge computing to create a mobile checkout system on wheels. “Just Walk Out” has been used successfully in several formats and allows customers to grab products off the shelf and leave the store without stopping at the checkout station. This approach allows individual stores to benefit from advanced technology without the need for significant on-site computing resources, enabling retailers to streamline operations, personalise customer service, and introduce innovations like AR for a richer shopping journey.

Autonomous vehicles

Autonomous vehicles, or self-driving cars, generate massive volumes of data provided by numerous sensor inputs, such as radar, light detection and ranging (LiDAR) technology and traffic cameras. The navigation system needed to process this information in real time is critical for enabling safe navi­gation and collision avoidance. Relying on cloud-based analytics can introduce critical latency, especially in complex driving scen­arios. In addition, ML models running at the edge can predict component failures, reducing downtime and maintenance costs. Further, edge-as-a-service allows automakers to deploy new features and updates efficiently, supporting the evolution of connected and autonomous vehicles. Some of these features include remote door locking/unlocking, sunroof control, remote parking and engine ignition/stop.

Earlier this year, Bengaluru Metro Rail Corporation Limited received its first fully Indian-made driverless train for the Yellow Line. Looking ahead, as autonomous and connected vehicles become more prevalent, edge computing will be integral to their safe operation and continual innovation.

Manufacturing

Manufacturing is a central pillar of the Industry 4.0 movement, where smart factor­ies depend on real-time data to optimise production processes, minimise downtime and improve product quality. By integrating intelligence at the edge, manufacturers gain the agility and responsiveness needed to stay competitive in a rapidly evolving market. Edge devices on the factory floor process data from internet of things (IoT) sensors, allowing for immediate detection and response to anomalies or deviations, which is crucial for predictive maintenance and quality assurance. For instance, Karnataka-based diversified contract manufacturer Aequs Group is utilising industrial edge computing platforms for ensuring low-latency analysis and decision-making across its production lines. IoT sensors gather information related to machine performance, environmental parameters and product quality.

Local data processing also reduces the need to transfer large volumes of information to distant data centres, saving bandwidth and improving efficiency.

Edge computing further supports automation and ensures a steady supply of raw materials by coordinating production activities in real time. An emerging application is tiny ML, which leverages edge computing to identify manufacturing irregularities early, enabling timely maintenance, redu­cing downtime and lowering operational costs. Additionally, wearable technologies that incorporate edge computing are being used in manufacturing, such as smart jackets equipped with device charging capabilities, demonstrating the diverse ways edge intelligence is transforming the industry.

Agriculture and allied activities

Edge computing is also reshaping agriculture by enabling real-time, on-site data processing, which is crucial for an industry fa­cing resource constraints and environmental pressures. By allowing data from IoT sensors, drones and advanced imaging devices to be analysed directly in the field, farmers can make faster, more informed decisions about crop health, soil conditions and pest management, leading to timely interventions that boost yields and reduce losses. This local processing is especially valuable in rural areas with unreliable connectivity, as it ensures that essential systems remain operational without constant reliance on cloud networks.

Edge computing also supports a range of applications, including precise resource (such as livestock) management through monitoring soil, pests, weather and animal health, predictive maintenance of machinery via real-time sensor alerts, and the use of autonomous equipment that optimises operations and reduces labour costs and prevents diseases among animals. Farmers can also oversee their fields remotely, making d­­ata-driven decisions that enhance sustainability and minimise waste. By keeping sensitive data on-site, edge computing improves secur­ity and traceability across the agricultural supply chain, making modern farming more efficient, resilient and transparent.

Aigroedge Technologies, a start-up based in New Delhi, has created cutting-edge digital solutions for the specialist agriculture sector that are powered by AI and IoT sensors.  For instance, its product KRAASHAKâ is an AI-powered edge IoT sensory device that uses a patented expert system to anticipate parameters impacting plant development, identify diseases and assess physical quality in order to increase yielding.

Conclusion

Edge computing is revolutionising enterprise operations across healthcare, finance, retail, manufacturing and agriculture. By bringing data processing closer to the source, organisations can achieve real-time insights, improved efficiency and enhanced security. As the technology continues to evolve, its impact will only grow, with industry estimates stating that the Indian edge computing market is poised to reach a projected revenue of $41,374.9 million by 2033, growing at a CAGR of 42.4 per cent from 2025 to 2033. This will usher in a new era of smart, connected and agile enterprises.