Market Overview

Swarm Intelligence Market is expected to register a CAGR of over 37% during the forecast period (2020 - 2025). The market is driven by the application of artificial intelligence through the integration of biological behavior.

  • The movement of goods and logistics along different routes increases the operational costs for business, along with the travel time. This generates the need for analytical models that can be solved through the Swarm model, thereby driving the demand for Swarm Intelligence during the forecast period.
  • The adaptation of the cooperative Multi-Agent System (MAS) across the healthcare domain is expected to be driven by the real-time closed-loop intelligence moderated by SI algorithms, thereby increasing demand for swarm intelligence platform.
  • The growing trend of predicting sports and financial trends, as well as to accesses the effectiveness of advertisements and movie trailers, through the interfaces and AI algorithms, has driven the human swarms to converge online thereby combining the knowledge, wisdom, insights, and intuitions of diverse groups into a single emergent intelligence.

Scope of the Report

Swarm intelligence is the seemingly intelligent behavior that emerges from the collective behavior of a large number of autonomous agents. It derives the collective behavior of self-organized, decentralized systems of either natural or artificial systems, that basically deals with the collective behaviors resulting from the local interactions of the individuals with each other as well as with their environment.

Key Market Trends

Transportation & Logistics Sector is Gaining Traction Due to Emergence of Optimisation Algorithm

  • Increasing usage of swarm intelligence for solving the location problems along with the rising adoption of swarm-based drones in the military is expected to drive the demand for its application in the transportation and logistics sector.
  • In transportation, the increases operational costs for business, as well as high travel time is catered the need for analytical models that can be solved using the swarm intelligence-based Ant Colony Optimization algorithm for optimizing the route, which would further propel the growth of the market across the transportation sector during the forecast period.
  • The embedded process of Swarn Intelligence across retail logistics provides huge opportunities for e-commerce players to automate their delivery services across their operating regions.

North America to Register as the Largest Growing Market During the Forecast Period

  • The growing demand for automation and route analytics due to the automation in the retail e-commerce sector is considered to be growing at a very high rate across the emerging economies of the US market dynamics which is expected to drive the market during the forecast period.
  • The United States is considered one of the major contributors to the growth of swarm intelligence across North America which is attributed to the increased adoption of swarm-based drones in the military and defense services.
  • Also, the application of the swarm intelligence system along with the AI integration helps in detecting major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation across the North America region.

Competitive Landscape

The Swarm Intelligence market is moderately competitive and consists of a few major players. In terms of market share, some of the players currently dominate the market. However, with the advancement in behavioral intelligence, new players are increasing their market presence thereby expanding their business footprint across the emerging economies.

  • February 2019 - Unanimous AI created Swarm, the world’s first AI platform that amplifies the intelligence of business teams. This breakthrough technology has been used to improve diagnostic accuracy, financial market forecasting, and provide insight into a wide variety of complex problems.
  • July 2018 - Swarm Technology aims to enable fleets of drones and robots to collaborate on shared tasks. The company demonstrated four autonomous vehicles powered by Atmel 8-bit microcontrollers working in tandem to balance on a see-sawing board. A controller board reported to the group over a Zigbee network changes in the board’s axis and each responded using a patented approach for sharing intent.

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