Section 6 – Commercial Methods of Classification

(1) These methods as designated in clause (iii) of sub-section (1) of Section 3 involve the categorisation of commercially produced and disseminated artificial intelligence technologies based on their inherent purpose and primary intended use, considering factors such as:

(i) The core functionality and technical capabilities of the artificial intelligence technology;

(ii) The main end-users or business end-users for the artificial intelligence technology, and the size of the user base or market share;

(iii) The primary markets, sectors, or domains in which the artificial intelligence technology is intended to be applied, and the market influence or dominance in those sectors;

(iv) The key benefits, outcomes, or results the artificial intelligence technology is designed to deliver, and the potential impact on individuals, businesses, or society;

(v) The annual turnover or revenue generated by the artificial intelligence technology or the company developing and deploying it;

(vi) The amount of data collected, processed, or utilized by the artificial intelligence technology, and the level of data integration across different services or platforms; and

(vii) Any other quantitative or qualitative factors that may be prescribed by the Central Government or the Indian Artificial Intelligence Council (IAIC) to assess the significance and impact of the artificial intelligence technology.

(2) Based on an assessment of the factors outlined in sub-section (1), artificial intelligence technologies are classified into the following categories –

(i) Artificial Intelligence as a Product (AI-Pro), as described in sub-section (3);

(ii) Artificial Intelligence as a Service (AIaaS), as described in sub-section (4);

(iii) Artificial Intelligence as a Component (AI-Com) which includes artificial intelligence technologies directly integrated into existing products, services & system infrastructure, as described in sub-section (5);

(iv) Artificial Intelligence as a System (AI-S), which includes layers or interfaces in AIaaS provided which facilitates the integration of capabilities of artificial intelligence technologies into existing systems in whole or in parts, as described in sub-section (6);

(v) Artificial Intelligence-enabled Infrastructure as a Service (AI-IaaS) which includes artificial intelligence technologies directly integrated into existing components and layers of digital infrastructure, as described in sub-section (7);

(vi) Artificial Intelligence for Preview (AI-Pre), as described in sub-section (8);

(3) Artificial Intelligence as a Product (AI-Pro) refers to standalone AI applications or software that are developed and sold as individual products to end-users. These products are designed to perform specific tasks or provide particular services directly to the user;

Illustrations

(1) An AI-powered home assistant device as a product is marketed and sold as a consumer electronic device that provides functionalities like voice recognition, smart home control, and personal assistance.

(2) A commercial software package for predictive analytics is used by businesses to forecast market trends and consumer behaviour.

(4) Artificial Intelligence as a Service (AIaaS) refers to cloud-based AI solutions that are provided to users on-demand over the internet. Users can access and utilize the capabilities of AI systems without the need to develop or maintain the underlying infrastructure;

Illustrations

(1) A cloud-based machine learning platform offers businesses and developers access to powerful AI tools and frameworks on a subscription basis.

(2) An AI-driven customer service chatbot service that businesses can integrate into their websites to handle customer inquiries and support.

(5) Artificial Intelligence as a Component (AI-Com) refers to AI technologies that are embedded or integrated into existing products, services, or system infrastructures to enhance their capabilities or performance. In this case, the AI component is not a standalone product but rather a part of a larger system;

Illustrations

(1) An AI-based recommendation engine integrated into an e-commerce platform to provide personalized shopping suggestions to users.

(2) AI-enhanced cameras in smartphones that utilize machine learning algorithms to improve photo quality and provide features like facial recognition.

(6) Artificial Intelligence as a System (AI-S) refers to end-to-end AI solutions that combine multiple AI components, models, and interfaces. These systems often involve the integration of AI capabilities into existing workflows or the creation of entirely new AI-driven processes in whole or in parts;

Illustrations

(1) An AI middleware platform that connects various enterprise applications to enhance their functionalities with AI capabilities, such as an AI layer that integrates with CRM systems to provide predictive sales analytics.

(2) An AI system used in smart manufacturing, where AI interfaces integrate with industrial machinery to optimize production processes and maintenance schedules.

(7) Artificial Intelligence-enabled Infrastructure as a Service (AI-IaaS) refers to the integration of AI technologies into the underlying computing, storage, and network infrastructure to optimize resource allocation, improve efficiency, and enable intelligent automation. This category focuses on the use of AI at the infrastructure level rather than at the application or service level.

Illustrations

(1) An AI-enabled traffic management system that integrates with city infrastructure to monitor and manage traffic flow, reduce congestion, and optimize public transportation schedules.

(2) AI-powered utilities management systems that are integrated into the energy grid to predict and manage energy consumption, enhancing efficiency and reducing costs.

(8) Artificial Intelligence for Preview (AI-Pre) refers to AI technologies that are made available by companies for testing, experimentation, or early access prior to wider commercial release. AI-Pre encompasses AI products, services, components, systems, platforms and infrastructure at various stages of development. AI-Pre technologies are typically characterized by one or more of the following features that may include but not limited to:

(i) The AI technology is made available to a limited set of end users or participants in a preview program;

(ii) Access to the AI-Pre technology is subject to special agreements that govern usage terms, data handling, intellectual property rights, and confidentiality;

(iii) The AI technology may not be fully tested, documented, or supported, and the company providing it may offer no warranties or guarantees regarding its performance or fitness for any particular purpose.

(iv) Users of the AI-Pre technology are often expected to provide feedback, report issues, or share data to help the company refine and improve the technology.

(v) The AI-Pre technology may be provided free of charge, or under a separate pricing model from the company’s standard commercial offerings.

(vi) After the preview period concludes, the company may release a commercial version of the AI technology, incorporating improvements and modifications based on feedback and data gathered during the preview. Alternatively, the company may choose not to proceed with a commercial release.

Illustration

A technology company develops a new general-purpose AI system that can engage in open-ended dialogue, answer questions, and assist with tasks across a wide range of domains. The company makes a preview version of the AI system available to select academic and industry partners with the following characteristics:

(1) The preview is accessible to the partners via an API, subject to a special preview agreement that governs usage terms, data handling, and confidentiality.

(2) The AI system’s capabilities are not yet fully tested, documented or supported, and the company provides no warranties or guarantees.

(3) The partners can experiment with the system, provide feedback to the company to help refine the technology, and explore potential applications.

(4) After the preview period, the company may release a commercial version of the AI system as a paid product or service, with expanded capabilities, service level guarantees, and standard commercial terms.