BCG-WEF Project: AI for India 2030

Shaping the AI Sandbox Ecosystem for the Intelligent Age

Artificial intelligence is rapidly transforming economies and societies, with advances in generative models, intelligent agents, and autonomous systems opening new frontiers for growth. This rapid evolution presents countries with a dual imperative: accelerating innovation while ensuring it remains responsible, inclusive, and aligned with the public interest.

India is well positioned to lead this transformation. With strong digital public infrastructure, a vibrant startup ecosystem, and a large, multilingual population, the country offers an ideal testbed for building and scaling AI solutions that address both domestic and global priorities. However, India continues to face structural challenges, such as limited access to localized datasets and compute infrastructure, a lack of standard validation frameworks, and constrained support for early-stage startups.

AI sandboxes offer a timely solution to address the most critical of these challenges. They provide secure, controlled environments where innovators can test, validate, and refine AI solutions using real-world data, infrastructure, and regulatory guidance. Globally, such sandboxes have been deployed in regulatory, innovation, and hybrid formats in sectors such as health care, finance, and education.

Research by the World Economic Forum, India’s Ministry of Electronics and Information Technology, and BCG offers a comprehensive framework for catalyzing the establishment of AI sandboxes. The framework has been developed through consultations with more than 20 experts, a multistakeholder workshop with over a dozen AI-first startups, and global benchmarking of best practices. It comprises two key components:

1. A strategic framework that outlines five layers of the AI sandbox ecosystem—infrastructure, data, models, innovation, and governance—each embedding enablers for the creation of AI solutions and guardrails for responsible deployment.

2. An operational framework that defines four phases of implementation:

• Defining the objectives and scope aligned with national and sectoral priorities
• Establishing multistakeholder governance and access protocols
• Designing and developing sandbox components, including datasets, compute infrastructure, models, and validation tools
• Establishing the AI sandbox, tracking outcomes, and scaling through structured adoption and commercialization pathways

The framework addresses five systemic challenges in India’s AI ecosystem: data accessibility and governance; access to compute infrastructure; model affordability and contextual representation, regulatory uncertainty, and lack of awareness around validation mechanisms; limited avenues for market access; and limited ecosystem enablement. It positions sandboxes not merely as pilot environments but also as long-term national platforms that propel responsible AI innovation and deployment.

Multiple stakeholders can contribute to the success of AI sandboxes. The government can play a catalytic role by funding pilots and enabling national coordination. Industry has an essential role in contributing infrastructure, expertise, and mentorship. Academia is critical for driving validation efforts and leading capacity-building initiatives. Startups are central to the sandbox’s success through active participation, continuous feedback, and codevelopment of scalable, real-world solutions. Regulators provide crucial oversight and guidance to shape safe and responsible experimentation environments. Together, these efforts can help establish AI sandboxes as a cornerstone of India’s AI strategy, positioning the country as a leader in inclusive, scalable, and trusted AI development.

Transforming Small Businesses: An AI Playbook for India’s MSMEs

Micro, small, and midsize enterprises (MSMEs) are the backbone of India’s economy, contributing nearly 30% of GDP, employing more than 230 million people, and accounting for nearly half of India’s exports. Their growth trajectory is crucial for achieving India’s ambition of becoming a $7 trillion economy by 2030.

MSMEs in India face challenges such as operational inefficiencies, limited financial resources, and constrained scalability. Artificial intelligence can enable these enterprises to overcome the challenges and generate more than $490 billion in economic value. Yet multiple barriers to AI adoption threaten to impede progress.

Research by the World Economic Forum, India’s Ministry of Electronics and Information, and BCG sheds light on these barriers, explores how stakeholders in government, industry, MSME associations, and academia could alleviate them, and presents a playbook to help policymakers design appropriate interventions and help the MSME ecosystem to become AI-ready.

The Need for an AI Playbook

The implementation of AI systems in Indian MSMEs is hindered by significant obstacles, including a lack of AI awareness and of data and data systems, low accessibility of relevant solutions, and undeveloped workforce capabilities.

The AI playbook—the outcome of design thinking–driven research, ethnographic studies, expert consultation, and contextual analysis—serves multiple purposes:

• To articulate and highlight the major barriers faced by MSMEs in their AI adoption journey.
• To offer an overview of major AI use case categories in the MSME ecosystem and present a framework to enable MSMEs to prioritize relevant use cases.
• To inspire MSMEs to use the transformative power of AI by showcasing real-world case studies.
• To provide a call to action as well as a detailed implementation roadmap delineating the role of various stakeholders.

The playbook also includes a structured approach to scaling AI adoption in Indian MSMEs, aligning stakeholder efforts around three pillars:

Awareness. This focuses on bridging knowledge gaps and building trust among MSMEs regarding AI adoption. It includes establishing AI experience centers, AI sandboxes, and capability-building programs to demonstrate the practical benefits of AI solutions and foster peer-to-peer learning.

Action. This is designed to equip MSMEs with actionable tools and frameworks such as the AI maturity index, an AI solutions marketplace, and alternative financing options. It enables businesses to assess their readiness, identify suitable solutions, and effectively implement AI technologies.

Recognition. This emphasizes the showcasing of successful early adopters as role models through an MSME AI pioneer program. By celebrating pioneers, this pillar aims to inspire confidence, encourage broader adoption, and foster ecosystem-wide momentum toward AI transformation.

Call to Action

Accelerating AI adoption and realizing its transformative potential within India’s MSMEs requires all stakeholders to collaborate and take concrete steps forward. Policymakers can establish enabling environments and infrastructure; MSME entrepreneurs can make efforts to understand and embrace AI; and AI startups and solution providers can focus on creating affordable and accessible solutions tailored to MSMEs. Collective action will empower India’s MSMEs and drive their economic growth.

Future Farming: A Playbook for Scaling Artificial Intelligence in Agriculture

As the climate crisis threatens the Indian farmer’s future by triggering extreme weather events, pushing costs up, and reducing yields, digital technologies and AI, in particular, hold the promise of revolutionizing Indian agriculture. If these technologies can be deployed at scale, they’re likely to transform farming practices, boost productivity while reducing costs, and ensure that farming in India becomes more sustainable in spite of climate change.

India’s agriculture, fishing, and forestry sector is the country’s largest employer, accounting for more than 40% of the working population, but its contribution to the country’s GDP, at 18%, is the lowest. That’s partly because the sector faces several challenges, including low productivity, fragmented landholdings, and limited access to markets and finances.

AI can help address those challenges by enabling more efficient, productive, and resilient agricultural practices. Several AI pilots, such as the Saagu Baagu project in the Indian state of Telangana, have increased yields, reduced costs, and improved farmers’ access to markets.

Scaling the use of digital technologies to reach millions of smallholder farmers demands a structured approach that can tackle the barriers and create an enabling environment. Research by the World Economic Forum and BCG—based on consultations with policymakers, researchers, industry leaders, agritech startups, and farmers—has yielded a roadmap for deploying AI solutions at scale that is based on three pillars: Enable, Create, and Deliver.

Enable focuses on the role of governments in catalyzing AI deployment in agriculture. The goal is to develop strategies that reflect regional needs while ensuring scalability and inclusivity by developing policies that guide AI procurement, incentivize innovation, and ensure data sharing. Central to this pillar is the creation of a data infrastructure that aggregates and standardizes agricultural data.

Create is centered on driving innovation by startups and innovators. Collaboration is critical; stakeholders can co-develop AI solutions by leveraging research institutions’ domain expertise to address real-world challenges. Validating solutions is equally important; pilots and testing will ensure that AI applications in Indian agriculture are scalable, reliable, and commercially relevant.

Deliver is all about ensuring that AI solutions reach the farmer, with extension systems and farmer networks playing the role of central actors. Extension workers must be retrained to integrate AI into advisory roles so that farmers receive actionable insights. And setting up feedback loops will allow the refinement of AI solutions that address farmers’ challenges.

These three pillars provide a foundation for building an AI-driven agricultural economy in India, aligning the efforts of stakeholders to foster a scalable AI ecosystem that will empower farmers, drive innovation, and transform Indian agriculture into a resilient and sustainable industry.

AI applications in agriculture are being piloted around the world. The World Economic Forum’s AI4AI framework has identified and assessed around 30 use cases spanning the stages of the agriculture value chain. Examples include intelligent crop planning, smart farming, and farm-to-fork solutions. The analysis identified the datasets needed for each use case and outlined a roadmap for operationalizing these AI applications by 2030.