Why India is poised to lead its digital future

This article is authored by Ankan Pal, assistant professor, BITS Pilani.

India's digital transformation has unlocked countless possibilities, yet there lies an untapped opportunity--one that could possibly transform how the world forecasts - from election results to economic trends. Opinion trading, globally known as information markets, has emerged as a sophisticated form of collective forecasting, and has quietly evolved from medieval forecasting practices into a data driven powerhouse. Unlike traditional polls or expert analyses, these markets thrive on a simple truth: When diverse perspectives merge in a structured, incentivised system, the resulting predictions often surpass even the most sophisticated models. India, with its unique blend of technological scale, analytical talent, and democratic engagement, stands at the brink of a breakthrough. While western platforms like Kalshi and Polymarket dominate headlines, homegrown innovators such as Probo and MPL Opinio are proving that the next chapter of this revolution could be written in India.

Digital era

Long before data-driven forecasting, humans relied on market mechanisms to gauge the future. One of the earliest documented examples dates back to 1503 in Rome, where crowds gathered to exchange views on the election of the next pope. Far from mere speculation, these interactions represented an early form of collective forecasting--a dynamic system where participants contributed their judgments, refining forecasting through shared knowledge.

By the 1800s, this practice had matured into a sophisticated instrument for political forecasting. Publications such as The New York Times began incorporating market-derived electoral odds into their reporting, recognising their remarkable accuracy to aggregate market sentiment. These platforms didn’t just estimate outcomes - they systematically distilled the wisdom of diverse participants into reliable and objective forecasts. The 20th century brought further validation when economist Friedrich Hayek, in his seminal 1945 work, highlighted markets’ unique ability to transform dispersed information into actionable intelligence--a principle that remains foundational to prediction markets today.

A pivotal shift occurred in the late 1980s with the creation of the Iowa Electronic Markets (IEM), an academic initiative that transformed how we understand collective intelligence. Unlike traditional polling methods, this regulated platform enabled participants to engage in structured and objective forecasting of US elections through event contract trading. Its consistent outperformance of conventional polls demonstrated how properly designed systems could harness collective insight to achieve superior predictive accuracy.

This breakthrough resonated across industries. By the 1990s, technology leader Hewlett-Packard (HP) had implemented internal forecasting exchanges where teams could evaluate product performance through structured participation. Simultaneously, DARPA--the pioneering US defence research agency credited with the invention of foundational internet technologies--began investigating how these market mechanisms could enhance strategic foresight and national security preparedness.

The methodology received rigorous validation in 2011 through the landmark Good Judgment Project, a collaboration between US intelligence agencies and academic institutions. In a striking demonstration of collective intelligence's power, carefully structured groups of ordinary citizens outperformed seasoned analysts in forecasting global events. This finding, complemented by seminal research articles like The Promise of Prediction Markets, cemented these systems' value as indispensable tools for both private sector strategy as well as public policy formulation.

The technology sector quickly recognised the transformative potential of prediction markets. Google pioneered this adoption through its internal forecasting platforms--initially launching Prophit from 2005 to 2011, followed by the more advanced Gleangen in 2020. These systems demonstrated remarkable efficiency, enabling Google to accurately forecast product development timelines, staffing requirements, and even operational challenges during global health crises. Not to be outdone, Meta (formerly Facebook) contributed to this evolution by developing Prophet, an open-source forecasting tool that integrates Artificial Intelligence (AI) to enhance predictive capabilities.

What began as a corporate experiment, has now entered the financial mainstream. Kalshi, operating under CFTC regulation, has reached a $2 billion valuation with support from prominent investors including Sequoia Capital. The platform's strategic alliances with major financial institutions, notably its partnership with Robinhood, signal growing institutional acceptance of prediction markets as legitimate financial instruments.

The sector continues to evolve through innovative collaborations. Polymarket, backed by PayPal and Palantir co-founder Peter Thiel, has formed a notable partnership with X (formerly Twitter), merging predictive analytics with social media engagement. Simultaneously, SIG--a leading quantitative trading firm on Wall Street--has expanded into sports prediction markets, demonstrating the versatility and expanding applications of these forecasting systems across domains.

The consistent superiority of these forecasting systems stems from three foundational pillars that work in unison. At their core lies a powerful incentive structure that directly rewards accuracy, creating a self-correcting mechanism where participants are motivated to conduct thorough research and refine their assessments continuously. This built-in reward mechanism ensures the most reliable insights to naturally rise to prominence.

Beyond individual accuracy, these platforms excel at synthesising the collective intelligence of diverse participants. By aggregating hundreds or thousands of independent perspectives, they effectively create the wisdom of crowds effect. The resulting market prices do not represent a single viewpoint but rather a dynamic consensus that evolves in real-time as new information emerges.

Perhaps most crucially, these systems possess an unmatched capacity for rapid adaptation. Unlike traditional surveys that capture sentiment at a single moment, prediction markets incorporate and reflect new data almost instantaneously as the market adjusts itself to the changes. This was demonstrated during events like the Covid-19 pandemic.

As global platforms like Kalshi, with its CFTC-regulated status, and Polymarket, through its integration with social media platform X, redefine the boundaries of collective intelligence systems, India finds itself at a crossroad. The parallels with previous technological revolutions in semiconductors, quantum computing, and social media are unmistakable. Yet in this domain, India possesses unique advantages: A digitally-connected population exceeding 950 million users, proven expertise in scaling intermediary platforms such as fantasy sports and emerging domestic innovators in this space like Probo and MPL Opinio.

The path to leadership is evident through strategic regulation that fosters innovation, leveraging India's world-class digital infrastructure, and nurturing homegrown information markets. This convergence represents more than an economic opportunity--it is a chance to usher in the beginnings of a Gyaanyug, an era where democratic participation and collective intelligence combine to create unprecedented forecasting capabilities. With the rules of this new paradigm being written now, India's next moves will determine its position in the coming age of data-driven forecasting.

This article is authored by Ankan Pal, assistant professor, BITS Pilani. (He was part of a recent data intensive study, conducted in collaboration with IIT Delhi, which quantifies the predominance of skill components in prediction markets)