Quantum AI next big thing in AI evolution

Source: GlobalData

Quantum AI emerges as the next big advancement in AI development, utilizing quantum mechanics to propel capabilities beyond current limits. With a notable 14% 3-year CAGR increase in patent filings from 2020 to 2022, quantum AI has vast influence and potential across industries, reveals the Tech Foresights model of GlobalData.

The technology landscape is dynamically evolving, necessitating a coherent data-driven framework to make the right bets at the right time. GlobalData’s Tech Foresights model is a data-driven, predictive innovation intelligence model that leverages multiple forward-looking indicators to decode future disruptions today.

Adarsh Jain, Director of Financial Markets at GlobalData, comments: “Quantum AI represents a transformative advancement in technology. As we integrate quantum principles into AI algorithms, the potential for speed and efficiency in processing complex data sets grows exponentially. This not only enhances the current AI applications but also opens new possibilities across various industries. The significant rise in patent filings is a testament to its growing importance and the key role it will play in the future of AI-driven solutions.”

Kiran Raj, Practice Head of Disruptive Tech at GlobalData, adds: “AI thrives on large amounts of data and computational power, but the inner workings of the technology often remain unclear. Quantum computing promises to offer not only more power but also potentially greater insights into these workings. This leads us to a future where AI can do more than just process data. It can create and innovate in ways we are just starting to explore.”

An analysis of GlobalData’s Disruptor Intelligence Center highlights the synergy between quantum computing and AI innovations for a revolutionary impact across various industries. Key developments include HSBC and IBM’s collaboration in finance, Menten AI’s healthcare advancements, Volkswagen’s partnership with Xanadu for battery simulation, Intel’s Quantum SDK, and Zapata’s collaboration with BMW.

Raj concludes: “Quantum AI offers the potential for smarter, faster AI systems, but its adoption is complex and requires caution. The technology is still in its early stages, demanding significant investment and expertise. Key challenges include the need for advanced cybersecurity measures and ensuring ethical AI practices, as we navigate this promising yet intricate landscape.”