Artificial Intelligence, the estimated market share of which is $207.9 billion in 2023, is projected to surge by 788.64% to reach $1.87 trillion by 2030.

The market share is anticipated to exceed the $1 trillion threshold for the first time in 2028 at $1.06 trillion, according to data obtained by Finbold, a rapidly expanding platform that provides extensive coverage of the latest financial news.

Elsewhere, India ranks first among countries with the highest level of trust in AI systems, with a score of 75%. China comes in second with a score of 67%, followed by South Africa in third place with a score of 57%. Brazil ranks fourth with a score of 56%, while Singapore takes the fifth spot with a score of 45%. The US comes in sixth place with a score of 40%.

Factors influencing AI market growth

Despite the varying AI systems’ trust scores, the technology market share is projected to continue surging in the coming years, driven by various factors. Notably, the growing demand for automation will likely increase the need for AI services.

As many businesses seek to automate their processes to reduce costs and increase efficiency, AI-powered automation tools can help achieve these goals. Moreover, the increasing availability of data from various sources can be leveraged to develop more sophisticated AI algorithms, driving growth.

Furthermore, as AI becomes more widespread and accessible, it is also expected to expand into new industries and use cases. Government investments in AI research and development and regulations to ensure AI’s ethical and responsible use can also drive growth in the AI market.

Drivers of AI systems trust score

Trust in AI systems is highly contextual and dependent on the specific application or use case, with significant variation observed across different jurisdictions. Despite this variability, AI is revolutionising technology, driving rapid innovations, and transforming industries and services with tools such as ChatGPT taking the lead.

However, the acceptance of these changes depends on the level of trust among different populations, and it is the central mechanism through which other drivers impact AI adoption.

Overall, trust in AI systems can be attributed to several factors, such as the institutional pathway, where people rely on authoritative sources and institutional processes to assure the technology’s safety and reliability. At the same time, the perceived benefits of AI potentially motivate trust, while uncertainty about its future impact is a possible driver of distrust, making people more concerned about its potential risks.

India’s high trust score in AI systems can be attributed to various factors. One of the significant contributors is the country’s emphasis on promoting digital literacy and technological advancements, leading to a better understanding of AI among the population. Furthermore, India has a robust tech industry, with startups at the forefront of developing AI applications, which has likely increased confidence in these systems.

Elsewhere, China is also emerging as an AI hub due to the country’s robust technology landscape that, in return, influences trust. Chinese companies dominate the sector by developing products such as facial recognition technology and other AI use cases. The Chinese government’s collection of vast amounts of data is also benefiting AI companies with government contracts.

The future of AI

On the flip side, AI still presents risks and challenges, with concerns about the trustworthiness of different systems, including data, algorithms, and applications. This is especially true following incidents of various AI platforms perceived as biased, discriminatory, manipulative, or unlawful.

For AI to be fully embraced and its benefits realised, it is crucial that the public trusts that it is being developed and used responsibly. In this line, several tech industry players have raised the alarm over the technology’s possible threats. For instance, Tesla CEO Elon Musk is on record warning that if unchecked, AI systems could lead to “civilisation destruction.”

Sustaining this trust is essential for accepting and adopting AI in society. To achieve this, AI systems must be designed and developed with responsibility and transparency, ensuring they do not go against societal norms.

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