Will AI Contribute $15.7 Trillion to Global GDP by 2030?
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Synopsis
Is AI set to revolutionize the global economy? A recent report reveals that AI could contribute a staggering $15.7 trillion to global GDP by 2030. Discover the insights on national strategies, sectoral advancements, and the sociological challenges of AI adoption.
Key Takeaways
- $15.7 trillion potential contribution to global GDP by 2030.
- Over 66% of developed nations have national AI strategies.
- Financial services and retail sectors are leading in AI adoption.
- Nearly 50% of AI pilots are scrapped before production.
- AI adoption challenges are largely sociological, not technical.
New Delhi, Sep 10 (NationPress) Artificial Intelligence (AI) is rapidly establishing itself as the pivotal technology of the 21st century, with projections indicating an addition of approximately $15.7 trillion to global GDP by 2030, according to a report released on Wednesday.
According to the joint report by FICCI and Boston Consulting Group (BCG), over 66 percent of developed nations have already implemented national AI strategies, whereas only 30 percent of developing countries and 12 percent of least-developed nations have done so.
The report identifies four interconnected dimensions driving the AI race: compute, data, models, and talent.
Countries like the US and China are currently leading in AI advancements, focusing on specific interventions, while other nations possess significant potential for growth.
Particularly, sectors such as financial services and retail are at the forefront of AI adoption, largely due to their data-rich environments.
Conversely, critical areas like agriculture and public services are falling behind, hindered by fragmented infrastructure and funding limitations due to ambiguous returns on investment.
FICCI Director General Jyoti Vij emphasized, “AI is not merely a technological trend; it is a strategic competition that will shape economic and social leadership in the future. It is essential that we approach AI as a shared mission to create value for all.”
The FICCI-BCG report also pointed out that despite substantial investments, nearly 50 percent of AI pilot projects fail before reaching production, with less than one in eight prototypes achieving deployment.
Major hurdles include isolated infrastructure, a lack of skilled personnel, and cultural resistance. The report asserts that the challenges of AI adoption are more sociological than technical, with 70 percent of obstacles arising from human and organizational issues rather than technology itself.
Organizations that prioritize reskilling, cultural transformation, and workforce empowerment are more likely to translate AI into tangible business results, the report concluded.
“We are witnessing a marked divergence in the global AI landscape. Most developed economies have embraced national AI strategies, while those still developing are yet to embark on this critical journey,” said Saibal Chakraborty, Managing Director and Senior Partner at BCG.
Point of View
I believe that the insights provided by the FICCI and BCG report highlight both the opportunities and challenges surrounding AI adoption. While developed economies are making strides, it is vital for all nations to work collaboratively to harness the potential of AI for global progress.
NationPress
10/09/2025
Frequently Asked Questions
How much could AI potentially add to global GDP by 2030?
AI is projected to contribute approximately $15.7 trillion to global GDP by 2030.
What are the main sectors leading in AI integration?
Sectors such as financial services and retail are leading the way in AI integration, primarily due to their data-rich environments.
What are the barriers to AI adoption?
Key barriers to AI adoption include siloed infrastructure, skills shortages, and cultural resistance, with 70 percent of challenges stemming from human and organizational issues.
What percentage of AI pilots fail to reach production?
The report indicates that nearly 50 percent of AI pilot projects are abandoned before reaching production.
Why is AI adoption considered more sociological than technical?
AI adoption challenges are often rooted in people and processes rather than technology, highlighting the importance of organizational culture.
