Is AI Cloud burning a lot of money? Morgan Stanley: By 2025, it will be equivalent to the spending of the Apollo Space Program! Fortunately, the application side is also very optimistic

AI is advancing rapidly, with companies increasing their investments and enthusiasm in the field.

According to a report released by Morgan Stanley on the 7th, global corporate capital expenditures in the AI cloud field are expected to reach a staggering level by 2025, almost equivalent to the total cost of the famous Apollo space program in history (approximately $257 billion, adjusted for current prices).

This raises the question: Is such high-tech investment really worth it? Can AI bring about the same enormous value as the moon landing?

Furthermore, Morgan Stanley stated that despite the significant investments in generative AI by companies, generative AI has gradually shown its effectiveness in practical applications, helping companies optimize production processes, improve customer service efficiency, and achieve cost savings in multiple areas. Therefore, the outlook is very optimistic.

Cloud computing expenditures skyrocketing, companies beginning to see returns

Morgan Stanley's data shows that by 2025, global corporate capital expenditures in the field of cloud computing will approach the total cost of the Apollo program, which cost approximately $257 billion (adjusted for current prices) between 1960 and 1973.

Morgan Stanley points out that although the costs of these investments are substantial, companies have gradually shown results in practical applications, especially in the widespread adoption of generative AI and the enhancement of enterprise productivity.

Morgan Stanley's AlphaWise survey covered 400 large companies from six different industries globally, demonstrating the significant effects of generative AI in practical applications.

The data shows that most companies using generative AI have achieved or exceeded their expected return on investment, with approximately 50% of projects meeting expectations and another 40% exceeding expectations.

Furthermore, despite the initial high barriers to entry for generative AI projects, once implemented, the cost benefits it brings are significant. Morgan Stanley states that among companies with revenues less than $1 billion, 37% reported a better-than-expected return on investment; for companies with revenues exceeding $15 billion, the likelihood of generative AI projects exceeding expectations is 15 percentage points higher.

It is worth noting that large enterprises with annual revenues exceeding $15 billion are more focused on using generative AI to reduce costs, while the technology and industrial sectors are more focused on using generative AI to increase revenue. Smaller companies seek to comprehensively utilize generative AI to increase revenue while reducing costs.

Not just about costs, but also an efficiency revolution

Generative AI not only helps companies reduce costs, but also improves production efficiency.

A report by Morgan Stanley pointed out that customer service is one of the most widely used areas for generative AI applications, with all six industries surveyed indicating outstanding performance of generative AI in customer service. Especially in large enterprises, generative AI can significantly reduce the time of manual operations, enhancing overall work efficiency.

For example, the report mentioned that global retail giant Walmart updated its massive product data catalog using generative AI technology, which is 100 times faster than traditional manual operations.

Another example is the cosmetics industry, where L'Oréal uses generative AI to help customers with skin analysis and product recommendations, significantly improving the efficiency of product selection for customers, increasing sales conversion rates from 10% to over 70%.

Most companies see data security as the biggest obstacle to generative AI projects

Despite the seemingly bright prospects of generative AI, Morgan Stanley also points out that companies still face many challenges when widely adopting this technology.

Surveys show that about 60% of companies consider data security as the top issue, and 25% of companies are concerned about the reputation risks that may arise from deploying AI tools too quickly.

However, Morgan Stanley stated that despite these challenges, the long-term potential of generative AI cannot be ignored. Especially against the backdrop of a global decrease in the labor force, generative AI is expected to become a key technology in addressing productivity and labor shortages.

The report predicts that as generative AI is widely applied in enterprises, it will gradually transition from being a cost-reducing tool to a core driver of enhancing corporate competitiveness