Goldman Sachs published a research paper questioning the economic viability of generative AI, stating that there is “little to show for” the massive spending on generative AI infrastructure. The paper raises doubts about whether generative AI will live up to its hype and become a transformative technology. Despite these concerns, Goldman Sachs acknowledges the potential for continued investment and stock market gains. The paper also highlights the optimism surrounding AI, driving growth in stocks like Nvidia, but warns that stock gains are already factored in and may not materialize. The paper concludes that AI’s impact on corporate profitability will be critical. Goldman Sachs researchers express skepticism about the cost and transformative potential of generative AI, stating that the technology is unreliable and incapable of solving complex problems. The report compares the AI hype to other technologies like virtual reality and blockchain, which have yet to find widespread real-world applications. The skepticism surrounding generative AI extends beyond journalists and workers to financial institutions that have invested billions in the AI industry.
Nvidia’s AI chips may generate a lower expected increase in corporate revenues, casting doubt on the optimistic outlook for the AI revolution. Reports from Goldman Sachs, Barclays, and Sequoia Capital highlight the massive amount of capital being spent on AI infrastructure and the significant revenue companies will need to generate to justify these investments. The lack of revenue raises skepticism about the feasibility of AI’s potential. Unknowns such as cost savings, solving complex problems, and energy supply further complicate the outlook for AI’s growth.
And let’s add to that this: According to a study by Lucidworks, concerns over accuracy and cost are slowing down the adoption of generative AI in the enterprise. 44% of manufacturers are worried about the accuracy of GenAI output, leading to a more cautious approach and fewer AI investments compared to last year. The challenges of cost and accuracy are seen as fundamental to the business of AI and could potentially impact the industry’s growth.
Why do we care?
We’re rocketing into the depths of the pit of despair as it relates to AI, as reality of the costs of the technology and finding practical uses begins to become the priority. For IT service providers, this means focusing on sustainable investments, client education, and the development of reliable and cost-effective AI solutions. Guide clients in identifying practical use cases where generative AI can deliver tangible benefits. And remember, right now, data is the key preparation.