The CEO of renowned cybersecurity firm Palo Alto Networks, Nikesh Arora, has publicly criticized the current cost structure of artificial intelligence (AI) technology. In an interview, Arora emphasized that the high price of AI services remains a major barrier to the adoption of the technology in global corporate environments.
Arora set an ambitious target for the tech industry, namely a 20 percent drop in the cost of using Large Language Models (LLMs) by 2027, reaching a 90 percent reduction by 2028. According to him, this price adjustment is an absolute prerequisite for AI to deliver sensible economic value to companies.
This criticism comes amid the limited effectiveness of AI in fulfilling its long-promised workforce automation potential. Instead of replacing human roles to cut operational costs, the trillion-dollar investments in the AI sector are perceived as not yet yielding proportional real-world results for companies, triggering a dilemma for executives.
Echoing Arora's sentiments, tech analyst Ed Zitron remarked that the current valuation of the AI industry seems forced. He sees a massive gap between market value claims and the actual real demand on the ground. This situation is viewed as a sign that the business models of current AI service providers may not be sustainable without prompt price efficiencies.
Pressure from major industry players like Palo Alto Networks sends a strong warning signal to AI developers. Going forward, service providers are urged to innovate quickly to lower operational costs without compromising quality, ensuring that investments in this technology remain relevant and profitable for corporate users.
