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Prompt Engineer, dedicated to learning and disseminating knowledge about AI, software engineering, and engineering management.

MIT NANDA research finds that only 5% of organizations successfully scale AI tools into production. American companies have invested between $35 billion and $40 billion in generative AI projects, yet so far, they have seen almost no return on investment. According to a report from MIT NANDA (Network AI Agents and Decentralized AI), 95% of corporate organizations have received zero returns from their AI investments. Only 5% of organizations have successfully integrated AI tools into production at scale. The report is based on structured interviews with 52 corporate leaders, an analysis of over 300 public AI projects and announcements, and a survey of 153 business professionals. The authors of the report—Aditya Challapally, Chris Pease, Ramesh Raskar, and Pradyumna Chari—attribute this "generative AI gap" to the inability of AI systems to retain data, adapt to environments, and learn continuously, rather than a lack of infrastructure, learning resources, or talent. > The "generative AI gap" is most evident in deployment rates, with only 5% of customized enterprise AI tools making it into production. "The 'generative AI gap' is most evident in deployment rates, with only 5% of customized enterprise AI tools making it into production," the report states. "Chatbots succeed because they are easy to try and flexible, but they fail in critical workflows due to a lack of memory and customization capabilities." As one anonymous CIO said in an interview with the authors, "This year we saw dozens of demos. Maybe only one or two were truly useful. The rest were either 'shelled' products or science experiment projects." The authors' findings align with other recent studies indicating that corporate leadership's confidence in AI projects is declining. The NANDA report does mention that a small number of companies have found uses for generative AI, and that the technology is having a substantial impact in two of nine industrial sectors—technology and media & telecommunications. For the remaining sectors—professional services, healthcare & pharmaceuticals, consumer & retail, financial services, advanced manufacturing, and energy & materials—generative AI has remained irrelevant. The report cites an anonymous COO from a mid-market manufacturing company: "The hype on LinkedIn is overwhelming, saying everything has changed, but in our actual operations, there has been no fundamental change. We process some contracts faster, but that's about it." One thing that is indeed changing is the employment landscape, at least in the affected industries. The report notes that in technology and media, "over 80% of executives expect to reduce hiring within 24 months." According to the authors, layoffs driven by generative AI are primarily occurring in non-core business activities that are often outsourced, such as customer support, administrative processing, and standardized development tasks. "These positions were already vulnerable due to their outsourced nature and process standardization before AI implementation," the report states, noting that 5% to 20% of support and administrative processing roles in affected industries have been impacted. According to The Register, Oracle's recent layoffs reflect its efforts to balance AI capital expenditures, which have become a heavy burden on the necks of American tech giants. Meanwhile, at IBM, employees feel that AI has been used as an excuse to shift jobs overseas. Regardless of the public reasons and true motivations behind the layoffs, generative AI is indeed impacting the technology and media & telecommunications sectors, which are also the areas where it is most widely adopted. Although about 50% of AI budgets are allocated to marketing and sales, the report's authors suggest that corporate investments should flow toward activities that can produce meaningful business outcomes. This includes front-end lead qualification and customer retention, as well as back-end reductions in business process outsourcing, advertising agency spending, and financial services risk assessments. The report points out that general tools like OpenAI's ChatGPT perform better than customized enterprise tools, even if those enterprise tools use the same underlying AI models. The rationale presented in the report is that employees are often more familiar with the ChatGPT interface, leading to more frequent use—this is a result of employees' spontaneous "shadow IT". The report quotes an interview with a company lawyer who described her mid-sized law firm's dissatisfaction with a specialized contract analysis tool that cost $50,000. "The summaries provided by the AI tool we purchased were very rigid, and the customization options were limited," the lawyer told researchers. "With ChatGPT, I can guide the conversation, iterate repeatedly, until I get exactly what I need. The fundamental quality difference is obvious; ChatGPT consistently produces better results, even though our vendor claims they use the same underlying technology." The authors believe that companies that successfully cross the "generative AI gap" approach AI procurement more like outsourcing business process services rather than as customers of software as a service (SaaS). "They demand deep customization, drive applications from the front lines, and hold vendors accountable for business metrics," the report concludes. "The most successful buyers understand that crossing this gap requires building partnerships, not just purchasing products."®

AI is gradually replacing outsourced and offshore workers. According to the "2025 Business AI Status" report released by MIT, artificial intelligence is not yet taking away your job. On the contrary, AI is currently mainly replacing outsourced and offshore labor. Why it matters: As American workers feel the pressure of a tightening labor market and worry about a wave of layoffs in white-collar jobs, MIT's findings indicate that the impact of AI is currently occurring mainly in more distant locations, although the long-term risks are much greater. What they say: Aditya Challapally, head of the MIT Media Lab's "Connected AI" group, told Axios: "There doesn't seem to be any layoffs at the moment. ... The jobs most affected are those that are lower priority or have already been outsourced." • The report points out that companies find that the real benefits come from "replacing business process outsourcing (BPO) and external agencies, rather than cutting internal staff." Looking at the big picture: Challapally stated that while 3% of jobs may be replaced by AI in the short term, in the long run, that number could be close to 27%. • Industries considered early adopters of AI are feeling the immediate impact on labor first. • In the technology and media sectors, over 80% of surveyed executives expect hiring to shrink in the next two years. These are also the only sectors showing clear signs of being impacted by AI. • Nevertheless, most surveyed companies are currently using AI to fill employee vacancies rather than directly replacing them. The data speaks: Currently, companies are not laying off employees but are simply canceling contracts involving outsourced labor, a strategy that is yielding financial benefits. • Back-office automation has also led to higher returns on investment, with the companies studied by MIT researchers cutting BPO spending by $2 million to $10 million. • One of the companies studied saved $8 million annually by spending $8,000 on an AI tool. The subtext: It is estimated that 50% of AI budgets are directed towards sales and marketing. • This may indicate that while back-office tools can save more money, front-office tools are receiving more investment. • This could also be because measuring the outcomes of AI-driven front-office work is more challenging. (For example, it is difficult to determine if AI really helped you achieve more sales in a year.) Key insights: For investors betting that AI will drive productivity growth, this report brings both hope and reveals risks. • Among organizations investing in generative AI, 95% have not seen any return on investment. • But Challapally said companies are indeed seeing "significant improvements in productivity." Core takeaway: If AI can enhance productivity, help companies cut costs, and not trigger mass layoffs, this could be an ideal "Goldilocks" scenario for investors—driving profit growth while avoiding the economic drag of widespread unemployment.

Today, there’s a hot news story on Hacker News about California's unemployment rate rising to 5.5%, the lowest in the nation, with the tech industry struggling: "The job market is too brutal." > According to data released by the state government on Friday, California's unemployment rate rose to 5.5% in July, ranking first among all states in the U.S. This is attributed to the ongoing weakness in the tech industry and other office jobs, along with a sluggish hiring market. The news attributes this to the weakness in the tech industry, as it plays a crucial role in California's economy. The discussion in the Hacker News community has been intense, with people analyzing the deeper reasons from their perspectives, which are far more complex than what the headline suggests. I think the discussion above summarizes well why the tech industry is currently experiencing low employment. 1. The core point is: the multiple aftereffects of saying goodbye to the "zero interest rate era" This is the most mainstream and profound viewpoint in the discussion. Many believe that the current predicament of the tech industry is not caused by a single factor, but rather a chain reaction triggered by the end of the "zero interest rate policy" (ZIRP) era over the past decade. - Capital bubble burst: From around 2012 to 2022, extremely low interest rates made capital exceptionally cheap. A large amount of venture capital (VC) flooded into the tech industry, giving rise to countless business models that relied on "burning money" for growth, especially those cryptocurrencies (Crypto) and metaverse companies that lacked real value. With the Federal Reserve raising interest rates, the era of cheap money ended, leading to a break in the funding chains of these companies, resulting in massive layoffs and bankruptcies. - Talent supply-demand imbalance: During the ZIRP era, the myth of high salaries in the tech industry attracted a large influx of talent. University computer science (CS) programs expanded significantly, coding boot camps proliferated, and coupled with tech immigration, the supply of software engineers surged dramatically over the decade. However, as capital retreated, the demand side (especially startups) shrank sharply, leading to a severe oversupply of talent. - Spillover effects on industries like biotech: Industries like biotechnology (Biotech), which also rely on long-term, high-risk investments, have also been severely impacted. These industries are even more dependent on cheap capital than the software industry. After ZIRP ended, VC funding gradually dried up, and startups, having exhausted their "runway" funds, could not secure new rounds of financing and had to lay off employees or shut down. > (by tqi): "In my view, it’s too early to say that 'AI' has a substantial impact on hiring in software companies. A more reasonable explanation is that between 2012 and 2022, the supply of software engineers surged... Meanwhile, on the demand side, the VC funds during the zero interest rate era mainly went to those nonsensical cryptocurrencies and metaverse companies, most of which failed, leading to a lack of later-stage or newly listed companies that could absorb this talent." 2. The "double-edged sword" of remote work: A new wave of globalization outsourcing The COVID-19 pandemic popularized remote work (Work From Home, WFH), which was seen as a boon by many developers at the time, but now, its negative effects are beginning to surface. - Paving the way for outsourcing: When developers fought hard for the right to work fully remotely, they may not have realized that this also opened the door for companies to outsource jobs to countries with lower costs. Since everyone is remote, why not hire an Indian or Eastern European engineer who is just as good but only earns 1/5 of what a U.S. engineer makes? - The "no turning back" office: Some commentators believe that the "Return to Office" (RTO) policies pushed by tech companies are, to some extent, aimed at protecting local jobs. Once it is proven that work can be done 100% remotely, it can be done from anywhere in the world, and the salary advantage of U.S. engineers will no longer exist. - Debate over outsourcing quality: Others argue that outsourcing has been ongoing for decades, and high-quality software development still requires top local talent due to issues like communication costs, time zone differences, and cultural backgrounds. However, supporters of outsourcing believe that as remote collaboration tools mature and management models improve, these barriers are gradually being overcome. > (by aurareturn): "I’ve been saying on HN since 2022: all North American developers supporting fully remote work will be shocked when your company decides to replace you with overseas workers. Since it’s all remote, why would a company pay you five times more instead of a harder-working, less complaining overseas employee?... Supporting the return to the office may, in the long run, save your career." 3. The role of AI: A productivity tool, a layoff excuse, or a capital "vampire"? The role of artificial intelligence (AI) in this wave of unemployment presents complex divisions in the discussion. - Limited direct substitution effect: Most people agree that current AI cannot fully replace experienced software engineers. However, it has begun to replace some junior, repetitive tasks, such as minor consulting tasks. Some consultants have reported that clients no longer contact them because they can use ChatGPT to solve minor bugs. - The "perfect excuse" for layoffs: A common viewpoint is that AI has become the "perfect excuse" for companies to lay off employees and cut costs. Even if the fundamental reason for layoffs is economic downturn or management decisions, companies are happy to package it as a strategic adjustment of "embracing AI and improving efficiency." - The "black hole" of capital: AI plays another key role—it siphons off the remaining venture capital that could have flowed into other tech fields. VCs are now almost exclusively interested in AI projects, exacerbating the financing difficulties for startups in non-AI sectors. 4. The "rust belt" of the tech industry? Structural concerns for the future Some discussants express concerns about the future from a more macro perspective, comparing the tech industry to the once-glorious but now declining manufacturing "rust belt." - Repetition of job losses: Just as the U.S. outsourced manufacturing to China, IT and software development jobs are now massively shifting to India, Latin America, and Eastern Europe. This could lead to long-term structural unemployment for the once high-paying software engineer group. - Political and social impacts: If a large number of middle-class tech jobs disappear, it could trigger new social and political issues, just as the decline of the "rust belt" continues to influence the political landscape in the U.S. - Controversy over immigration and visa policies (H1B/O1): Some discussions point fingers at work visas like H1B, arguing that they are abused, driving down local engineers' salaries and intensifying competition. Others staunchly defend tech immigration, believing that it is these top talents from around the world (like graduates from the University of Waterloo) that form the cornerstone of innovation in Silicon Valley. 5. Company management and cultural changes: The "Musk effect" An interesting viewpoint suggests that Musk's massive layoffs at Twitter (now X) have created a demonstration effect. - Rationalization of layoffs: When Musk laid off over 75% of Twitter's employees, the product continued to operate, prompting many CEOs to reflect: "If he can do it, why can’t I?" This broke the past mindset of tech companies that "more talent is better," making large-scale layoffs psychologically and commercially easier to accept. 6. Political and policy factors: Controversies over tax law changes A technical but far-reaching clue is about changes in U.S. tax law. - R&D expense amortization rules (Section 174): A provision in the 2017 tax reform bill (TCJA) by the Trump administration requires companies to amortize software development salaries and other R&D expenses over five years starting in 2022, rather than deducting them in full in the year incurred as before. This greatly increases the tax burden on tech companies (especially startups) and suppresses their willingness to hire domestically. - Recent legislation's remedial effect: The recently passed "Build Back Better" (BBB) act partially corrected this issue, allowing domestic R&D expenses to be deducted immediately again. Some commentators believe they felt a warming in the hiring market around July, which may be related to this. In conclusion From these discussions, it appears that the reasons for the current low employment in California's tech industry are quite complex and not caused by a single factor. It cannot simply be attributed to "AI replacing humans" or "cyclical industry downturns," but rather a result of the economic reckoning following the end of the zero interest rate era, the restructuring of the global labor market brought about by remote work, the dual impact of AI as a new technology and capital magnet, and changes in specific tax policies, among other factors. I wonder when we will be able to emerge from this predicament? Or perhaps the reasons are not just those discussed above.

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