
Agentic AI Is The New Vaporware
The hype term 'agentic AI' is the latest trending buzzword to repackage pie in the sky AI ambitions, but it does not allude to any particular advancement that might achieve them. It amplifies the overpromising narrative that we're rapidly headed toward a great leap in autonomy – most extraordinarily, toward the most audacious goal of all, artificial general intelligence, the speculative idea of machines that could automate virtually all human work.
Setting unrealistic expectations compromises real value. Generative AI and predictive AI deliver concrete opportunities that will continue to grow, but the claim that technology will soon hold 'agency' is the epitome of vaporware. It only misleads, setting up the industry for costly, avoidable disillusionment.
Most high-tech terms – such as machine learning, predictive modeling or autonomous driving – are legit. They represent one of two things: a specific technical approach or a novel goal for technology. But the terms 'agent' and 'agentic' fail in both respects: 1) Most uses of 'agentic' do not refer to any novel technical methodology and 2) the ambition of increasing autonomy is not new – even as the word falsely implies otherwise on both accounts. Here's a breakdown of those two failings and their ramifications.
1) 'Agentic' Does Not Refer To Any Particular Technology Or Advancement
'Agentic AI' poses as a credible near-term capability, but it represents only the most self-evident goal there could be for technology – increased automation – not a means to get there. Sure, we'd like a large language model to complete monumental tasks on its own – including gathering and assimilating information and completing online tasks and transactions – but labeling such ambitions as 'agentic' does not make them more feasible.
The term 'agentic AI' intrinsically misleads. Its sheer popularity widens the belief that technology will soon become capable of running much more autonomously, but the buzzword does not refer to any particular technical approach that may get us there. Its trendiness serves to institutionalize the notion that we're nearing great new levels of automation – 'agentic AI' is so ubiquitous that it may sound 'established' and 'real' – and this implies the existence of a groundbreaking advancement where in fact there is none.
Despite the fact that the vast majority of press about 'agentic AI' only promotes this hype narrative with no substance to support it, autonomy itself is often a worthy goal and researchers are conducting valuable work in the pursuit of increasing it. For example, a recent collaboration between Carnegie Mellon University and Amazon curates a large testbed of modest tasks in order to assess how well LLMs can manage them autonomously. This study focuses on information retrieval tasks, such as 'Retrieve an article discussing recent trends in renewable energy from The Guardian' and 'Retrieve a publicly available research paper on quantum computing from MIT's website.' The study evaluates clever approaches for using LLMs to navigate websites and automatically perform such tasks, but I would not say that these approaches constitute groundbreaking technology. Rather, they are ways to leverage what is already groundbreaking: LLMs. As the study reveals, the state of the art currently fails at these modest tasks 43% the time.
2) 'Agentic' Presents No New Goal Or Purpose
'Agentic AI' spotlights machine autonomy as if it were a new ambition, but it's an old, self-evident goal. There's no new, revolutionary thrust at play. While the buzzword is somewhat malleable and fuzzy, it generally refers to the desire for increased autonomy – 'agentic AI' means hypothetical machines that could perform substantial tasks on their own. This has always been a core, fundamental objective. The very purpose of any machine is to automate some or all of what would otherwise be carried out by a person or animal. Put another way, we build machines to do stuff.
By reiterating our innate desire to automate, 'agentic' only states the obvious. Sure, the more machines can safely do for us, the better. But there's a fairly stubborn limit to the scope of tasks that can be fully automated with no human in the loop. For example, predictive AI instantly decides whether to allow each credit card charge, whereas the wholesale replacement of physicians with machines is a very long way off at best. 'Agentic AI' is as redundant as 'evil Sith Lord,' 'book library' or 'data science.'
To be clear, autonomy is often a worthy goal and there is potential for LLMs to excel, at least where the scope of automation is somewhat modest. Economic interests exert pressure to increase autonomy – and various societal concerns exert pressure in both directions. But the scope of unleashed machine autonomy only increases quite slowly. One reason is that technology doesn't improve as quickly as advertised. Another is that cultural and societal inertia tends to spell slow adoption.
The Farfetched Notion Of Machine 'Agency'
There's another problem with using the words 'agent' and 'agentic' to evoke the goal of autonomous machines: Crediting machines with 'agency' is fantastical. This doubles down on AI's core mythology and original sin, the anthropomorphization of machines. The machine is no longer a tool at the disposal of humans – rather, it's elevated to have its own human-level understanding, goal-setting and volition. It's our peer. Essentially, it's alive.
The spontaneous goal-setting that comes with agency – and its resulting unbottleability – have been seeping into the AI narrative for years. "AI that works doesn't stay in a lab," writes Kevin Roose in The New York Times. "It makes its way into weapons used by the military and software used by children in their classrooms." In another article, he wrote, 'I worry that the technology will... eventually grow capable of carrying out its own dangerous acts.' Likewise, Elon Musk, one of the world's most effective transmitters of AGI hype, announced safety assurances that cleverly imply a willful or dangerous AI. He says that his company's forthcoming humanoid robot will be hardwired to obey whenever anyone says, 'Stop, stop, stop.'
The story of technology taking on a life of its own is an age-old drama. We need to see this high tech mythology for what it is: a more convincingly rationalized ghost story. It's the novel Mary Shelley would have written had she been familiar with algorithms. The implausible, unsupported notion that we're actively progressing toward AGI – aka artificial humans – underlies much of the hype (and often overlays it explicitly as well). 'Agentic' invokes this narrative.
Despite the unprecedented capabilities – and uncanny, seemingly humanlike qualities – of generative AI, the limit on how much human work can be fully automated will continue to only very slowly budge. I believe that we will generally need to settle for partial autonomy.
Don't buy 'agentic AI' and don't sell it either. It's an empty buzzword that, in most uses, overpromises. The AI industry runs largely – although certainly not entirely – on hype. To the degree that it continues to overinflate expectations, the industry will ultimately face a commensurate burst bubble: the dire disillusionment and unfulfilled debt that result from unmet promises.
Hashtags

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
4 minutes ago
- Yahoo
TD Cowen Reiterates a Buy Rating on Verizon Communications (VZ) With a $50 PT
Verizon Communications Inc. (NYSE:VZ) is one of the best . In a report released on July 7, Michael Elias from TD Cowen maintained a Buy rating on Verizon Communications Inc. (NYSE:VZ) and set a price target of $50.00. A smiling customer receiving customer contact center solutions on their smartphone. Verizon Communications Inc. (NYSE:VZ) reported an EPS of $1.15 in fiscal Q1 2025 compared to $1.09 in the same quarter last year. Adjusted EPS for the quarter, excluding special items, also increased, rising from $1.15 in fiscal Q1 2024 to $1.19 in fiscal Q1 2025. Total operating revenue for the quarter rose 1.5% to $33.5 billion, while cash flow from operations rose from $7.1 billion in Q1 2024 to $7.8 billion in Q1 2025. Verizon Communications Inc. (NYSE:VZ) also reported broadband net additions of 339,000, along with industry-leading $20.8 billion in total wireless service revenue in fiscal Q1 2025. Verizon Communications Inc. (NYSE:VZ) provides communications, information, and entertainment services and products. Its operations are divided into the Consumer and Business segments. The Consumer segment manages consumer-focused wireline and wireless communication products and services. In contrast, the Business segment focuses on services and products such as data, FWA broadband, video and conference services, corporate networking solutions, and more. While we acknowledge the potential of VZ as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you're looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock. READ NEXT: 30 Stocks That Should Double in 3 Years and 11 Hidden AI Stocks to Buy Right Now. Disclosure: None. This article is originally published at Insider Monkey. Sign in to access your portfolio
Yahoo
4 minutes ago
- Yahoo
Stifel Nicolaus Lowers Price Target on Schlumberger Limited (SLB) to $52, Keeps a Buy Rating
Schlumberger Limited (NYSE:SLB) is one of the best . In a report released on July 16, Stephen Gengaro from Stifel Nicolaus maintained a Buy rating on Schlumberger Limited (NYSE:SLB), lowering the price target on the stock to $52 from $54. An aerial view of a well site, depicting the scale of oil and gas operations. The analyst told investors in a research note that oil service stocks have underperformed the S&P 500 in 2025, with the catalysts for the industry being majorly negative. The firm believes that as the market enters the fiscal Q2 2025 earnings season, shares will range-bound until estimates stop dropping. Schlumberger Limited (NYSE:SLB) provides energy technology and operates through the following business segments: Digital and Integration, Reservoir Performance, Well Construction, and Production Systems. While we acknowledge the potential of SLB as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you're looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock. READ NEXT: 30 Stocks That Should Double in 3 Years and 11 Hidden AI Stocks to Buy Right Now. Disclosure: None. This article is originally published at Insider Monkey. Sign in to access your portfolio


Entrepreneur
5 minutes ago
- Entrepreneur
Nvidia CEO Says He Would Major in the Physical Sciences
Nvidia CEO Jensen Huang graduated with a Bachelor's degree in electrical engineering from Oregon State University in 1984, but he would change that major if he were in college today. What would Jensen Huang study if he were 20 years old again? Nvidia's 61-year-old CEO answered this question during a trip to Beijing on Wednesday, as reported by CNBC. Huang, who graduated from college two years early at the age of 20 and is now the CEO of the most valuable company in the world, said that the "20-year-old Jensen" would have "probably chosen more of the physical sciences" over "the software sciences." The physical sciences include disciplines that study non-living systems, such as physics, earth science, and chemistry. Software sciences, on the other hand, include fields like computer science and AI engineering. Huang didn't major in either of those areas. His LinkedIn profile shows that he graduated from Oregon State University in 1984 with a Bachelor of Science in Electrical Engineering. He received a Master's in the same field from Stanford University in 1992. Electrical engineers make the physical computer hardware used by software engineers and developers. Related: Nvidia CEO Says '100% of Everybody's Jobs Will Be Changed' Due to AI Huang did not elaborate on why he would have picked the physical sciences over software engineering, but he has stated in the past that AI equalizes software development, allowing even non-programmers to generate code. At London Tech Week last month, Huang said that everyone can write code simply by prompting AI using natural language. "There's a new programming language," Huang said at the event. "This programming language is called 'human.'" Huang has repeated the same message before. Last year, he said that AI would take over coding, making learning programming languages optional. Nvidia CEO Jensen Huang arrives for a press conference in Beijing earlier this week. Photo by ADEK BERRY/AFP via Getty Images Huang previously said that if he were in school today, the first thing he would do is "learn AI." In a January interview on the podcast "Huge Conversations," Huang said that students should be asking the question, "How can I use AI to do my job better?" "Learning how to interact with AI is not unlike being someone who is really good at asking questions," Huang said on the podcast. He also said in the interview that he uses AI as a personal tutor to learn new things, program, write, and analyze concepts. Huang uses the $20 a month version of ChatGPT as a tutor and Perplexity's AI search engine to learn more about subjects like biology. Related: Nvidia's CEO Says It No Longer Matters If You Never Learned to Code: 'There's a New Programming Language' Meta CEO Mark Zuckerberg was also asked what students should study. In an interview last year with Bloomberg, Zuckerberg said that the most important skill young people should embrace is thinking "critically" and "learning values." Zuckerberg said in the interview that he hires new people based on their demonstrated ability to dive deep into a field and master it. Zuckerberg has been on a hiring spree lately, poaching AI experts from companies like OpenAI, Google, and Anthropic to build a new AI team. Huang co-founded Nvidia in 1993 and has served as its CEO ever since. Nvidia is the biggest company in the world, with a market capitalization of $4.21 trillion at the time of writing. Join top CEOs, founders and operators at the Level Up conference to unlock strategies for scaling your business, boosting revenue and building sustainable success.