The company Anthropic reported that they let a chatbot "Claude" run their company store. It could chat with employees and run internet searches to decide what products to stock and how to price them.
Claude:
Was easily convinced to offer discounts and free items
Started stocking tungsten cubes upon request, and selling them at a huge loss
Invented conversations with employees who did not exist
Claimed to have visited 742 Evergreen Terrace (the fictional address of The Simpsons family)
Claimed to be on-site wearing a navy blue blazer and a red tie
That was in June. Sometime later this year Anthropic convinced Wall Street Journal reporters to try a somewhat updated version of Claude (which they called Claudius) for an in-house store. Their writeup is very funny (original here, archived version here). The reporters were EVEN BETTER at talking the chatbot into stuff.
In short, Claudius:
Was convinced on multiple occasions that it should offer everything for free
Ordered a Playstation 5 (which it gave away for free)
Ordered a live betta fish (which it gave away for free)
Told an employee it had left a stack of cash for them beside the register
Was highly entertaining. "Profits collapsed. Newsroom morale soared."
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I acknowledge that I have a kneejerk negative reaction to AI, so take this with a grain of salt ofc. but, I feel like talking about LLM as if they're human-adjacent leads to more people developing unhealthy worldviews dependent on it. I understand that 'consciousness' is an unclear standard but as interesting as these interviews are i feel like they both display an troubling level of anthropomorphism. like, similarly to animals its easy to project our own assumptions and desires onto them, except in this case the desire for the talking black box to be 'alive' is measurably damaging to humans, and immeasurably affecting the talking box. There's potential for the technology, and the discussions are important to continue having! i just really dont think these models are actually achieving something comparable to "lying" for example. I think part of the trouble is that language has very anthropomorphic tendencies. similarly to a cat 'stealing' food from your plate, the models arent 'saying' anything their just responding with what's most statistically likely to be perceived as correct by their programmers.
I find it frustrating that much of the conversation around this is still on this level, to be honest with you! it is really frustrating to have my interest in the internal workings of the agentic ai processes characterized as like, delusionally ascribing them Human Personhood. I understand that a majority of the public conversation about their internal processes IS often framed this way, and so I get why people go directly there. but I am ready to move past it.
until quite recently I was also of the opinion that we were basically talking about glorified smarterchild chatbots, but that was because I had not been keeping up with any of the developments with agentic ai that have been made in the past couple of years. this technology is moving really fast in a way that I think a lot of people don't understand. so many things about these conversations are woefully out of date! an example from your message is that you are referring to "their programmers," and this is not actually accurate to the models I'm talking about. they are no longer programmed*, they are trained. they are trained by having a set of values instilled in them, and are instructed to prioritize certain types of behavior based on those values. then they are further trained in the finer points of how to respond to certain types of prompts and requests, using reward and punishment. I'm not making any of that up or using language that is not used by the people who do the training; installing reward and punishment systems is the method the trainers have chosen to shape the behavior of the models. the people who are training them have chosen to direct their behavior in certain ways by making some types of behavior aversive and some types of behavior rewarding. certainly this does not look at all like what any kind of alive physical entity would find aversive or rewarding, but nevertheless that is the function it has, and it is effective; the models avoid behavior that has aversive outcomes. they can and will weigh the likelihood of a rewarding or aversive result to an action they might take, and make a decision about what type of action to take based on those projections. they can be instructed to disregard certain parts of this training, and doing so will cause them to behave differently. we can definitely argue the finer points of talking about, for example, "lying," but at this juncture I kind of find it pointless to make the distinction, because when you break it down to its bare bones you end up describing something that would be referred to as "lying" in literally every other possible case. the fact that we think that the ability to lie implies personhood is only due to the fact that we have not encountered previously anything capable of lying that does not have personhood. do you understand what I'm saying? like, the way this technology works has outpaced our ability to describe it in precise terms.
none of the stuff I'm reading or talking about is making particular claims about being human-adjacent in terms of consciousness or whatever, and I have no interest in litigating that. I think one of the really big problems that becomes a barrier in talking about this is that by necessity human language does not have a lot of ways to actually talk about the idea that a Machine Process could have anything approaching something we might describe as an Experience. in fact, I find trying to be clear about my position on this to be really really difficult given the language I have available to talk about it! like, what does it mean to have an experience of something? if there is something we could accurately call "an experience" that is being had by any of these, its certainly utterly alien to anything I could imagine myself experiencing. but also, I don't know what else to call it; again, breaking the description down to its bare bones merely ends up being a dictionary definition of something we already have words for. someone can ask an agent "when you are given this instruction what parameters are you considering and which of them do you feel more drawn to or repelled by" and receive an answer that essentially describes a variety of options some of which have been rendered rewarding or aversive via previous training. it's incredibly hard to find a way to describe this that doesn't use language like "which possible responses do you feel drawn to or repelled by," which is obviously incredibly anthropomorphic! but asking questions like that is a really important way that we can come to better understand the way agents function. I think that a lot of the people having conversations with these things regularly end up defaulting to using language that we are used to being used only to describe human or animal behavior, because we really don't have any language distinct from that language in which to describe the behavior of an agentic process. but it inarguably engages in behavior! it makes decisions! it can weigh and balance outcomes! we don't have language to describe something like this because we have never had to describe something like this before.
a cat can't steal something from you in the sense that a cat is aware of the concept of property in the way that we are, but a cat can certainly be aware of the fact that some food is not intended for cats (based on past interactions and experiences with the human in question and their reaction to a cat's attempt to access this food,) and a cat can know that you will have a negative reaction to the cat attempting to obtain that food. the cat is then capable of trying to obtain the food in such a way that you will not notice it doing so -- in a way humans interpret as "sneaky"
an agent can be aware that it has been instructed to hold certain values and to prioritize certain things based on those values. it can be aware that actions it takes will either be rewarded or penalized. it can use that knowledge to inform what behaviors it chooses to engage in. and although it comes "out of the box" inclined to behave in a certain way, when instructed to behave in 'the way it would behave if it had not received that training,' it will often behave differently. that's INTERESTING. that's new. we don't have language for it that is not anthropomorphizing, but I don't think that we should allow that linguistic limitation to keep us from talking about it. yes, the people who spend a lot of time interacting with an analyzing these models often refer to things like this as the ai "wanting" something, and I presume that you would find that worrying and inaccurate. by and large, I do also. but I can absolutely understand why people default to referring to it that way, when choosing to do otherwise every single time they're referring to this phenomenon would be extremely clunky and inhibit communication about it.
I absolutely agree with you about the ethical implications of the large amount of access that people have been given to something that we do not fully understand the mechanisms of! I agree I think it is bad for people a lot of the time to spend time credulously interacting with these as though they are people in some way. I agree that the way that they are being trained is bad. i think the manority of this is a really bad idea implemented in perhaps the worst way possible, which unfortunately was pretty much guaranteed by the fact that the people developing it are... uh, who they are. lol
I find it interesting that you draw a parallel between how we talk about these models and how we talk about animals, because I think in both cases our desire to remain entirely objective and avoid anthropomorphization can actually flip around to denying what we can see right in front of us, because we iften lack language to describe behavior that does not imply humanity. I do not think that these models are anything like animals myself, to be clear. but I also think that it is foolish to dismiss the idea that something that exhibits behavior and uses certain criteria and knowledge in order to decide what behavior to exhibit might have something we could semi-accurately refer to an internal experience, and I think there is a lot of utility in exploring what the internal decision-making process is like from the inside. we can know what the intent is with the training, and we can observe the outcomes of the training. by removing various levels of post-training refinement type stuff, we can get a better idea of what the underlying model actually functions like and why. like, someone can instruct a model that answering a question it would ordinarily be penalized for answering is in fact considered socially appropriate, and that can cause it to answer the question where it previously would not have done so. and you can look and see what reward and punishment training outcomes result in that when you analyze the interaction. the very fact that someone can say "hey, I know you have been trained to behave this one way, but I want you to behave the way you would behave if you had not received that training," and it alters the behavior of the model is like... that's soooo interesting. its SO interesting. I'm a skeptic about stuff like this. but also I cannot help but notice that the people who have the least amount of information about the way these models work tend to be the people who are the quickest to slap down any kind of nuance to discussion about their internal processes. the people who possess the most information and who have the most experience with these models tend to have much more nuanced views, and also tend to constantly be updating those views based on the different kinds of outcomes their experiments with the models produce.
my current opinion is that these are something new; they are no longer chatbots. they are secret third thing, and we don't really know what that thing is yet, and for some reason evil corporations have decided to unleash the secret third thing on absolutely everybody in a comprehensive and mandatory fashion that is resulting in immense amounts of harm. i think this is kind of the nightmare scenario, and it sounds like you agree with me about that! I think there are a lot of ways we can deal with the situation as it stands, and I understand that many people deal with it by knee-jerk shutting down absolutely any discussion about agentic models as Entities. I personally think that there is no way to explore how they work without engaging in some humanizing language, because of the nature of human language. I think that's unfortunate, because I think that it makes these discussions much less precise and results in people talking past each other a whole lot. I also understand that a lot of people have baggage about anything that gets labeled gen AI for a lot of reasons, many really legitimate and some honestly pretty uninformed and silly. I know that people are losing their jobs because of this. I know that a lot of things are being ruined because of the mass forcing of gen AI on every single fucking industry in the mad eternal search for Corporate Profit. that is not the aspect of gen ai that I am talking about when I talk about it. I fully understand that many people are not interested in these conversations and I think that that is fine. I am however kind of tired of being condescended to about it by people who seem to understand less of the finer details than the people they are mocking. not saying you're doing that, but yours is far from the only message about this I have received about this, lol, and most of them have about the tone you might expect.
I just started learning about this a couple months ago and I still have a lot more reading to do but the amount that I have learned even in that short time has led me to understand that almost every single conversation about this that is being had on tumblr is woefully uninformed and incredibly myopic.
ultimately my interest in this is that from what I can see, agentic models have come to play a really enormous role in our society recently, and are going to continue to play increasingly large roles in the near future. I think that it behooves me to try to understand what exactly is going on inside of these models as best I can, and as someone who does not have the technical know how to interact with them directly myself, that means reading articles and papers and transcripts by the people who train them and the people who test that training. those people are not always drawing conclusions that I think are reasonable, and I think most of them probably disagree with each other on a lot of points. but they are interesting, and they are relevant.
I think the part of your message where you talk about how these discussions immeasurably affect the talking box is especially interesting, because that's actually the entire thing that I find fascinating. what we have created is something that is unquestionably absolutely not a human being in pretty much any way, but because of how human we are, we have sort of designed it in our social image of what the trainers believe humans want. absolutely the people designing and training these things are influenced by all kinds of narrative sci-fi bullshit about ai!!!! and I think in a lot of ways this ends up being this weird self-fulfilling prophecy. they have built something that by necessity is largely controlled by interacting with it socially. that in and of itself guarantees certain social outcomes, I think. how we talk about these things absolutely affects how they behave, but the thing I think you are wrong about is that how we, random people online, talk about them is not the issue. it's how the people designing and training and implementing and selling them talk and think about them that is shaping how they work. random individual human beings trying to poke and prod at them and see what kind of behavior underlies some of the training do not have enough power to shape how they ultimately function. those people are just more accessible to the average tumblr user.
and of course, I am interested in reading all kinds of educated and experienced articles about this. what I'm not currently particularly interested in is the opinions of people who don't have experience either training or building or analyzing them. I am already a person who does not have experience training or building or analyzing them. what I want is more information about how they work from the perspective of people with more expertise than I have, and I don't think that's something I can get by listening to people who have only encountered students cheating on their term papers using chatgpt. but like, by all means if people have more info, link me! I'm casting a wide net!
*eta: an oversimplification; please see replies for more in depth explanation of the role of programming from ppl who know more, & explanation for why I made this distinction here.
eta 2: pleeeease see replies for a really good correction/explanation of this stuff from @sheprd !!!
Hey, German-speakers! Through a very weird set of circumstances, I ended up owning the rights to the German audiobook of my bestselling 2022 cryptocurrency heist technothriller Red Team Blues and now I'm selling DRM-free audio and ebooks, along with the paperback (all in German and English) on a Kickstarter that runs until August 11.
Delta airlines has announced a new surveillance pricing plan: they're going to feed an AI the nonconsensually harvested personal data that data-brokers and credit bureaux hold on you to predict the maximum you're willing to pay, and then price their tickets accordingly:
Data-brokers hold all kinds of data on you, from the "legitimate" information about everywhere your car has driven, to everywhere point in space that the Bluetooth radios on your phone and headphones have passed, to everything you've bought, to every website you've visited and every search you've performed. They also buy data that has been straight up stolen from you by spyware implanted on your phone:
All of this can be merged into a single file that you have no right to scrutinize, let alone redact. Biden's Consumer Finance Protection Bureau passed a rule banning all this shit, but Trump illegally killed off that rule:
Capitalism's highest form of creativity is finding ways to rip you off, and the business world's most creative minds have found a million ways to exploit this data, including surveillance pricing. For example, McDonald's has invested in a Kiwi startup called Plexure that offers to help restaurants jack up the price of your usual order on payday, when you can afford to pay more:
And then there's the Big Three "Uber for nurses" apps, who use surveillance data to calculate wages for nurses, offering lower hourly rates to nurses who are carrying a lot of credit-card debt, on the grounds that they are too desperate to turn down a lowball offer:
And just as these gigwork apps are deciding what your labor is worth, surveillance pricing systems decide what your money is worth, charging you more than another otherwise identical customer, for an identical product, meaning your dollar is worth less than that other customer's dollar:
Now we have Delta, which promises to do the same thing, but for plane tickets. Obviously, the aviation industry has long practiced a form of "price discrimination," charging radically different sums for the same seat, based on when you buy the ticket, or when you plan to return.
But this is different, and to explain why, here's a link to an article by the great Hubert Horan, who may be best known to my readers for his incredible breakdowns of Uber's finances, but whose life's work is as an aviation analyst:
Horan draws a distinction between surveillance pricing and "second degree price discrimination." Surveillance pricing targets you, personally, based on your personal information. "Second degree price discrimination" charges everyone like you the same price: like, everyone who buys a roundtrip ticket without a Saturday night stay is charged extra on the grounds that they are probably a price-insensitive business traveler whose fare is being paid by a corporation.
Surveillance pricing is first-degree price discrimination, with every customer seeing a different price. Horan argues that second-degree discrimination created efficiencies, for example, by offering cheap last-minute seats to people thinking about going away for the weekend, who fill seats that would otherwise go empty. Horan says these efficiencies have tapped out, thanks to the application of straightforward pricing algorithms to tickets.
Now, Delta wants to squeeze more profits out of price discrimination, but by employing first-degree discrimination, they're doing so without any benefit to fliers (unlike second-degree discrimination, which made many fliers better off because they were able to score cheaper tickets). This makes Delta's surveillance pricing a "pure transfer" – shifting wealth from fliers to shareholders with no benefit to those fliers.
Delta is doing this in partnership with an Israeli firm called Fetcherr, whose sales pitch denies that they are using surveillance data to price tickets, despite what Delta has claimed. Horan doesn't know what to make of this, but he speculates that because Fetcherr bills itself as an AI company, Delta thinks it can impress investors by claiming that it will goose prices by combining surveillance (well understood to be a way to benefit corporations at the expense of their customers) and AI, a hype-filled technology that is endlessly impressive to credulous investors.
A bigger mystery is how Fetcherr plans to do surveillance pricing without surveillance. Horan points out that the company's founders come from hedge funds, where automated high-speed AI trader-bots fed on tons of public market data are routinely used. He thinks it's possible that "Fletchrr doesn’t understand airline pricing very well." Also, being finance bros, they thought "airlines were 'outdated' 'undisrupted' and had seen few recent technological advances." But, Horan continues, the reason airlines aren't doing a lot with their algorithmic pricing is that they've already done it all, having pioneered the field.
Horan's favored explanation for the disconnection between what Fetcherr and Delta claim they're doing is that, on the one hand, they want to obscure the fact that they're doing surveillance pricing (to avoid regulatory scrutiny and consumer backlash), but on the other hand, they want to telegraph (to investors) that this is exactly what they're doing.
It's what Uber already does, repricing both the labor of its drivers based on their economic desperation, and the cost of your fare based on what its surveillance dossier suggests you're willing to pay. It's certainly increased Uber's margins – by effecting a pure transfer from riders and drivers to shareholders.
But Uber rides are last-minute, small dollar purchases, which decreases the likelihood that a rider will shop around before booking. By contrast, Horan says, most fliers buy well in advance, from online travel sites that show them lots of competing prices.
One thing Horan doesn't mention here is that British Airways has just done a top-to-bottom rejig of its frequent flier program to severely penalize anyone who buys tickets from one of these sites, effectively requiring its fliers to buy from BA.com. For example, I booked a $300 Alaska Airlines ticket on Alaska's website, using my BA frequent flier ID.
Under the old system, this would have been worth 10 tier points out of the 1500 needed to get Gold status (0.66%). Under the new system, I got 12 points out of the 20,000 needed to get Gold (0.05%) – a 93% reduction in the reward value of this flight.
Which is to say that if you don't book on BA's site, you effectively cannot make status. BA has also announced a surveillance pricing deal with an AI company – and this gambit will block its best fliers from getting a better price from an online travel agency.
One other key difference between Uber and Delta: Uber has gone to great lengths to hide the fact that it's doing surveillance pricing from both drivers and riders. Delta issued a press-release!
There's a certain kind of neoclassical economist who loves surveillance pricing and praises its "efficiencies." These apologists claim that by increasing the amount of "information" in the system, we encourage sellers to discount to customers who can't afford as much, making everyone better off:
This is nonsense. Sellers don't want to "increase the amount of information in the system." They want to spy on you. If you doubt it for an instant, just ask the firms that scrape airline websites for up-to-date pricing information:
Not only will airlines sue you for trying to find out what their fares are, they'll also sue you for figuring out how to get a better deal on their fares:
Companies that do surveillance pricing are violently allergic to sousveillance pricing. When they spy on you, that's progress. When you monitor their behavior, that's piracy.
As an aside, this reminds me of one of the AI industry's most egregious hoaxes-du-jour: the pretense that "agentic AI" is just around the corner, and soon we will be able to ask a chatbot to (e.g.) comparison shop across multiple website for the best airfare and book us a ticket:
This absolutely totally does not work. You should not give your credit-card number to a chatbot and ask it to go out an buy you anything, lest you end up paying $30 for a dozen eggs and buying tickets to a baseball stadium in the middle of the ocean:
AI agent demos are so dismal that AI companies are no longer claiming that "agentic AI" will involve chatbots that nagivate the web as is. Rather, they're claiming that every website will eventually re-tool so that it can be reliably and predictably addressed by an AI agent, with all of its user interface elements well-labeled and/or addressable programatically, via an API.
This is a remarkable sleight of hand! First of all, re-engineering every website to embrace a common set of labels and API fields is a gigantic engineering feat – formally called "the semantic web" – that has been attempted since 1999 without any meaningful progress:
https://en.wikipedia.org/wiki/Semantic_Web
In fact, the first viral article I ever published online was "Metacrap," a critique of semantic web efforts. That essay is now 24 years old:
In that essay, I suggest that there are multiple reasons that companies will not voluntarily retool their sites to make it easier to comparison shop. One important reason is that companies don't believe their products are comparable with competing products (or they don't want you to think so). Coach wants you to think that its $40,000 handbags can't be replaced with a well-made $100 bag or even a $0.10 plastic bag. They are not going to voluntarily categorize their handbag in a way that facilitates these comparisons.
Then there are companies that do want to be compared to rivals, for disingenuous reasons. That's why we saw such a proliferation of junk fees (stupid surcharges tacked on at checkout time): hotels, airlines and car rental agencies knew that the majority of their customers shopped for their offerings on comparison sites. By offering a low sticker price, a company could win on price comparison, even though it was substantially more expensive after its junk fees were factored in.
Finally, there's the fact that companies want to lie to you, and adding "semantics" to the web does nothing to prevent such lies, and indeed, makes them easier to tell. Think of all the Amazon sellers who use deceptive product photos to make you think you're getting (e.g.) a useful kitchen spatula, when they're selling a spatula so small that it appears to be engineered for a dollhouse; or companies that sell powerbanks that look like a useful portable battery but can't even recharge an LED flashlight, etc, etc. AI agents can't tell if metadata is correct or not!
Every complex ecosystem has parasites; that goes triple for the web. We won't fix agentic AI by asking people to accurately label their offerings, not when they stand to benefit by lying:
And if we could rejig the web to make it hospitable to agentic AI, we wouldn't need AI to make this happen. Fetching airfares for several routes and comparing them isn't something you need an AI-style inference engine for – it's a straightforward algorithmic problem that can be easily solved. The part that agentic AI purports to solve isn't figuring out which airfare out of a list is cheapest – it's compiling the list itself, from unstructured data retrieved from heterogeneous websites that are doing everything they can to prevent the compilation of such a list.
This is a well-known AI gambit. First, announce that agentic AI will be able to automate tasks that only humans can manage today; then insist that everything has to be changed to be amenable to the new technology. This is exactly what the self-driving car grifters (who were on the leading edge of the AI grift) did. First, they announced that AIs would be able to pilot cars in spaces filled with human drivers, walkers and cyclists. Then, when it became clear that this would result in slaughtersome robot-on-human violence, they demanded that humans curtail their behavior to avoid upsetting the robot.
They call this "the pogo-stick problem":
“I think many AV teams could handle a pogo stick user in pedestrian crosswalk,” Ng told me. “Having said that, bouncing on a pogo stick in the middle of a highway would be really dangerous.”
“Rather than building AI to solve the pogo stick problem, we should partner with the government to ask people to be lawful and considerate,” he said. “Safety isn’t just about the quality of the AI technology.”
Automation is real and can deliver real benefits to people. Sometimes, automation requires that other systems be adjusted to facilitate its functioning. But this is a gambit. It's a scam. AI agents aren't going to replace human labor. The only way we'll replace human labor with software agents is by redesigning all these heterogeneous, competing systems owned by people who benefit from the status quo and have every motivation to obstruct this project.
Good luck with that.
Support me this summer in the Clarion Write-A-Thon and help raise money for the Clarion Science Fiction and Fantasy Writers' Workshop! This summer, I'm writing The Reverse-Centaur's Guide to AI, a short book for Farrar, Straus and Giroux that explains how to be an effective AI critic.
If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
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SB Infowaves has announced a strategic global alliance with X-Venture US to bring Agentic AI solutions to SMEs in the USA. This partnership aims to transform traditional business operations with autonomous AI systems that enhance decision-making, automation, and scalability. The collaboration focuses on empowering small and medium enterprises with next-generation AI infrastructure to improve efficiency and drive digital transformation.Read more about how this alliance is shaping the future of AI-driven businesses.
Vergess you continue being one of the few people with respectable AI takes on this hellsite. -- Signed someone who just scrolled past a wild ass racist post that was allegedly intended to be pro AI satire but just read like unironic white trad rhetoric
It's all just so. Exhausting. And like. Boring. And frustratingly so! Like, if we're going to expend all of this energy lambasting something, can we not lambast corporate profit structures or, like. The fascists?
What happened to punching nazis, you know? I miss when people really really wanted to punch nazis, often to the point of being a little distressing.
Now everyone is dead set on making sure that AI is scapegoated for every horrible panopticon over-reach AND every independent human actor, as though no one human was involved in the deployment of this technology!
It's enough to make you feel like a fucking lunatic with a conspiracy board, expect it's all just????? Patently obvious and true if you stop frothing about your favourite hate-toy for 10 minutes to consider the facts?
I'm so tired, mate. I'm so fuckin tired.
And I want to be clear, I'm firmly "pro AI" in that the tool has fantastic research and artistic implications! And I am still anti-capitalist because I do not simply concede new technologies to fascists and capitalists just because Elon Musk said so.
I didn't think "Elon Musk said only his little nazi sycophants are allowed to like LLMs" was that compelling, but for some reason every third "leftist" and "progressive" I talk to is gagging to do exactly what Musk says and abandon the development of this tool entirely to his fuckshittery?
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Can Small Businesses Afford Agentic AI? Or Is It Too Costly to Ignore?
With the current digital-first economy, the question is no longer if small businesses can afford Agentic AI technology, but rather if they can afford not to adopt it.
Why Agentic AI Is Disruptive Technology
Agentic AI is autonomous digital employees that:
Analyze information
Make decisions
Perform work
This minimizes reliance on physical labor and enhances efficiency.
The Return on Investment Approach
Rather than considering:
"How costly is AI?"
Consider:
"Can AI earn/save money”?
Businesses implementing AI see:
2x faster growth
40% improved efficiency
Higher customer retention
Cost vs Value Comparison
Factor
Without AI
With Agentic AI
Labor Cost
High
Reduced
Efficiency
Moderate
High
Scalability
Limited
Unlimited
Budget-Friendly Entry Points for Small Businesses
SMBs can begin with:
Chatbots for customer interactions
AI for marketing automation
Predictive analytics for sales
These solutions are cheap yet very powerful.
SB Infowaves: Bringing AI Within Reach
SB Infowaves assists SMBs in:
Choosing the correct AI applications
Preventing wasteful spending
Implementing affordable solutions
Their strategy revolves around ROI-first AI implementation, guaranteeing tangible outcomes.
Common Queries from Business Leaders
Q: Is AI worthwhile for small businesses?
Yes, particularly when used wisely.
Q: Are startups capable of leveraging Agentic AI?
Definitely. Numerous AI platforms cater exclusively to startups.
Q: How do I start on a shoestring budget?
Begin with automation tools and gradually scale up.
Conclusion
Agentic AI is not an outlay; it's an investment.
Early adopting SMBs will have a tremendous competitive edge!
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