AI ‘Consulting’ Services Can Help Smaller Businesses, but Risks Persist

Consultancy firms can be very useful for growing businesses, giving new companies guidance or financial or management advice when needed, backed by experience and expertise. But for smaller enterprises with narrow margins, the cost of hiring top-rank consulting firms can be financially out of reach. Enter AI, according to a new report on Business Insider. In much the same way that generative AI tools promise to add, say, coding expertise to a small team or free up workers from mundane tasks to engage in more productive work, AI-powered “consultant” apps are emerging from a suite of Silicon Valley startups, with the goal of helping small firms carry out market research, analyze data, or smooth and optimize their business operations. Business Insider quotes Thomson Nguyen, co-founder and managing partner of Wyoming-based venture capital outfit Saga, on the phenomenon. These new AI consultancy players won’t be challenging big consulting firms any time soon, he thinks, simply because if you’re a “Fortune 500 company building AI infrastructure for your call center, you’ll still hire the Big Four,” because you’ll have the budget set aside and experience in working with third-party consultancies. So the real target for these startups is smaller companies, making under $100 million a year, which are too small to hire a McKinsey or Deloitte. Business Insider notes that AI apps like PromptQL, from Bangalore-based AI unicorn Hasura, are directly set up to tackle typical consultant roles—including analyzing a company’s internal data, and continually adapting over time. PromptQL even has a team of engineers that’ll help craft an AI analyst agent specifically to meet the needs of a client company. Hasura co-founder and CEO Tanmai Gopal admitted to Business Insider that it’s “not as good as a McKinsey consultant,” but it has the benefits of being “instant.” That’s the very opposite of the sometimes protracted process during which a consultant learns about their client company before tackling an analysis, since an AI can just be switched on and immediately wrestle with data. Among the top tasks being assigned to AI consultancy startups are starting and managing call centers and customer service automation, integrating software and AI into the client company’s operations, and building management and operational AI systems. There are even AI tools targeting executive coaching. This may not be a surprise, considering that big tech names like Salesforce are already selling their own agent-based AI services aimed at automating the sales process and call center operations. AI startups offering similar options and targeting smaller companies as clients is natural. Gopal told Business Insider that, for now, these AI consultancy tools aren’t really replacing human workers—echoing many an AI evangelist’s arguments about the role of AI in the workplace. Human workers have more diverse skills, and for the moment such services depend as much on the “network” of colleagues that a human worker can access as on their advice. What’s the takeaway for your company? If you find yourself struggling with an expertise gap, you may find that there’s an AI-powered consulting tool out there that will fit your needs. But as with most AI tools, perhaps the thing to remember is that (just as with human consultants, though perhaps less obviously) AIs are not infallible. AI systems regularly make mistakes, and can hallucinate analysis and advice that they then pass off just as if it was real advice. You’ll have seen this by now, perhaps when you asked an AI to write a snippet of code for you. The AI may insist the code works, but when you say “No, it doesn’t,” the AI may say “Oh! You’re right!” and offer a fix. Whenever you’re using AI it’s best to run the results past a human worker before making a critical decision based on an AI consultant’s analysis. BY KIT EATON @KITEATON

Far From Silicon Valley, This Founder’s Data Center Business Is Building the Future of AI

There’s a common refrain among business strategists that it’s better to be a pickaxe salesman than a gold prospector—or, in other words, that the best way to capitalize on a gold rush is to sell tools to the people hoping to strike it rich, rather than trying to hit paydirt yourself. With artificial intelligence currently enjoying a boom of its own—one that some big names have even called a bubble—plenty of companies are stepping in to sell the AI equivalent of pickaxes, such as backend infrastructure and computational power. That includes big-name ventures such as CoreWeave, the AI cloud company that IPO’d earlier this year and counts Microsoft, IBM and OpenAI among its clientele. CoreWeave claimed the No. 45 spot on this year’s Inc. 5000 list of the fastest-growing private companies in America, and is one of the AI boom’s biggest winners so far. But beating it out on that same list was another AI infrastructure company, the Chicago-based Introl, which came in at No. 14 on the list just a few years after its founding. Introl founder and CEO Ryan Puckett launched the company in 2021 while between jobs and looking to work as a freelance project manager. Introl helps set up GPUs, or graphics processing units: the computer chips that train and run modern AI models. A former low-voltage cable technician, Puckett has since built the company up to impressive scale: it’s grown annual revenue nearly 10,000 percent over the last three years, and Puckett says domestic revenue was about $38 million last year. All of that growth is bootstrapped, the success of which the CEO attributes to “managing cashflow effectively and efficiently”—as well as, at least initially, “a lot of credit card debt.” And though Introl was born in Dallas, Puckett moved it to Chicago a few years in; he’d lived in the Windy City during his early 20s, and wanted to go back. “There’s not a better city in the country,” he says of Chicago. “There was no other thought in my mind to build it anywhere else.” Blake Crosley, Introl’s CTO, says the company has deployed “up to 100,000 GPU units in a data center.” Each one needs multiple connections, he adds, requiring lots and lots of fiber optic cable; the company says it has run more than 40,000 miles of the stuff in all. “We don’t actually own or operate the data centers,” Crosley explains. “We basically help design, like, what does it look like to actually get that set up in the space? Once the racks are in place, how are we going to actually connect everything together?” This work, he adds, is known as “rack and stack.” Installation is followed by testing and quality control. NDAs limit Introl’s ability to disclose specific client names, but the company says it has around 45 to 50 full-time employees, plus over 1,000 subcontractors. The startup deploys that workforce to data centers around the country and the planet. Those data centers are so big, Puckett says, that people get around them in golf carts and measure their footprints in terms of how many Costcos could fit inside. Speed to market is the CEO’s biggest challenge, he tells Inc. Companies will sometimes give Introl barely a week’s notice to get people on-site to a data center, he says, and it can sometimes be hard to find enough hotel space to house all those staffers—who will sometimes number in the hundreds for a job—especially in the small towns where many data centers go up. “In a lot of cases, because they are trying to get things online so quickly…certain specific sections of [the data centers] are being built while you’re in a different part,” Puckett says. “It’s a constant flow of trucks coming in, dropping off pallets of cables.” AI is big business right now, but if the fervor starts to die down, demand for the underlying hardware could follow suit too. “I’m not 100 percent sure what our pivot would be [if], say, GPU deployments just kind of fell off the face of the earth,” Puckett says, although Introl’s focus could shift toward maintenance. Right now, he estimates, 70 percent of the company’s work surrounds new installations, while the other 30 percent has to do with maintaining pre-existing sites. For now, though, the company is feeling good about where things are headed. “Obviously there’s a lot of talk about [an] AI bubble and stuff like that,” says Crosley, the CTO. “The players are huge, and the money that’s flowing is even bigger. But from a user perspective, on the side of utilizing AI, I can only see things expanding faster in the total adoption and usage.” BY BRIAN CONTRERAS @_B_CONTRERAS_

Here’s How LinkedIn Co-Founder Reid Hoffman Says AI Needs to Be Regulated

Regulation can be good for technology, so long as it’s done thoughtfully, according to LinkedIn co-founder, investor, and AI-enthusiast Reid Hoffman. Speaking on the heels of a pitch event in San Francisco called Entrepreneurs First Demo Day, he compared AI regulation to seatbelts in vehicles. “Seatbelts are a good thing, relative to the fact that regulatory stuff can have a positive impact on society, technology evolution. Now doing it smart in the right way is important,” he tells Inc. “You don’t try to solve everything before you get on the road. You get on the road and then solve it as you go,” he adds. His voice joins a chorus of others from big names in tech speaking up about how much—or in the case of legendary investor Marc Andreessen and companies like Meta—how little regulation they support. Hoffman sits on the board of Entrepreneurs First, an international talent investment firm that hosts incubator-style programs and related annual pitch competitions. Those events are called Demo Days, and the most recent took place in San Francisco on Wednesday. Hoffman joined EF’s board after leading a significant round of investment in the company in 2017 through his capacity at venture capital firm Greylock Partners. Hoffman was not on the ground at Demo Day this year, but another big name in tech was: Anthropic co-founder Jack Clark was the keynote speaker in conversation with Entrepreneurs First CEO Alice Bentinck. Just a few days prior, Clark had made waves for commentary he gave at The Curve conference in Berkeley, California, and later published in essay form in his newsletter. He compared AI to a “mysterious creature” of humanity’s own creation. He said he was optimistic about its potential as well as appropriately afraid of it, especially if AI’s goals are not absolutely aligned with humanity’s. And finally, he ended by emphasizing the need for conversations with a broad swathe of society to help craft a “policy solution.” “There will surely be some crisis,” Clark notes in his blog. “We must be ready to meet that moment both with policy ideas, and with a pre-existing transparency regime which has been built by listening and responding to people.” In response to the post, U.S. AI and crypto czar David Sacks accused Anthropic of fearmongering. Hoffman’s take, which he wrote about in his recent book, is by no means anti-regulation, but does differ somewhat from Clark’s. “In the book that I published in January, Superagency, part of what I was arguing for within AI is iterative deployment and development,” he tells Inc. “We do the regulatory thing, but we do it in response to what we can actually see versus imagination of what [could] happen,” he adds. AI has never been more topical, especially among aspiring entrepreneurs. This week at Demo Day in San Francisco, founders from 20 different startups pitched more than 200 tech investors, among them big name firms like a16z, Khosla Ventures, Paladin Capital, Insight Partners and Engine Ventures, in hopes of landing as much as $7 million in seed funding. It represented the culmination of some six months of work the founders had put in during Entrepreneurs First’s incubator-style program. On the lips of most of those entrepreneurs was AI. “The majority of the companies that were pitching yesterday—85 to 90 percent—are all using AI in some way. Some of them are building novel AI models, others are creating wrappers or scaffolding around existing AI models,” says Bentinck. “If you look at what early stage investors want to put capital behind, they see this enormous opportunity in the new AI economy.” Originally founded in London, Entrepreneurs First started off as a nonprofit in 2011 before becoming the investment vehicle it is today, starting in 2015. The company expanded overseas to offer programming in San Francisco at the start of 2024, and continues to run cohorts across Europe, India and the U.S. Entrepreneurs First functions something like an incubator, although Bentinck says EF thinks of itself more as a “talent investing studio.” It searches out individuals, usually with technical backgrounds, who also possess certain qualities related to pacing, productivity, determination, and even aggression, Bentinck says—qualities that alert EF that these individuals may outperform their peers. EF then guides them through the process of building a startup including helping them ideate if they don’t already have an idea and introducing them to potential co-founders. “We find exceptional individuals, pre-team, pre-idea, pre-company. Really all that we’re looking for is their entrepreneurial potential and then we run them through a process that helps them build a startup from scratch,” Bentinck says. The group that pitched this week included the top tier companies from EF’s European and U.S. programs. Each of these teams had been selected by EF and received $250,000 in pre-seed investment in exchange for 8 percent equity. “That’s the culmination of EF and we then send them off into the wild to build enormous companies,” Bentinck says. BY CHLOE AIELLO @CHLOBO_ILO

How AI Can Make You a Better Negotiator: A Step-by-Step Guide

Earlier this year, Jennifer Barnes received an email from a client in financial distress, asking to renegotiate their contract. As the founder and CEO of Optima Office, an outsourced HR and business services company based in San Diego, this was not the first time she’d received a message like this. She’s been in business since 2018, growing her 100‑employee company to around $18 million in revenue and earning a place on the Inc. 5000. There isn’t much she hasn’t seen. From experience, Barnes knew negotiating was going to burn the better part of an hour. First, she’d have to read the whole exchange. Then she’d think about how to respond. After that, she’d have to spend a lot of time writing and editing the response. She’d have to be diplomatic and keep her own emotions in check, she says: “Clients can be really unreasonable when they’re very low on funds.” This time, however, instead of working through it on her own, Barnes popped the email into her paid version of the AI chatbot Claude and asked it for a three‑point summary of the client’s demands. She then uploaded a brief synopsis of her perspective on the situation, did a light edit and hit send. Total time to craft the message that solved the problem? Five minutes. Negotiating is much of the work of growing a company. Whether it’s with clients, suppliers, investors, joint venture partners, contractors, or employees, as an entrepreneur it can feel like you’re constantly either preparing, actually doing, or managing the results of a negotiation. All of that is intellectually and emotionally demanding, says Emily DeJeu, professor at the Tepper Business School at Carnegie Mellon University, who teaches classes on negotiation. “Even in our textual exchanges, negotiation is happening as much with our guts as with our brains.” But with the advent of AI, using your own brain unassisted has become a bit passé. If sensitive, time‑consuming tasks like negotiating can be even partially off‑loaded without inadvertently blowing up your company, well, that’s pretty compelling. On the other hand, a recent MIT report found that 95 percent of companies are getting literally zero return on their generative AI investment. But it doesn’t have to be that way. By deploying today’s AI tools to prepare for negotiation—with a keen understanding of their current limits—you can leverage them to your advantage right now. In this Premium article you will learn: A step-by-step guide for incorporating AI into the negotiation process Best practices for combining human intuition with artificial intelligence How many hours a week you can expect to save by using AI When an hour takes five minutes For growing companies, there’s a wide array of AI tools from business-function-specific programs like Salesforce’s Einstein to generally available large language models like ChatGPT or Perplexity. All of these AI tools can analyze data and generate cogent text or other forms of output. Between the time savings and the added bonus of strictly controlling her tone, which might have had a sarcastic edge, Barnes says she quickly found herself relying on Claude for her frequent negotiation tasks: to research, prepare, and learn from prior wins. “It saves me about eight hours a week,” she says. “It’s like having another executive on the team.” Of course, that extra executive is sometimes fallible. “It makes mistakes. Don’t get me wrong,” she says. Generative AI systems are known to hallucinate, or produce inaccurate and even fabricated results. But AI seems just as confident when it’s wrong as when it’s right. That’s why Barnes says she would “absolutely not” allow an AI to send a message on her behalf without reviewing it first. When I asked Claude for a comment it agreed: “People getting real value are using me as a tool they control, not as a replacement for judgment. The moment anyone treats me as a peer negotiator rather than a research assistant, things get questionable.” Machine processing power versus human nuance Even if AI never made a mistake, there are serious questions about how well machines can accomplish the extremely human task of negotiating a complicated deal, says DeJeu, who is also hosting a conference on how businesses can use generative AI later this year. Artificial intelligence lacks the ability to read human emotion, which is often cited by the negotiators she’s trained as an advantage. DeJeu, however, disagrees. “Emotion has a distinct, powerful role to play in persuasion,” she argues. “Negotiation is one of the most human‑touch-necessary communication scenarios. It’s nothing but nuance.” Today’s tools, she says, aren’t capable of the key basic task of accurately reading a room. DeJeu acknowledges that not every negotiation is that deep. Not every supplier contract needs an analysis of subtle body language. And she certainly sees many benefits of using an AI tool to research and synthesize information ahead of a negotiation. “It can make you a little more nimble,” she says. DeJeu specifically finds using voice‑enabled AI for rehearsing negotiations to be beneficial. She suggests preparing 10 minutes for every 10 seconds of talking time in a negotiation. It’s hard to imagine a human critique partner enduring that without diminishing returns, but AI is tireless. Agents of the Future Of course, AI tools are rapidly evolving. Building on LLMs are the more eye‑catching AI‑powered agents—also known as agentic AI—which are capable of self‑direction. “AI agents act with autonomy and authority to find and negotiate deals with suppliers at scale,” explains Kaspar Korjus, CEO of Pactum AI. If technology continues its progress, AI agents will eventually handle every step of negotiation, from first contact to final contract and delivery. While going totally hands‑off is not an available option for most small to midsize companies today, corporate giants have been working on this for a while. For example, way back in 2021, Walmart worked with Pactum AI to create a pilot to handle certain supplier negotiations with AI chatbots. That led to a wider deployment in 2022—which you may recall is the year when ChatGPT first launched its public version. Now that ChatGPT has more than warmed up the general audience—the latest estimates for this one platform alone are 700 million users worldwide—agentic AI will only become more common. Nearly three‑quarters (72 percent) of chief procurement officers surveyed by Gartner say that AI tools like these are their top technology priority over the next five years. However, the next five years are not the next five minutes. “It’s still early days—we really don’t see any process that is fully agentic,” says Sesh Iyer, North America chair of BCG X, the tech build-and-design unit of Boston Consulting Group. For one thing, agentic AIs are still flummoxed by unexpected things, and that can make them take strange, if not brazen, shortcuts. For example, in a Carnegie Mellon study of a simulated company, researchers found that when an AI agent couldn’t find a particular person it needed to contact to complete a task, it just renamed another user. Overall, the top‑performing AI agent successfully completed only 24 percent of its tasks. But make no mistake—the tech is evolving fast, says Iyer: “We always overestimate what new technology will do in the short term and underestimate what it will do in the long term.” A practical playbook To avoid these problems of estimation in either direction, Iyer suggests starting with what you have right now. It’s easy enough to incorporate AI into negotiation prep with the tech your business probably already uses. Test it out with background research, brainstorming arguments and counterarguments, and use the voice function for rehearsal. But even at the most basic level of AI usage, it’s best to check in with your legal and IT security teams, since there are heavy privacy implications for both. When you’re using LLMs to their fullest for negotiation, you’re “allowing an incredible amount of access to information, including emails and alendars,” says Cameron Powell, co-founder of DeepLaw, a legal consultancy that uses AI tools for negotiation on behalf of its clients. Sharing this information can raise questions about confidentiality, liability, and intellectual property. When AI has proved its mettle and security to your satisfaction, the next step is using it to conduct deep analysis of your current contracts, sales, and negotiation processes. This could mean using AI to review your less-used suppliers that might be costing you more than they’re worth. You could also use AI to create side-by-side comparisons of your competitors or to provide a deep analysis of your current contracts to see what advantages you may be leaving on the table. AI can help manage tasks that are too time‑consuming or unwieldy to otherwise manage closely. Eventually, you can move to testing semi‑autonomous AI agents on repetitive or less nuanced negotiating tasks. Wherever you are in the process of integrating this new tool, Iyer suggests moving deliberately, and with a sharp eye toward integrating AI into your and your employees’ workflows. That MIT report that found little return on generative AI investment attributed much of the problem to enthusiastic focus on the gee-whiz technology itself, at the expense of truly considering how to make the best use of it today. “Focus on things that truly matter to your business,” urges Iyer. “Don’t try to do a thousand things at once.” BY ALISON J. STEIN