5 Side Hustles You Can Start Today With AI

Artificial intelligence can turn into a significant income source for people who choose a smart AI side hustle. AI may still have a long way to go with tasks that involve rich context and institutional knowledge, but with others, especially when there are reliable patterns, it can increase productivity and boost results. Fortunately for you, there are scores of companies looking to take advantage of those benefits. The best AI-driven side hustles use the technology as a great equalizer to compete against established enterprises. Small business owners, particularly of established businesses, often use AI in a limited fashion, if at all, says Peter Hansen, director of research and policy analysis with the National Federation of Independent Business (NFIB). Those founders value and emphasize the human connection to their customers. But even if they don’t use it, they recognize AI can help in other areas. Many of those owners don’t have the time to learn the ins and outs of various AI systems. And even companies that are using AI are often not taking full advantage of it. That creates an opening for side hustles that center around AI. “More than three-quarters of businesses already using AI report higher productivity, yet most are still applying it to a narrow set of tasks,” says Simon Worsfold, head of data communications at Intuit QuickBooks, which puts out a monthly Small Business Index exploring market trends. “What is emerging is a large, underserved layer of advisory, implementation, and training services that small businesses need in order to scale their use of AI,” he says. Here are five ideas for AI-focused side hustles that could be lucrative—or even become the foundation of a full-time business. AI Consultant This is a side hustle with multiple branches. Some people are well suited to help people or businesses integrate AI with their calendar, notes, and local files. Others can develop workflow audits that review how a company’s employees work to discover repetitive tasks that the AI could handle. Rates for an AI consultant range from $150–350 per hour for independent workers and people running it as a side hustle. Those can jump as high as $600 per hour if you convert this side hustle into a full-time company. AI Researcher To stay competitive, businesses need to know what their competitors are doing and what’s trending in their industry. That data can be remarkably complex, however, and not every founder or CEO has the time to do the deep dive it requires. Side hustle operators with strong AI skills can use the technology to filter the data into easily digested insights, then sell those as reports, newsletters, or direct subscriptions. You’ll need to carefully identify the best source material and be sure to double check the output, since AI’s comprehension is still flawed. “The AI doesn’t give the correct answer all the time,” says Shaun Ghavami, Founder of 10XBNB, a side hustle-turned-business that now oversees a portfolio of over $100 million of short-term property rentals. “The real skill is in prompting.” GEO (AI Search) Optimization For the past two decades, businesses have hired specialists to help them rank high on search results pages. While that’s still valuable placement, smart business owners are also looking into how they can be among the frequently-cited sources for AI search results. People with a combination of AI and content knowhow can create a side hustle specializing in this. You’ll teach companies the best ways to refine their content and meta tags and improve readability for large language models. If you have the tools to measure analytics, such as Alli AI, Frase, and MarketMuse, you have a better chance of establishing a recurring relationship with those clients, increasing your income and establishing a base should you want to make this more than a side hustle. Content Repurposing (Clipping) Both content creators and businesses regularly churn out videos and stories as promotional tools, or in an effort to be seen as thought leadership experts. Quite often, though, that content needs to be pared down before they’re posted on everything from TikTok to LinkedIn to Instagram. And that takes time, which the companies and content creators may not have to spare. As an AI content repurposing expert, you can transform the long-form content into digestible bites to widen the potential audience in a much shorter period of time. Use tools like CapCut, Canva, and ChatGPT to effortlessly pick and highlight the most relevant parts. Create AI Microtools AI can be intimidating to many people who don’t know where to start, especially when it comes to creating agents or GPTs that are relevant to their needs. A smart side hustle operator, though, knows that you don’t have to be an expert to create your own AI tools. Sites like Gumloop let you visually build workflows that can be run at large scale. You’ll use a drag and drop template that lets you create workflows that do just about anything, from running a search engine optimization audit of a Website to a ranking system for job applicants. You can either custom create those for clients or build general purpose tools and sell them on Etsy or some other marketplace. BY CHRIS MORRIS @MORRISATLARGE

Want AI to Actually Help Your Company Make Money? Follow These 5 Tips From Microsoft’s Playbook

Buying AI tools is easy. The hard part is turning them into actual business results. On Thursday, Microsoft published its Frontier Playbook, a guide for companies trying to move beyond AI experiments and into time-saving deployments that boost productivity. The playbook draws on more than 100 of Microsoft’s internal AI projects across its corporate functions, commercial organization, and engineering teams. A McKinsey survey published in August on enterprise AI adoption found that nearly 90 percent of respondents said their organizations regularly used AI in at least one business function. But only 44 percent said AI was scaling across the enterprise as token costs rise. That’s up from 38 percent in 2025. The study comes as businesses are making their AI deployments with caution. Microsoft’s wisdom aims to make that shift easier. By studying what worked and what fell short, Microsoft concluded that AI adoption can’t be treated like a software rollout or another IT project. Rather, it’s a “business transformation” that must be guided with “clear business outcome goals,” according to the playbook. Here are its five biggest takeaways. 1. Set actual business goals Start with the outcome, not a pile of possible AI uses. Take the sales team, for example. Rather than simply getting more sales representatives to use Copilot, Microsoft suggests tailoring its usage for specific outcomes. That could mean setting goals like increasing revenue per representative, boosting conversion rates, and improving customer retention. Microsoft also recommends assigning an executive to own each goal. 2. Build a “diffusion engine” Microsoft recommends fixing inefficient processes before automating them. For example, its supply-chain team simplified its workflows before deploying 111 AI agents across planning, sourcing, fulfillment, and logistics. The company says cycle times—the time it takes to complete a task—fell 75 percent in selected workflows, reducing manual effort and increasing measurable value. Redesigning workflows is part of what Microsoft calls a “diffusion engine,” which is a system that also includes training employees, tracking results, and spreading successful practices. 3. Invest in your people Microsoft found that manager behavior was its strongest predictor of AI adoption. The tech titan found that its employees saw 17 percentage points more value from AI when managers actively demonstrated how they used it, according to the company’s playbook. The company embeds short lessons into employees’ workflows and recruits advanced AI users to mentor colleagues. It recommends involving employees in job redesign and strengthening skills such as judgment, critical thinking, and business acumen. 4. Codify your advantage and controls A generic AI model does not know what makes your company different. Microsoft recommends turning institutional knowledge—including your company’s mission statement, performance standards, taste, and risk limits—into private evaluations that test whether AI performs work the company’s way. A customer-service business, for example, could evaluate AI responses based on accuracy, tone, and if it properly handles escalating an issue to a person. 5. Safeguard your security Treat AI like you would a human. Microsoft says each agent should have its own identity, limited permissions, and a record of what it does. Their actions should be traceable, auditable, and reversible. That way, humans catch mistakes and misuse without losing control as adoption grows. BY AARON MOK

These 40 Jobs May Be Replaced by AI. These 40 Probably Won’t

A new study measuring the use of generative artificial intelligence in different professions has just gone public, and its main message to people working in some fields is harsh. It suggests translators, historians, text writers, sales representatives, and customer service agents might want to consider new careers as pile driver or dredge operators, railroad track layers, hardwood floor sanders, or maids — if, that is, they want to lower the threat of AI apps pushing them out of their current jobs. Why should anyone heed yet another of the myriad, sometimes conflicting reports in AI’s potential impacts on jobs? Because the researchers behind the new findings really know what they’re talking about. They all work for tech giant Microsoft, which is developing Copilot and related AI apps examined in the study. And those tools, the authors say, risk putting ticket agents and telemarketers out of work far sooner than orderlies and paving equipment operators. The Microsoft study comes as debate continues about the employment threats AI may pose to millions of people in clerical, administrative, communications, marketing, and other jobs. Executives of several tech companies, including AI developer Anthropic CEO Dario Amodei, have alternatively cheered or warned about bots automating a wide range of work tasks, potentially eliminating up to half of all white-collar and entry-level jobs in the process. Other business leaders, notably serial entrepreneur Mark Cuban, believe the tech will generate even more new positions than it erases by assuming a lot of repetitive drudge work. Microsoft’s new research doesn’t offer an opinion on the quantitative consequences on employment that AI will ultimately have. But it does provide clear indication of which 40 jobs are already using apps most frequently — and the contrasting 40 professions reflecting the tech’s lowest levels of penetration. The full text of their findings and the two rankings are available here. These 40 jobs are most threatened by AI Interpreters and Translators Historians Passenger Attendants Sales Representatives of Services Writers and Authors Customer Service Representatives CNC Tool Programmers Telephone Operators Ticket Agents and Travel Clerks Broadcast Announcers and Radio DJs Brokerage Clerks Farm and Home Management Educators Telemarketers Concierges Political Scientists News Analysts, Reporters, Journalists Mathematicians Technical Writers Proofreaders and Copy Markers Hosts and Hostesses Editors Business Teachers, Postsecondary Public Relations Specialists Demonstrators and Product Promoters Advertising Sales Agents New Accounts Clerks Statistical Assistants Counter and Rental Clerks Data Scientists Personal Financial Advisers Archivists Economics Teachers, Postsecondary Web Developers Management Analysts Geographers Models Market Research Analysts Public Safety Telecommunicators Switchboard Operators Library Science Teachers These 40 jobs are least threatened by AI Phlebotomists Nursing Assistants Hazardous Materials Removal Workers Helpers–Painters, Plasterers Embalmers Plant and System Operators, All Other Oral and Maxillofacial Surgeons Automotive Glass Installers and Repairers Ship Engineers Tire Repairers and Changers Prosthodontists Helpers–Production Workers Highway Maintenance Workers Medical Equipment Preparers Packaging and Filling Machine Operators Machine Feeders and Offbearers Dishwashers Cement Masons and Concrete Finishers Supervisors of Firefighters Industrial Truck and Tractor Operators Ophthalmic Medical Technicians Massage Therapists Surgical Assistants Tire Builders Helpers–Roofers Gas Compressor and Gas Pumping Station Operators Roofers Roustabouts, Oil and Gas Maids and Housekeeping Cleaners Paving, Surfacing, and Tamping Equipment Operators Logging Equipment Operators Motorboat Operators Orderlies Floor Sanders and Finishers Pile Driver Operators Rail-Track Laying and Maintenance Equipment Operators Foundry Mold and Coremakers Water Treatment Plant and System Operators Bridge and Lock Tenders Dredge Operators The results were obtained by analyzing 200,000 “conversations between users and Microsoft Bing Copilot.” Researchers then matched those with “measurements of task success and scope of impact, [to] compute an AI applicability score for each occupation.” The jobs with the highest use rates tended to be office positions or other work communicating data or thoughts for specific business purposes. “We find the highest AI applicability scores for knowledge work occupation groups such as computer and mathematical, and office and administrative support, as well as occupations such as sales whose work activities involve providing and communicating information,” the study says. “Additionally, we characterize the types of work activities performed most successfully, how wage and education correlate with AI applicability, and how real-world usage compares to predictions of occupational AI impact.” The upshot of that is data showing the work of ticketing agents, proofreaders, and PR specialists is already being automated at far higher levels than labor provided by housepainters and plasterers, embalmers, ship engineers, and phlebotomists — the technicians who draw blood for medical tests. But despite the study establishing a de facto ranking of the jobs threatened the most — and least — by AI, its authors ultimately waffle a bit on just how big the tech’s impact on overall employment and workplace stability might be. That’s probably not surprising, given they all work for the same Microsoft employer whose business future will largely depend on successfully developing and selling those work-automating apps to other companies. And some of the study’s disclaimers suggest underlining AI’s potential for possibly eviscerating current employee counts wasn’t considered the best messaging for broadening the appeal of apps to prospective customers. “It is tempting to conclude that occupations with high overlap will experience job loss,” they write in one of those hedges on AI’s likely impact on employment. “This would be a mistake, as our data do not include the downstream business impacts of new technology, which are very hard to predict.” On the one hand, authors do specify that AI tools are being used most often for communications tasks like language interpretation, emailing, and composing marketing materials. But on the other, they hasten to add it isn’t clear apps are also being asked to assume the complete array of tasks those workers perform on the job — or whether they’d even be capable of doing that. The researchers similarly note the different objectives employees studied had in using bots. Some of those workers asked apps to entirely handle and complete certain job tasks. But in many other cases, people queried AI assistants about the most effective ways to fulfill work duties themselves, retaining their own value to employers. Meantime, the study’s authors also seem to balance between the higher productivity objectives — and potentially decreased labor costs — that some employers hope AI will provide and employees’ contrasting fears about their job security. Those diverging focuses, the authors say, won’t generate the zero-sum results many warn of — at least not necessarily. “For example, if AI makes software developers 50 percent more productive, companies could raise their ambitions and hire more developers as they are now getting more output per developer, or hire fewer developers because they can get the same amount done with fewer of them,” they say. “Our data is only about AI usage and we have no data on the downstream impacts of that usage, so we only weigh in on the automation versus augmentation question by separately measuring the tasks that AI performs and assists.” But the study also makes it clear that the jobs least likely to be disrupted initially by increased or dominant use of AI are those involving some mixture of manual activity, use of machines, and interaction with people. That combination leaves nursing assistants, hazardous waste removers, car windshield installers, and medical equipment preparers among the professions with the lowest level of app penetration. But even there, the authors create some wiggle room for eventual employment outcomes. They note their research is based on use of AI that Microsoft developed from large language models (LLMs). More focused apps tailored to individual professions — possibly paired with robotic machines — might still leave many manual jobs vulnerable to the tech’s influence in the future. “Note that our measurement is purely about LLMs,” the authors note. “Other applications of AI could certainly affect occupations involving operating and monitoring machinery, such as truck driving.” Meaning, any historians or brokerage clerks feeling fearful about their work after reading the study might want to rethink any plans about rushing into careers as a roustabout or packaging machine operator. Because those professions, too, may come under the growing influence of specialized AI apps in the not too distant future. BY BRUCE CRUMLEY @BRUCEC_INC

Only 14 Percent of Small Businesses Have Successfully Integrated AI. Anthropic Says This Is the Missing Link

Small businesses want to use AI. The problem, Anthropic says, is that many don’t know how. On Thursday, Anthropic published findings from its Claude SMB Tour, a series of free workshops it held for six weeks with more than 1,000 small business owners across 10 U.S. cities. The majority of attendees came from industries like construction, manufacturing, and logistics. Before launching the tour, Anthropic surveyed 503 small-business decision-makers. It found that 81 percent were open to trying new AI tools. Their top pain point, however, was that employees didn’t know how or when to use them. That uncertainty showed up during the workshops. Anthropic says many attendees had already used its Claude chatbot daily, but hadn’t tried more advanced features like Cowork, skills, or connectors, which use agents, instructions, and integrations to automate multi-step workflows. Others told Anthropic that AI was changing so quickly that training programs struggled to keep up. Anthropic says hands-on training helped. During the workshops, business owners learned how to set up Claude Cowork and build workflows for tasks like automating payroll or creating a “virtual chief-of-staff.” Across 635 exit surveys, the guided build session was the most-cited highlight, and nearly two-thirds of attendees asked for more hands-on help implementing AI afterward. Owners also wanted to learn from other small businesses. Hearing how their peers used AI was the second-most-cited highlight of the workshops, and attendees requested a shared collection of real-world use cases more often than any new product feature, according to Anthropic. The findings come as small businesses race to figure out where AI fits into their operations. A Goldman Sachs survey of 1,256 small business owners published in March found that 76 percent of them were using AI, but just 14 percent had fully integrated it into their core operations. Nearly half cited a lack of technical expertise as a barrier, while 73 percent said more training and resources would help them implement AI. For small businesses with limited staff and resources, that training can help owners move beyond playing around with chatbots and identify tasks they can actually hand off to AI, potentially freeing up time for work. Anthropic is betting that more training can close that gap. The company is launching a Claude SMB Trainer Program to teach community organizations and AI partners how to bring AI workshops to small businesses themselves. The first two training sessions will take place in San Francisco and New York City, with the dates still to be announced. Its Claude SMB Tour is also expanding to more cities this fall, starting with Boston on September 16. BY AARON MOK