Solopreneur AI Statistics: Adoption vs. Integration

Artificial intelligence is changing how Americans run businesses without employees. Independent consultants use it to research and prepare client work. Online sellers use it to manage product information. Local service providers experiment with automated inquiries, scheduling, and administrative tasks.

But using AI occasionally and integrating it into everyday business operations are two different things.

The U.S. Census Bureau counted 31,985,874 nonemployer establishments in 2024, generating approximately $1.86 trillion in gross receipts. These businesses have no paid employees and provide the closest available federal measure of the solopreneur economy.

In the Federal Reserve Banks’ 2025 Small Business Credit Survey, 40% of surveyed nonemployer firms reported using AI. Yet only 10% of those already using AI said they had fully integrated it into their operations.

Meanwhile, a September 2026 FreshBooks survey found that 86% of surveyed solopreneurs and microbusiness owners try AI before hiring outside help for a task they cannot complete independently.

These findings point to a changing business model. AI is becoming part of how independent owners work, but adoption alone does not establish better financial performance.

This research examines how solopreneurs are adopting AI, where they use it, the costs and barriers they face, and what evidence shows about productivity, revenue, and business growth.

Key Findings

• 40% of surveyed nonemployer firms used AI. The comparable figure among businesses with employees was 46%, a six-percentage-point difference.
• Only 10% of nonemployer AI users reported full integration. Another 45% were experimenting, while 45% had partially integrated the technology.
• Writing and marketing dominate adoption. Among nonemployer AI users, 87% used AI for writing or marketing, compared with 36% for administrative business functions.
• AI is influencing outsourcing decisions. In the FreshBooks survey of 500 solopreneurs and microbusiness owners, 86% said they attempt to use AI before hiring outside help for work they cannot complete themselves.
• Some business owners report meaningful time savings. In a separate survey of 187 AI-using small-business owners, 60% reported saving at least two hours per week. The result was not reported separately for solo owners.
• Accuracy is the leading AI-related concern. Among nonemployer AI users surveyed by the Federal Reserve, 51% reported concerns about accuracy, bias, or misinformation.
• Business challenges remain widespread. Some 62% of surveyed nonemployer firms reported difficulties reaching customers or increasing sales, while 41% reported operating at a loss at the end of 2024.
• Most nonemployer establishments have relatively low receipts. Census data show that 86.69% generated less than $100,000 in annual gross receipts in 2024.
• A nationwide AI profitability benefit has not been established. The available U.S. datasets do not demonstrate how much additional profit AI adoption has generated for solopreneurs.

Research qualification: The Federal Reserve figures come from a weighted, nonrandom business survey. Census counts come primarily from administrative tax records. The 40% survey adoption rate cannot be multiplied by the nearly 32 million establishments to produce a verified national count of AI-using solopreneurs.

How Big Is America’s Solopreneur Economy?

The Census Bureau’s 2024 Nonemployer Statistics, released September 29, 2026, show that the number of nonemployer establishments increased by approximately 1.56 million from 2023.

Gross receipts also increased, although average receipts per establishment grew much more slowly.

Source: U.S. Census Bureau, 2023 and 2024 Nonemployer Statistics. Growth rates and averages calculated from published national totals. Receipts are nominal and not adjusted for inflation.

The number of establishments grew by 5.12%, but that does not mean 1.56 million additional people became full-time entrepreneurs.

An establishment is a business reporting unit. One person may own multiple establishments, and some owners operate businesses alongside paid employment.

What Counts as a Solopreneur?

A solopreneur generally operates a business independently, without employees. The Census Bureau uses a more specific statistical definition.

Nonemployer Statistics generally include businesses that:

• Have no paid employees.
• Are subject to federal income tax.
• Record at least $1,000 in annual receipts, except construction businesses, which have a $1 threshold.
• Fall within the industries and geographic areas covered by the program.

The categories overlap, but they are not identical.

The 2024 Census legal-form breakdown included 27,644,187 sole proprietorships, representing 86.4% of nonemployer establishments. Another 4,341,687 establishments had other legal forms, including partnerships and corporations.

Some of those establishments may have multiple owners or use independent contractors.

This distinction matters because claims about the number of solopreneurs often mix individuals, self-employed workers, sole proprietors, and nonemployer establishments.

For readers considering independent business ownership, our earlier examination of the challenges of starting a solo business provides additional context about managing work, expenses, and responsibilities without a traditional team.

Most Nonemployer Businesses Generate Less Than $100,000 Annually

The average nonemployer establishment generated $58,194 in gross receipts in 2024.

That figure does not describe the typical owner’s take-home income.

Business expenses, contractors, taxes, and other costs must be considered before receipts can be interpreted as earnings.

The national receipts distribution also shows that most nonemployer establishments operate at relatively small revenue levels.

Source: Census Bureau, 2024 Nonemployer Statistics. Shares independently calculated and rounded.

Approximately 86.69% of establishments recorded less than $100,000 in annual gross receipts.

The midpoint establishment falls within the $10,000–$24,999 receipts bracket. The published table does not identify an exact median dollar amount.

This distribution has several implications for AI adoption.

• AI budgets cannot be assumed to be uniform. A business recording $10,000 annually has a different capacity to absorb recurring software costs than one generating $250,000.
• Cost savings matter differently across businesses. A subscription replacing an existing expense may be more valuable than one adding a new expense without measurable returns.
• Not every establishment is a full-time business. Some owners may use their businesses to supplement income rather than replace employment.
• Revenue does not establish software purchasing power. Businesses with similar gross receipts may have very different operating expenses and margins.

There is also a difference between the Census population and the Federal Reserve survey.

In the Federal Reserve’s 2025 nonemployer sample, 69% of respondents reported annual revenues of $100,000 or less. That differs from the Census’s approximately 86.7% below $100,000.

The reporting thresholds, years, and data collection methods are not identical. Still, the difference is important when interpreting survey results as evidence about the entire nonemployer economy.

How Many Solopreneurs Are Using AI?

The Federal Reserve Banks’ 2026 Chartbook on Nonemployer Firms provides one of the most relevant recent views of AI use among businesses without employees.

The survey was conducted between September and November 2025.

Its optional AI module received answers from 4,013 nonemployer firms and 5,248 employer firms.

Source: Federal Reserve Banks, 2026 Nonemployer Chartbook, page 58. Figures describe weighted survey responses and are not a verified census of AI use.

Employer firms were six percentage points more likely to report currently using AI.

However, nonemployer firms were slightly more likely to say they intended to begin using it within the next year.

The 18% planning figure represents an intention expressed in fall 2025. It does not confirm that those businesses adopted AI in 2026.

AI Adoption and AI Integration Are Different

Among businesses already using AI, relatively few said it was fully integrated into their operations.

Source: Federal Reserve Banks, 2026 Nonemployer Chartbook, page 59. Percentages are conditional on current AI use.

The difference becomes clearer when considering what each level might look like in practice.

• Experimentation: A business owner occasionally asks an AI assistant to summarize research or prepare a marketing draft.
• Partial integration: The owner uses AI within recurring activities, such as weekly reports, proposal preparation, or customer-inquiry organization.
• Full integration: AI has become an established component of ongoing business processes, with repeatable workflows and defined oversight.

These descriptions illustrate the operating distinction rather than additional categories measured by the survey.

Multiplying the rounded 40% adoption rate by the 10% full-integration share suggests that approximately 4% of the weighted nonemployer survey population both used AI and reported full integration.

That is a derived survey proportion, not a confirmed national business count.

Another finding adds context. Among firms already using AI, 29% of nonemployers described it as very important to producing their core goods or services. The comparable figure among employer firms was 21%.

Nonemployer firms were less likely to use AI overall, but a larger share of those using it considered the technology very important to their core work.

The Federal Reserve did not establish whether these firms earned higher profits because of that dependence.

What Are Solopreneurs Actually Using AI For?

The strongest AI adoption is concentrated in writing, marketing, productivity, and planning.

Administrative business functions, customer service, and coding are less common.

Source: Federal Reserve Banks, 2026 Nonemployer Chartbook, page 61. Nonemployer AI-user sample: 1,612. Multiple selections were allowed.

Writing and marketing use exceeded administrative business use by 51 percentage points among nonemployer AI users.

That gap matters because producing content and operating a business involve different kinds of work.

Writing and Marketing Are the Most Common Uses

Independent owners may use AI to prepare:

• Website and product descriptions.
• Marketing emails.
• Social media content.
• Sales proposals.
• Presentations.
• Customer-facing explanations.
• Initial advertising concepts.
• Research summaries.

These activities are generally easier to experiment with because the owner can inspect a draft before publishing or sending it.

However, producing more marketing content does not automatically solve customer acquisition problems.

The same Federal Reserve survey found that 62% of nonemployer firms reported challenges reaching customers or increasing sales.

The survey does not establish whether AI marketing caused, reduced, or failed to affect those challenges.

It demonstrates that marketing activity and commercial outcomes are different measures.

A solopreneur developing a customer-acquisition strategy can combine AI-assisted production with a broader approach to marketing a one-person business.

For website traffic, the fundamentals also remain relevant. Our guide to essential SEO skills for solopreneurs addresses the search and website knowledge that AI-generated content alone cannot replace.

Planning and Analysis Are Also Widely Used

Among nonemployer AI users, 61% reported using AI for planning or analysis, compared with 51% of employer AI users.

These tasks may involve:

• Analyzing sales records.
• Reviewing customer feedback.
• Organizing competitor research.
• Comparing pricing options.
• Preparing financial scenarios.
• Summarizing reports.
• Identifying recurring customer problems.

The results can be useful without requiring the AI system to make the final business decision.

For example, a business owner might ask AI to group customer complaints by subject. The resulting categories can help identify a recurring issue, but the owner still needs to check the original messages and decide what to change.

The Federal Reserve figures establish that planning and analysis are common AI uses. They do not measure how often AI-generated analysis leads to better pricing, stronger customer retention, or improved profitability.

Administrative Business Functions Remain Less Common

Only 36% of surveyed nonemployer AI users reported applying the technology to administrative business functions.

Potential uses include:

• Preparing invoice drafts.
• Organizing business expenses.
• Summarizing customer inquiries.
• Updating business records.
• Tracking follow-up tasks.
• Preparing routine reports.
• Organizing meeting notes.

These activities can require access to actual business records, connected applications, and sometimes financial information.

That makes them different from producing a standalone marketing draft.

An incorrect social post may be corrected before publication. An incorrect invoice, duplicate payment instruction, or missing customer record can create more difficult operational problems.

The practical opportunity is to automate suitable execution work while preserving controls over consequential decisions.

For readers who want to explore individual products, integrations, and software comparisons, we cover those separately in our guide to AI tools and skills for solopreneurs. The focus here is adoption, integration, and measured business outcomes rather than a ranking of applications.

AI Opportunities Differ Across One-Person Business Models

Research about solopreneurs often emphasizes digital businesses, including freelance writing, consulting, software development, and online content creation.

Those activities represent only part of the nonemployer economy.

The Census Bureau’s largest nonemployer industry in 2024 was transportation and warehousing, with nearly 4.5 million establishments.

Source: Census Bureau, 2024 Nonemployer Statistics. Industries ranked by establishment count. Averages derived from industry receipts divided by establishments.

A transportation business cannot use AI to perform the actual driving. A construction contractor still needs to complete physical work. A local service provider cannot automatically replace an in-person appointment with generated text.

AI may still assist with the paperwork, communication, scheduling, research, or planning surrounding those activities.

The important distinction is between the work that must be performed and the supporting tasks that may be improved.

AI Integration Matrix by Business Model

The following examples describe potential applications and evaluation criteria. They do not represent measured AI adoption rates or verified financial results within each industry.

Freelancers: Using AI Without Losing Their Brand Voice

For a freelance writer, consultant, coach, or creative professional, the final product often depends on judgment and a recognizable style.

AI can help prepare drafts, but generic output may weaken that differentiation.

One way to reduce the problem is to build a reference based on approved examples of the business’s existing work.

1. Collect representative samples. Select three to five approved emails, proposals, or deliverables that reflect the established voice.
2. Document the style. Record typical sentence length, level of formality, preferred language, and phrases to avoid.
3. Provide business context. Include accurate service information, positioning, and customer expectations.
4. Review generated drafts. Compare the output with the approved examples before delivering it to a client.
5. Measure editing work. Track drafting time, revisions, and corrections rather than only how quickly the first draft appeared.

For example, a consultant can use approved proposal samples to prepare a new proposal outline. The final scope, commitments, pricing, and claims still need direct review.

This is an illustrative workflow, not a reported client case study.

Local Services: AI Can Support the Booking Process

Consider an independent home-cleaning business receiving requests about services, availability, and appointments.

A possible workflow is:

1. The customer submits an inquiry through a form.
2. An AI assistant summarizes the non-sensitive request.
3. The owner verifies the service requirements and price.
4. An appointment is confirmed using scheduling software.
5. The scheduling system sends an automatic reminder.

Existing scheduling products such as Square Appointments already provide booking and reminder functions. Those features do not require an AI system to make pricing or availability decisions.

AI may be useful for organizing inquiries or drafting communications, while the scheduling system manages confirmed appointments.

The owner should continue handling unusual requests, disputed charges, hazardous work, and exceptions to normal policy.

Relevant measurements include inquiry-response time, incorrect estimates, completed bookings, and administrative hours.

Online Sellers: AI Can Support Listings and Customer Questions

An online seller may use AI within an existing ecommerce platform rather than building an entirely separate workflow.

For example, Shopify Magic can assist with product-description drafts, while Shopify Inbox provides AI-generated suggested replies for customer messages.

A potential workflow is:

Verified product details → AI-assisted description → owner review → published listing → customer inquiry → suggested reply → owner approval.

Product facts still need verification, including:

• Materials and ingredients.
• Dimensions and sizing.
• Care instructions.
• Compatibility and technical specifications.
• Shipping and return policies.
• Product benefits and advertising claims.

Better writing does not compensate for inaccurate product information.

A merchant can compare listing preparation time, customer reply corrections, product-page conversion, and returns related to misleading descriptions.

Shopify’s documentation establishes the available functions. It does not prove that this illustrative workflow increases sales.

Nontechnical Owners: Test One Process Before Paying for Automation

Business owners do not need technical expertise or custom software connections to test whether AI is useful.

A basic evaluation can remain manual.

1. Choose one repetitive task that produces an output the owner can inspect.
2. Use approved sample information without unnecessary customer details.
3. Complete ten typical tasks with an existing or free AI application.
4. Record the time spent preparing, checking, and correcting the results.
5. Compare those results with similar tasks completed without AI.
6. Continue only if the quality and net time savings justify the process.

This ten-task exercise is a proposed evaluation method, not a published performance benchmark.

It is particularly relevant for owners who do not want to manage APIs, multiple software subscriptions, or complicated automations.

AI Is Changing How Solopreneurs Think About Hiring

A September 2026 FreshBooks survey suggests that AI is becoming an initial option when independent owners encounter work they cannot perform themselves.

The FreshBooks study, conducted by Wakefield Research, included 500 solopreneurs and microbusiness owners surveyed between June 22 and July 1, 2026.

Its findings included:

• 86% try AI before hiring someone for a task they cannot complete independently.
• 90% say AI makes starting and running a business easier for one person.
• 65% say reviewing and checking AI-generated work can create a risk of AI-related burnout.
• 57% spend more than ten hours weekly on administrative work.
• 56% use AI for marketing and design, compared with 46% for financial management.

The findings describe the survey’s respondents, which include both solopreneurs and microbusiness owners. They are not nationally representative estimates for all U.S. nonemployer establishments.

The 86% figure also does not mean that 86% eliminated an employee position or stopped hiring contractors.

Trying AI first may mean testing whether it can prepare a draft, answer a question, or assist with an unfamiliar task.

Whether it can replace paid assistance depends on the completed work, accuracy, responsibility, and cost.

When AI, a Virtual Assistant, a Specialist, or the Owner Makes Sense

A virtual assistant is a person who can carry out assigned tasks, ask follow-up questions, manage exceptions, and coordinate ongoing work.

An AI application may prepare information or perform configured actions, but responsibility for the result remains with the business.

Freelance marketplaces such as Upwork identify email handling, calendars, research, customer inquiries, and data entry among common virtual-assistant responsibilities.

A specialist freelancer serves a different purpose from a general virtual assistant.

Tax professionals, security consultants, experienced designers, and other specialists may provide expertise that neither the owner nor an AI application possesses.

The decision also connects to the broader question of whether to build a business alone or with a partner. AI may expand an owner’s working capacity, but it does not assume the responsibilities of an actual business partner.

What Does AI-Assisted Work Cost Compared With a Virtual Assistant?

Cost comparisons should begin with the same finished task and the same quality standard.

Upwork’s May 2026 hourly-rate guide lists virtual assistants at approximately $10–$20 per hour, with specialized services potentially costing more.

Those are marketplace guide ranges, not guaranteed quotes.

Consider an illustrative monthly workload of routine customer inquiries.

In one approach, a virtual assistant spends ten hours handling the work at an assumed rate of $15 per hour.

In another, a paid automation assists with drafting and processing, while the owner spends two hours reviewing the results.

Illustrative comparison, not a reported company result. The $19.99 amount uses Zapier Professional’s advertised monthly equivalent when billed annually, as listed in the October 2026 research. API spending, hourly rates, and owner time values are assumptions. Initial setup, annual commitment effects, and exceptional work are excluded.

Under these assumptions, the AI-assisted route costs $55.01 less for the month.

That saving is meaningful only if both approaches complete the required work to an equivalent standard.

If the virtual assistant resolves customer issues independently while AI only prepares drafts, the comparison is incomplete.

Owners also need to count setup time, escalations, mistakes, missed inquiries, and other tasks that return to them.

Business Challenges Persist Despite AI Adoption

The Federal Reserve’s 2025 survey shows that nonemployer businesses face operational and financial challenges that extend well beyond content creation.

Source: Federal Reserve Banks, 2026 Nonemployer Chartbook, pages 20–21. Operational and financial challenges come from separate survey questions. Respondents could select multiple answers.

These figures help explain why AI adoption alone is an incomplete measure of business improvement.

• A business may generate marketing content more quickly while struggling to find paying customers.
• Invoice preparation may become faster without reducing late payments.
• AI-generated proposals may save preparation time without improving acceptance rates.
• Customer support may become more efficient without addressing the underlying reason for complaints.
• Automated recordkeeping may reduce manual work while introducing new verification requirements.

Different business challenges require different measurements.

Profitability Is a Separate Test

The Federal Reserve survey found that nonemployer firms were less likely than employer firms to report operating at a profit at the end of 2024.

Source: Federal Reserve Banks, 2026 Nonemployer Chartbook, page 11. Percentages are rounded and may not total exactly 100%.

The nine-percentage-point profitability difference cannot be attributed to AI.

The figures describe the financial position of different business populations. They do not compare otherwise equivalent AI adopters and nonadopters.

The survey also found that 64% of nonemployer firms experiencing financial challenges used personal funds in response, compared with 54% of employer firms.

That makes implementation cost especially relevant.

For owners using personal savings to cover business expenses, another recurring subscription must compete with inventory, rent, transportation, taxes, and other obligations.

AI may eventually reduce expenses or improve capacity, but the return should be evaluated before assuming the cost is justified.

Our article on staying cash solvent in the first year of business discusses the broader financial discipline that remains relevant regardless of which technology a company uses.

Does AI Actually Save Time for Solopreneurs?

Recent surveys provide evidence that some business owners and workers report substantial time savings from AI.

But the results come from different populations and should not be combined into one national estimate.

Small-Business Owners Who Already Use AI

A Network Solutions survey published October 20, 2026 examined 187 U.S. small-business owners who had used AI in the previous three months.

Of those respondents, 57% operated their businesses alone.

Across the entire selected sample:

• 60% said AI saved at least two hours per week.
• 29% reported saving six or more hours weekly.
• 12% reported saving eleven or more hours weekly.
• 73% used more than one AI tool.

The study also found a relationship between the number of tasks assigned to AI and reported time savings.

Among respondents using AI for eight or more of ten surveyed business tasks, 48% reported saving at least six hours weekly.

Among those using it for four or fewer tasks, only 8% reported that level of time savings.

That is an association, not proof that assigning more tasks to AI caused the difference.

The survey included only owners already using AI. Its time-savings results were not published separately for solopreneurs.

What the U.S. Census Bureau Found About Workers

The Census Bureau’s March 2026 Household Trends and Outlook Pulse Survey provides a separate view of reported AI time savings among workers.

Among respondents who used AI at work during the previous week:

Source: U.S. Census Bureau, August 11, 2026, revised September 24, 2026. Figures are self-reported estimates among recent workplace AI users, not a solopreneur-specific sample.

The results show meaningful variation.

Some people report saving several hours each week. Others report no benefit or additional time required.

Neither this study nor the Network Solutions survey provides a nationally verified average number of hours saved by U.S. solopreneurs.

Why Reported Time Savings Need Context

Consider two different outcomes.

A consultant uses AI to prepare a report in three hours instead of five. The report still requires the same quality review and satisfies the client’s requirements.

Another consultant generates the report in one hour but spends four additional hours correcting unsupported claims and formatting mistakes.

The initial drafting speed may be impressive in the second situation, but the complete process takes longer.

These are illustrative scenarios, not observed business cases.

Useful measurements include:

• Initial task time.
• Review and correction time.
• Time spent preparing instructions and source material.
• Time required to transfer information between applications.
• Completed work accepted by the customer.
• Actual expenses reduced or revenue-producing capacity created.

Real Solopreneur Businesses Using AI: What the Cases Show

Named business accounts provide examples of how AI is being incorporated into independent companies.

They also illustrate why customer numbers, business receipts, and profitability should not be treated as interchangeable.

Ben Broca: 10,000 Paying Customers Without Employees

In a July 2026 Wall Street Journal report, entrepreneur Ben Broca described running a business offering AI tools to entrepreneurs without other employees.

The publication reported:

• Approximately 10,000 paying customers.
• No additional employees.
• AI assistance across business activities.
• A projected $10 million in revenue during 2026.

The paying-customer count was a reported commercial outcome.

The $10 million figure was a projection at the time of publication, not verified completed annual revenue.

The account demonstrates that at least one founder reported substantial customer activity while operating without a traditional employee team.

It does not independently establish the portion of revenue attributable to AI or the company’s net profit.

Junead Khan: An Early-Stage One-Person Software Business

In an October 11, 2026 Business Insider account, Junead Khan described leaving Microsoft to build Treasury, a financial-coaching software business.

Khan reported:

• Operating the business without a cofounder or employees.
• Using AI coding tools, including Claude Code and Codex, to develop the product.
• Generating more than $6,000 in revenue from paying customers.
• Continuing to rely on personal savings rather than drawing a salary.

The account illustrates how AI-assisted development can support an individual founder in bringing a software product to market.

It also demonstrates that generating customer revenue is not the same as achieving financial independence or profitability.

An Unsuccessful AI-Assisted Venture

The Wall Street Journal also reported the experience of Samir Ahmad, who used AI while building a solo coaching and consulting business.

The venture did not gain sufficient traction, and Ahmad returned to employment.

This is an individual account of an unsuccessful business that used AI.

It does not establish that AI caused the failure.

Together, these cases reveal different commercial outcomes:

Business outcomes depend on more than the software used.

Product demand, pricing, experience, industry knowledge, customer acquisition, available capital, and competition all affect whether a venture succeeds.

AI Advice Does Not Always Improve Business Performance

One of the most important research findings comes from a randomized field experiment rather than a commercial survey.

A July 2026 study published in Management Science examined a GPT-4-powered business adviser provided to entrepreneurs in Kenya.

The researchers studied 640 entrepreneurs over approximately five months.

The experiment did not find a statistically established average improvement in business revenue or profit across the full sample.

However, results differed depending on how businesses performed before receiving AI assistance.

• Businesses with weaker initial performance experienced worse outcomes after receiving AI advice.
• Businesses with stronger initial performance showed suggestive evidence of improvement.
• The differences appeared connected to which recommendations owners selected and implemented.

The study reported that initially lower-performing businesses experienced outcomes approximately 10% worse, while initially stronger businesses may have benefited by more than 15%.

The positive result for stronger businesses was suggestive rather than definitive at conventional statistical thresholds.

Researchers found that weaker performers were more likely to adopt generic strategies, such as reducing prices or increasing advertising, while stronger performers more often implemented changes tailored to their specific business conditions.

This does not establish that AI advice generally harms inexperienced entrepreneurs or that the same results would occur in the United States.

The study examined a specific intervention, population, and period.

It does establish an important limitation: access to useful-looking AI advice does not guarantee that a business owner will choose and execute the right action.

A practical evaluation should separate three questions:

1. Did AI produce usable information?
2. Did the information improve a business process or decision?
3. Did that improvement produce a meaningful customer or financial result?

A pilot can succeed at the first stage while failing at the second or third.

The Biggest AI Implementation Barriers

The Federal Reserve survey asked AI-using businesses about their main challenges.

Accuracy ranked first among nonemployer respondents, followed by adapting tools to business needs.

Source: Federal Reserve Banks, 2026 Nonemployer Chartbook, page 62. Respondents could select multiple challenges.

Accuracy and Reliability

A solopreneur may be responsible for researching, drafting, reviewing, and delivering the same project.

AI-generated errors can therefore move directly into work presented to customers if the owner does not verify the output.

Risky areas include:

• Financial calculations.
• Contract language.
• Advertising and earnings claims.
• Research presented as factual.
• Technical specifications.
• Product descriptions.
• Customer refunds and payment instructions.

The National Institute of Standards and Technology’s Generative AI Profile provides a voluntary framework for identifying and managing generative AI risks.

For an independent owner, useful controls include original-source checks, approval requirements, testing unusual inputs, and tracking recurring errors.

Adapting AI to Existing Workflows

Among surveyed nonemployer AI users, 39% reported difficulty adapting tools to their business needs.

An AI application may produce a useful summary but still fail to connect with the owner’s customer records, scheduling system, bookkeeping process, or approval requirements.

Adding integrations can also introduce more work.

Connections need permissions, maintenance, testing, and occasional repairs.

A process that requires more troubleshooting than the manual task it replaces may not justify automation.

Privacy and Customer Information

Data-security and privacy concerns were reported by 28% of nonemployer AI users.

Before connecting customer information to an AI application, owners should determine:

• What information is shared with the provider.
• How the information is stored and retained.
• Who can access connected records.
• Whether data may be used to improve the provider’s models.
• How connected permissions can be revoked.
• Whether the application meets applicable confidentiality and privacy obligations.

Risk increases when an AI system can take actions rather than merely prepare drafts.

Approval requirements should reflect the possible consequences of an error.

These concerns sit alongside the broader operational challenges of running a one-person business in the United States, where one owner must coordinate financial, technical, customer, and administrative responsibilities.

Not Every Business Plans to Use AI

The Federal Reserve survey also examined nonemployer businesses that did not plan to adopt AI.

Among those respondents:

• 52% said AI was not applicable to their business.
• 35% preferred not to use it.
• 21% identified accuracy concerns.
• 21% cited ethical or social concerns.
• 20% identified privacy concerns.

These figures describe nonusers with no plans to adopt, not the entire nonemployer sample.

Some business owners may lack relevant applications. Others may prefer existing working methods or judge the risks and expenses too high.

The Federal Reserve data do not establish how many would benefit from changing their decision.

How to Measure AI Return on Investment in a One-Person Business

AI return on investment requires more than comparing subscription prices.

The complete cost includes the work necessary to introduce, supervise, and maintain the process.

A useful evaluation considers:

• Direct software costs: Subscriptions, API use, connectors, and usage charges.
• Implementation: Initial setup, workflow design, testing, and training.
• Human review: Time spent checking outputs and correcting mistakes.
• Maintenance: Broken connections, changing instructions, and process updates.
• Verified benefits: Net time saved, expenses avoided, or additional contribution from completed business.

Be careful not to count the same benefit twice.

If time saved is already valued through additional completed sales, adding the full monetary value of that time to the sales contribution may exaggerate the return.

Example AI ROI Worksheet

The following is a hypothetical monthly calculation. It illustrates the method and does not represent an actual company’s results.

In this example, AI reduces execution time by four hours, but review, maintenance, and allocated setup work consume part of the benefit.

The estimated result is $37.50 in net monthly time value after the software expense.

That is not automatically $37.50 in additional accounting profit.

If the owner does not use the recovered time to reduce expenses, complete paid work, or create another economic benefit, the gain may be increased capacity rather than immediate cash income.

Which AI Performance Metrics Matter?

For AI to become a measurable business investment, the improvement needs to survive after correction and operating costs are included.

How Solopreneurs Can Move From Experimentation to Integration

The Federal Reserve’s integration figures show that most nonemployer AI users are still experimenting or working with partially integrated systems.

Moving beyond experimentation does not require automating the entire business.

A practical approach is to improve one process, measure it, and expand only when the results justify doing so.

1. Identify a Specific Business Problem

Begin with a process that already consumes time or creates errors.

Possible examples include:

• Preparing client proposals.
• Responding to routine inquiries.
• Organizing customer feedback.
• Drafting invoices.
• Preparing project reports.
• Updating customer records.

A narrow process is easier to evaluate than a general goal such as automating the entire business.

2. Record the Current Performance

Before introducing AI, measure:

• Average task completion time.
• Frequency of the task.
• Number of errors or revisions.
• Existing outsourcing costs.
• Customer delays.
• Completed outcomes.

Without a baseline, the owner may be unable to determine whether the new approach is actually better.

3. Separate Rules From Judgment

A fixed rule might classify an inquiry based on a selected service type.

An AI action might summarize the customer’s request.

A human decision might determine the price or scope of the project.

These should not be treated as equivalent responsibilities.

4. Test With Realistic Inputs

Test the process using representative information, including problem cases.

• Missing fields.
• Duplicate customer submissions.
• Unusual requests.
• Long or unclear messages.
• Incorrect source information.
• Tasks outside the business’s normal service offering.

Decide what should happen if the system fails or cannot complete the work safely.

5. Keep Approval Where It Matters

Initially, have AI prepare drafts, suggestions, or summaries for review.

Only consider allowing automatic actions after the business has tested the process and defined its limits.

Financial transactions, customer promises, legal commitments, and sensitive decisions deserve stronger controls.

6. Measure and Maintain the Process

Compare the results with the baseline.

Track net time saved, error rates, owner interventions, software costs, and the intended business outcome.

Review the workflow when the business changes its services, policies, applications, or customer process.

Worked Example: AI-Assisted Client Intake

A solo consultant can connect a basic inquiry form with an AI-generated summary and an email draft.

For example, supported applications such as Google Forms, Zapier, and Gmail can be combined with an AI service to create a reviewable intake process.

1. Collect the inquiry. Ask for the service requested, project description, business email, and preferred contact method.
2. Receive a new submission. A connected workflow is triggered by the form response.
3. Prepare a summary. AI summarizes the request and identifies missing information.
4. Create a response draft. A Gmail draft acknowledges the inquiry without promising pricing or availability.
5. Require review. The owner checks the request and approves the response before sending.
6. Measure the outcome. Track response time, corrections, missed inquiries, software charges, and follow-up work.

This is a supported workflow pattern, not a claim that a named company achieved particular savings.

A connected multi-step process may require paid automation features and separately billed API use. A regular AI chat subscription should not be assumed to cover automation API charges.

The first version should produce drafts rather than automatically sending customer commitments.

Legal and Commercial Responsibilities Still Apply

AI-generated output does not remove a business owner’s responsibility for published claims, customer information, intellectual property, or contractual obligations.

Advertising and Customer Claims

In September 2024, the Federal Trade Commission announced Operation AI Comply, targeting allegedly deceptive AI-related claims and practices.

The actions addressed issues including fake reviews, misleading legal-service claims, and promises involving automated online-business earnings.

Practical precautions include:

• Substantiating advertised performance and earnings claims.
• Checking generated product and service descriptions.
• Avoiding fabricated reviews or testimonials.
• Not representing automated work as professionally reviewed when it has not been.
• Checking applicable advertising and consumer-protection requirements.

Copyright and Creative Work

The U.S. Copyright Office explained in January 2025 that AI-assisted work may qualify for copyright protection when sufficient human-authored expression is present.

Merely writing prompts generally does not establish copyrightable authorship of the resulting machine-generated expression.

AI assistance does not automatically prevent protection either. Original human expression, creative arrangements, and modifications may matter.

Solopreneurs who sell AI-assisted creative deliverables should accurately document their contributions and avoid promising rights they cannot establish.

Business Software and Tax Treatment

Business software and technology expenses may qualify for deductions under applicable tax rules, depending on the nature of the expense and the owner’s circumstances.

The IRS Schedule C instructions provide guidance relevant to business expense reporting.

A deductible expense still requires cash to purchase.

Tax treatment should therefore remain separate from the operational question of whether AI delivers enough value to justify its cost.

Where America’s Nonemployer Businesses Are Concentrated

Geographic Census data add context about where independent business activity is concentrated.

Using the Census Bureau’s Vintage 2025 estimates for the July 1, 2024 population, the United States had approximately 94.1 nonemployer establishments per 1,000 residents.

Florida had the highest state-level concentration, at 147.3 establishments per 1,000 residents.

West Virginia had the lowest, at 55.1.

California had the largest absolute count, followed by Florida and Texas.

Sources: Census Bureau, 2024 Nonemployer Statistics; Census Vintage 2025 state population estimates; and the published state-level calculation. Rates and averages are derived figures. States are selected for illustration, not presented as a complete ranking.

California, Florida, and Texas together accounted for approximately 10.43 million nonemployer establishments, representing 32.6% of the national total.

But absolute counts and population-adjusted rates answer different questions.

• Establishment counts describe the size of a regional business population.
• Establishments per 1,000 residents measure the prevalence of nonemployer activity relative to population.
• Average gross receipts describe total receipts divided by establishments, not personal earnings or profit.

None of these measures establishes state AI adoption rates.

Major Urban Counties

County-level statistics provide a closer view of nonemployer activity around major cities.

Source: U.S. Census Bureau QuickFacts, 2024 nonemployer establishment counts. Counties are selected for illustration and do not represent a national top-six ranking.

These figures describe county boundaries rather than entire metropolitan areas or municipalities.

For example, New York County covers Manhattan, not all five boroughs of New York City.

Geographic counts can inform market research and business-support planning, but they cannot identify which states or cities have achieved the greatest financial benefits from AI.

What Could the Solopreneur Economy Look Like Through 2028?

The Census Bureau recorded establishment growth of 5.12% and nominal gross-receipts growth of 6.18% between 2023 and 2024.

Those are historical measurements, not forecasts.

To illustrate how continued growth at those rates would affect the nonemployer economy, the Solopreneurs Research & Analytics Team calculated conditional scenarios from the 2024 baseline.

One scenario holds the establishment count constant. Another repeats the observed annual establishment growth rate. A separate calculation repeats the nominal receipts growth rate.

Source: Solopreneurs Research & Analytics Team calculations using Census Bureau 2023 and 2024 establishment and receipts totals. These are mechanical scenarios, not predictions or government forecasts. Receipts are nominal and not adjusted for inflation.

If the observed establishment growth rate repeated every year, the modeled total would reach approximately 39.06 million establishments in 2028.

Nominal gross receipts would reach approximately $2.37 trillion under the corresponding receipts scenario.

Neither calculation estimates AI-generated economic value.

The models do not account for inflation, business closures, changes in industry composition, shifts between employer and nonemployer status, or future economic conditions.

More establishments and larger aggregate receipts would not necessarily establish that the typical owner is financially better off.

The available research does not support a credible national projection of solopreneur profit growth attributable to AI through 2028.

What the Research Means for Solopreneurs

The findings point to several practical conclusions for independent business owners.

1. Treat Adoption and Integration as Separate Stages

Trying AI for individual tasks can be useful without requiring extensive implementation.

Integration becomes more valuable when the task repeats, the workflow is reliable, and the owner can measure a meaningful improvement.

2. Begin With the Business Constraint

A business struggling to find customers may need a stronger offer or better distribution rather than more automatically generated content.

A business losing hours to administrative work may benefit from organizing repetitive processes.

The constraint should determine the approach.

3. Do Not Assume AI Eliminates the Need for People

AI can prepare information and support execution.

Some work still requires a virtual assistant, experienced freelancer, specialist, employee, or business partner.

The decision depends on responsibility, quality, cost, and the completed result.

4. Measure Net Productivity

Include time spent checking outputs, correcting mistakes, maintaining applications, and handling exceptions.

Faster first drafts do not automatically translate into more completed work.

5. Protect Business and Customer Information

Evaluate permissions, data handling, and vendor policies before connecting confidential records to AI systems.

Require human approval when errors could affect customers, finances, contractual obligations, or legal rights.

6. Recognize That Full Integration Is Not Always Necessary

An independent contractor, local service operator, creative professional, and software founder may need very different levels of automation.

The appropriate level depends on the economic value of the workflow, not how advanced the technology appears.

Methodology and Research Limitations

This report combines federal administrative business data, business surveys, original academic research, current regulatory publications, reported founder accounts, and independently calculated comparisons.

Business Population

The Census Bureau’s 2024 Nonemployer Statistics, released September 29, 2026, supplied national establishment counts, receipts, legal forms, receipts-size classes, industries, and geographic totals.

The 2023 Nonemployer Statistics supplied the prior-year baseline.

Nonemployer Statistics are derived primarily from federal business income-tax records.

These establishments are not identical to unique full-time solopreneurs, and receipts are not equivalent to net income.

AI Adoption and Business Conditions

The Federal Reserve Banks’ 2026 Nonemployer Chartbook used the 2025 Small Business Credit Survey, conducted from September through November 2025.

The survey included 5,027 nonemployer respondents and 6,525 employer respondents.

The optional AI-use question received answers from 4,013 nonemployer respondents and 5,248 employer respondents. Conditional follow-up questions had smaller respondent counts.

The survey uses weighting but is not a random probability sample. Results are subject to the limitations of convenience-sample methodology.

The AI definition included stand-alone applications and AI capabilities embedded in other software.

Additional AI Research

The FreshBooks survey was conducted by Wakefield Research among 500 solopreneurs and microbusiness owners from June 22 through July 1, 2026.

The Network Solutions survey was conducted in September 2026 among 187 U.S. small-business owners who already used AI. Of those respondents, 57% were solo operators.

The Census Bureau’s March 2026 Household Trends and Outlook Pulse Survey supplied worker-reported AI time-savings information. Its findings are not specific to solopreneurs.

The OECD’s April 2026 research examined AI use and digital maturity among a non-representative sample of more than 2,000 SMEs across 12 OECD countries. It found that off-the-shelf AI adoption was increasing while strategic integration remained uneven.

The Management Science field experiment in Kenya supplied randomized evidence about the effects of AI business advice on entrepreneurial performance. Its findings should not be generalized automatically to U.S. solopreneurs.

Founder cases from The Wall Street Journal and Business Insider are reported accounts rather than independently audited financial case studies.

Calculated Measures

The following formulas were used for derived figures:

• Annual establishment growth: (2024 establishments ÷ 2023 establishments − 1) × 100.
• Nominal receipts growth: (2024 receipts ÷ 2023 receipts − 1) × 100.
• Average gross receipts: Total receipts ÷ establishments.
• Receipts-bracket share: Establishments in bracket ÷ national total × 100.
• Establishments per 1,000 residents: Establishments ÷ population × 1,000.
• Conditional future value: 2024 baseline × (1 + observed annual growth rate) raised to the number of years after 2024.

The geographic calculations used the Census Bureau’s Vintage 2025 estimates for July 1, 2024 population.

The 2028 figures are conditional arithmetic scenarios, not forecasts of business formation, future receipts, or AI-related growth.

Evidence Limitations

• Census establishment counts do not identify a unique population of full-time business owners.
• The Federal Reserve survey and Census administrative datasets cover different business populations and measurement periods.
• The Federal Reserve survey cannot establish the exact national share of nonemployer establishments using AI.
• Self-reported time savings are not equivalent to independently measured productivity gains.
• Time savings do not automatically create additional revenue or profit.
• Survey associations do not establish causation.
• Reported founder revenue does not establish profitability or the share attributable to AI.
• The examined research does not establish state-by-state AI adoption rankings for U.S. nonemployer establishments.
• The available national datasets do not verify a causal AI-related increase in solopreneur profits.

The Next Stage of Solopreneur AI Adoption

America’s nonemployer economy now includes almost 32 million establishments generating more than $1.8 trillion in annual gross receipts.

Artificial intelligence is already becoming part of how many independent owners research, create, plan, communicate, and operate their businesses.

The Federal Reserve’s 2025 survey found substantial AI use, especially in writing, marketing, and analysis. It also found that relatively few nonemployer AI users considered the technology fully integrated into their operations.

Other research provides evidence of time savings and new business capabilities, alongside implementation costs, accuracy concerns, and uneven commercial outcomes.

For solopreneurs, the next opportunity is to identify where AI changes the actual performance of the business.

That might mean reducing administrative work, improving customer response times, expanding service capacity, or freeing time for work that generates revenue.

The evidence needed is practical: completed tasks, verified time savings, reduced errors, lower expenses, more paying customers, and financial results that justify the investment.

AI adoption tells us how many businesses are using the technology. Measurable business outcomes will tell us how much it is changing the economics of working for yourself.