Do small businesses need AI?
Small to medium-sized businesses don’t need their employees to be AI experts. The better, more practical angle is that they need small, practical AI skills. These skills don’t all need to be with every individual. Instead, they should be spread across your team. AI skills such as prompt writing, output-checking, tool orchestration, and more.
So let’s get our bearings for a second before continuing with the rest of the article: you’re here because you’re not new to AI. You’ve already adapted it, like they’ve all been saying. “They,” being tech giants, industry influencers, big media (hardly trustworthy, but yes, in this situation), and business and thought leaders.
Thryv’s 2026 AI and Small Business Adoption Survey stat has a line about this:
AI adoption among SMBs rose from 55% in 2025 to 66% in 2026, but 70% of SMBs say they still need more AI training.
As a business owner or leader, you’re here because you want to know more about AI for small businesses.
You’re asking which of your team members need AI training for which skills or tools. You’re also asking what the tell is – for AI skills that can be nurtured in-house, and which ones require that you seek out seasoned hands.
This article fills those blanks in, minus the thicket of technicalese.
In This Blog:
What AI Skills Does Your Business Need?
Before it slips past us, “AI skills” isn’t limited to coding for a chatbot or building an AI application. These are specialized technical skills. Skills that most small businesses don’t need to go that far down the road for.
What surveys say (2026 Adobe Express):
- 27% consider prompt engineering “very important” to their operations
- 36% would choose a job candidate with this skill over one without it.
It’s now becoming less niche and more mainstream. Having basic AI skills as a standard for hiring, or for upskilling.
But again, which skills? We’re about to get to it.
Here are the five artificial intelligence skills you can get your team equipped with this year:
1. Prompt writing and context setting
This is the ability to give an AI tool clear instructions, including what you want, who it’s for, and what format the output should take. Data from PE Collective shows that job postings requiring prompt-engineering skills grew roughly 3x between 2024 and 2026, even as the standalone “Prompt Engineer” job title declined by about 30% over the same period. The skill spread into other roles instead of disappearing.
2. Basic workflow automation
Movement of information is more efficiently done when tools are tuned to channel it to and from the right start and end points. Better done via automation so no one has to be typing it each time. One load you can take off the person in your team who’s been doing that.
Job listings have been less shy about including platforms like n8n, Make, and Zapier as “ideal to have but not required.” In truth, hiring specialists brush through resumes that don’t have them.
2026 hiring data from AINative shows a heading and it’s towards that outlook: it’s becoming a standard requirement.
Does your team need to be masters of all three? No. The mark to get as close as possible is knowing how to connect forms to your CRM or inboxes to task lists.
3. Verifying/checking output
Checking AI-generated content before it leaves the nest and reaches a customer or is used in a decision. Professional-grade tools have their error rates, too. You should never go full-AI-generated without doing a once-to-thrice-over.
Real-life example:
Stanford RegLab and Stanford HAI research found legal AI tools producing incorrect information between 17% and 33% of the time (depending on the tool and the type of question asked).
That’s specialized software. It’s more than a casual or plug-and-play tool, and yet it still gets things wrong. AI tools used across marketing, customer service, and admin work need someone keeping watch.
4. Recognizing when a human needs to step in
The bit about someone keeping watch isn’t something that’s needed all the time. There are instances when AI outputs are good to go after the first run. Nevertheless, there are cases where more than catching an error is imperative.
There was an incident concerning Air Canada when, in 2024, their tribunal ruling held the airline responsible after its customer service chatbot gave a passenger inaccurate refund information.
A tribunal rejected the airline’s argument that the chatbot should be treated as a separate party; the implication is that businesses, in any industry, remain accountable for how their AI tools operate. And how those same tools affect the people they work with.
5. Understanding how your tools connect
As you add more AI-powered software, the more tracking reveals itself an obvious necessity. Someone has to do it on repeat, on the usual. Someone has to mind the machinery. Or in this case, the map of the whole system.
One of the skills becoming a required skill in many industries: data literacy (Gartner, 2026 data and analytics predictions).
These five skills cover what a general employee can reasonably learn and apply. Where the work goes deeper – ongoing platform monitoring, multi-system integration, building automations that run without daily supervision – is where training stops being enough.
That’s covered next.
What Is Human In The Loop? (HITL)
Key takeaway//Quick Answer
Human-in-the-loop (HITL) is an approach where people remain involved in an AI system’s process, reviewing, correcting, or approving its outputs before important decisions or actions are taken. It combines AI’s speed and scale with human judgment, particularly when accuracy, context, or accountability matters. In a business setting, HITL might mean having an employee check an AI-generated customer response before it is sent.
Why is Human in the Loop important?
Because of another budding phrase: “set-it-and-forget-it.” The thing that the “human in the loop” helps prevent when it comes to AI software for small businesses. The human, someone on your team, checks what AI produces each time, catching mistakes and filling in missing or misaligned context. They step in when a human decision is in the offing.
Is human-in-the-loop basically reviewing things? Double-checking? From a broad perspective, yes. It’s actually about knowing which work can be left to AI, and which work cannot be left there.
The Hybrid Workflow That Works for Small to Medium Businesses
Employees are willing, but they’re also struggling to find the balance between doing the work they’re actually skilled to do (their title and job description) and adding regular, just-as-consistent AI-related operations to their work.
Splitting the AI skills training among the rest of your teams? That’ll work for now, and for a while. But you’ll have to think of a more efficient solution once business picks up and grows, and workflows with it.
SMBs who’ve thought this through earlier than most are going “hybrid.” They’re bringing in AI specialists, but not in the usual, conventional manner. This, too, we’ll get to in the next section.
The Real Decision: Teach Your Team vs Hire the Specialist
Once you’ve sorted through the AI solutions for small business (and specifically yours), it’s only right to think about two things:
Hire a local AI specialist or work with someone remote.
Two more things: Some tasks need a dedicated specialist, while others don’t.
Why a Local AI Hire Is Hard to Justify Right Now
Average AI Automation Specialist salaries in the United States is $76,465 per year, according to ZipRecruiter’s 2026 salary data. $57,000 and $98,500 in its typical range. The top earners, the senior or experienced roles, get $110,500 and above.
Then benefits and payroll taxes. Then onboarding and other company-related perks.
You know what your budget can take, and for a lot of businesses, the cost ruins all calculations and planning.
The scenario from earlier about existing employees absorbing the work (as an extra part-time responsibility)? It’s happening, and it explains why so many AI workflows in small businesses aren’t properly maintained.
The overloaded employees aren’t the problem here.
What a Dedicated Specialist Solves That Training Doesn’t
Here’s what training usually covers:
- Prompt writing
- Basic automation
- Verification habits
Here’s what training doesn’t cover:
- Someone watching your automations daily
- Catching a broken integration before it causes a week of panic over bad data
- Configuring a platform correctly the first time so you can cross troubleshooting of your team’s list for good
It’s specialized work.
Now, according to 2026 job listing data, outsourcing AI specialists from countries like the Philippines equates to a monthly salary range of $1,391 to $1,739. That’s a fraction of the loaded cost of a US-based hire, for comparable ongoing platform ownership.
What You Can Do Now: Train your team, or have them trained, on the five skills mentioned two sections before (you can also refer to the table). This will help them use AI tools more adeptly for the day-to-day operations.
Hire a specialist once the work starts involving connecting and managing systems, and fixing issues across several platforms.
How to Use AI for Small Businesses and Startups: Your 4-Step Rollout Plan
Step 1: Audit for repetitive areas where work gets stuck
Look at what your team does every week that follows the same steps with the same inputs. Data entry, appointment confirmations, invoice processing, routine follow-up emails. All candidates for AI support.
Tasks that require context unraveling and human decisions are your team’s to take charge of.
Step 2: Build Your AI Tool Stack
It’s easy to collect AI tools. Faster, too, than your team can learn them. Give everyone five new platforms, and you may end up with five half-used subscriptions.
Keep the first version of your stack small, and choose the tool that best handles each immediate need: content, scheduling, data entry. Or whatever came out of your audit. Let your employees get familiar with those tools before you start connecting them.
Once people know what each AI tool is doing on its own, you’ll have a much clearer idea of where connecting them could save time.
Step 3: Write Down the Process Before You Automate It
Before anyone builds an automation, document what happens now. Include the small details your team handles without thinking about them.
What information comes in, where it goes, who checks it, what happens when something is missing, and what happens when the usual process takes a different turn.
It’s extra work at first, but will save plenty of confusion in the long run. A specialist can build from a documented process, and your employees have something to refer back to when an automation needs checking or changing.
Step 4: Decide What Your Team Should Handle
Go through your audit and sort the work according to the level of AI knowledge it requires. An employee who has learned prompt writing, output verification, and basic automation can take care of plenty of everyday AI tasks.
More involved work belongs in a different category. If an automation needs to run across several platforms, requires regular monitoring, or keeps needing technical fixes, you’re dealing with specialist work.
Related Read: Learn about where and how tech is entering industries and why SMBs are adapting to the changes fast. A breakdown of What is a Marketing Automation Specialist and No Code Development for US Businesses.
How Remote Staff Fits Into This
For some small businesses, the next step is bringing in someone who can take care of the technical side and answer “how to use AI” every day, while the rest of the team gets on with their regular work.
Remote Staff has AI automation specialists among its remote talent pool, with experience across areas such as workflow automation, prompt engineering, API integration, and AI systems.
The company screens for hands-on experience with the platforms candidates will actually be working with, which is particularly useful when you need someone to work inside your existing setup.
There’s also room to match the arrangement to the workload. Depending on what the business needs, that can mean full-time, part-time, or project-based support.
For a small business still figuring out its AI setup, that flexibility can make the specialist route easier to consider.
FAQs
Do small business owners actually need to learn AI skills, or can they just hire someone?
Some knowledge still needs to stay with the people using AI every day. The U.S. Chamber of Commerce reported in 2026 that more than 75% of small business owners use AI, yet only 14% have fully integrated it into their core operations. More than 70% also said additional AI training would help. Owners don’t need to become AI specialists. They do need enough understanding to make sensible decisions about how their employees use these tools and when outside expertise is needed.
What AI skills do employees need to learn first?
Start with the skills that apply to ordinary work: writing useful prompts, checking AI-generated information, and handling simple workflow automation. Prompt engineering is already being treated as a useful workplace skill. Adobe Express found that 36% of small business owners were more likely to hire a candidate with prompt-engineering skills. Those basics give employees a practical foundation before more technical AI work enters the picture.
Is it cheaper to train my team or hire an AI specialist?
For everyday AI use, training is usually the more sensible place to begin. Employees can learn prompting, verification, and simple automation without adding a specialist salary to the payroll. Building and maintaining connected systems is what requires hiring an AI specialist. ZipRecruiter listed the average U.S. salary for an AI Automation Specialist: $76,465. The range runs from $57,000 to $98,500.
Can AI mistakes made by my business create legal liability?
They can. However, it’s a useful reminder that putting an AI tool in front of customers does not remove the business’s responsibility for what that tool tells them.
Does training my team on AI create a retention risk?
One UK study found an interesting trade-off. EY’s 2025 Work Reimagined research reported that employees who received more than 81 hours of AI training in a year were 59% more likely to move on from their current employer, while also reporting an average productivity boost of 14 hours per week. That’s a reason to think about how AI knowledge is shared. Keep processes documented and make sure important know-how belongs to the business as a whole.
What’s the difference between an AI assistant and hiring an AI specialist?
Think of an AI assistant as something an employee uses to get a job done. ChatGPT, for example, can help someone draft an email, summarise a document, organise information, or work through a first draft. An AI specialist works on the machinery around those tools. They can build automations, connect platforms, configure workflows, and deal with problems when those systems need attention. A business may need the first every day and only need the second once its AI use becomes more involved.
Extra Read: Something’s happening in cybersecurity. Breaches are escalating like never before. Go through this Cybersecurity Data Breach Legal Guide and why SMBs should aim for prevention than cure.
AI Solutions for Small Businesses Are Two-Way
AI has already made its way into a lot of small businesses. The harder part for many owners is working out what should happen next. Employees need enough AI knowledge to use these tools properly, while more technical work may call for someone who spends their working day building and maintaining AI systems.
There’s no prize for giving everyone every AI skill. Teach your team what helps them do their existing jobs better. Keep the processes clear. When the work starts reaching across several platforms or needs someone watching the systems behind it, bring in the expertise that work calls for.
That’s a much more practical way to build AI into a small business, and a lot easier to manage as the business grows.
Ready to work out which AI skills your business needs? Talk to Remote Staff today and Request a Callback.
Vaune Everis Cura has always been a writer in the truest sense, drawn to the art both as a personal creative pursuit and as a profession. Her experience penning content across digital marketing spaces and collaborating with business owners and market shapers has broadened her craft to include strategic direction and SEO insight. Having spent years with the InterContinental Hotels Group before stepping boldly into freelancing, she understands that at the centre of it all are genuine, meaningful brand–customer relationships built on purposeful, human content.
