What AI Means to Small Businesses

Mauri says the number one action small-business owners should take is to experiment with AI alongside humans. "Hack Future Lab's research shows that using AI as a co-pilot can lead to efficiency gains of 40%, speed to insights of 33% and streamlining of workflow processes and routines," he says. When operational headwinds are strong, Mauri warns that not taking a risk is actually risky.

However, small businesses need a strategy for adapting to technology changes — and market shifts. Kelsey Ruger, chief product and technology officer at Hello Alice, which provides advice and capital to small businesses, says he believes AI will radically change how entrepreneurs work and build their businesses. However, instead of fixating on the technology — which is ever-changing — he suggests concentrating on finding effective strategies for leveraging AI.

Ask the Right Questions

Ruger says small-business owners need to answer three critical questions:

Automation: What aspects of your business can be automated through AI? "Identifying processes that can be efficiently automated will help with enhancing productivity and reducing costs," Ruger explains.

Augmentation: How can AI augment your current entrepreneurial activities? "Determining where AI can complement your unique skills and amplify your capabilities will help accelerate what you will be able to accomplish as an entrepreneur," Ruger says.

Autonomy: What elements of your business should remain under your personal control? "Recognizing areas where the human touch adds intrinsic value or where your expertise outperforms machine capabilities will be crucial in the proper application of AI," Ruger says.

By addressing these questions, he says you can not only leverage AI effectively in the short term, but incorporate it throughout your business in the long term.

AI can improve a small business in a variety of ways. Sameer Maskey, founder and CEO of Fusemachines in Long Island, New York says it can be a transformative force across industries, and can automate functions, improve precision and enhance processes and decision-making.

"Automation facilitated by AI involves taking various inputs and making a series of decisions that can help in automating tasks or streamlining workflows from end to end or in parts," he explains. Examples include predicting manufacturing defects, automatically removing substandard parts from production lines or managing the entire customer-service journey.

Prediction, which is a fundamental AI capability, can also provide benefits. "It enables small businesses to anticipate sales, demand and customer behavior, optimizing strategies and resource allocation," Maskey says. As an example, he points to predictive maintenance, which can help small manufacturers anticipate equipment failure. That allows people to replace worn or failing parts before they break, which reduces downtime and costs.

Precision is another area that can be significantly improved by implementing AI. "Precision, empowered by AI, ensures accurate identification of defects, precise responses in customer service and targeted marketing campaigns tailored to individual preferences," Maskey says. That improves efficiency and enhances user experiences across the board.

When these facets are interconnected, Maskey says AI could revolutionize operations and enable organizations to adapt, innovate and thrive in dynamic market landscapes.

Many small businesses are still uncertain if they can achieve the same AI results as big companies. Eric Siegel, a machine learning consultant and author of "The AI Playbook: Mastering the Rare Art of Machine Learning Deployment," says that they can, starting by tapping into the power of enterprise machine learning (predictive AI). The differences between big and small AI users are in the size of the operation and the amount of data accumulated.

For example, he says, if a small organization sends an annual holiday direct-mail greeting to half a million prospects, AI can accumulate digital knowledge by "learning" which customers respond to the contact. "Machine learning taps that data to better target next year's mailing, potentially skyrocketing the bottom line," Siegel says. This, he adds, is an example of how the size of a data pool — not the size of business — determines the opportunity.

AI also can help a small business anticipate change. "It's about improving efficiency, which translates into profit — and, depending on current priorities and strategy, its deployment can be tuned, more specifically, to focus on cost savings or, alternatively, on increased returns," Siegel says.

There are many micro-decisions in business operations, such as whom to contact, where to investigate and what to approve. Siegel says it is easy to be wrong in any of these areas. "Transactions turn out to be fraudulent, cardholders default and customers fail to buy — because business is a numbers game," he says. However, Siegel adds that machine learning turns prediction into a capability. "It's the holy grail for playing that game more effectively, tipping the odds in the business' favor," he concludes.

Talent management is an important component of any company, but especially for small businesses where every hire is critical to the company's success. Maskey points to AI applications in the talent-management cycle, ranging from recruitment to talent retention.

Improve Recruitment: Businesses can use AI tools to augment the recruitment process by scanning resumes and then comparing each applicants' skills and capabilities with a job description.

Anticipate Hiring: AI also can review employee and department data to look for patterns of turnover, enabling businesses to proactively implement hiring or retention strategies.

Retain Talent: AI can identify commonalities and trends in data derived from sentiment analysis surveys, suggesting initiatives to boost employee morale and help organizations identify activities that foster a strong work culture.

According to the most recent report by the U.S. Chamber of Commerce, 52% of small businesses identify inflation as their biggest challenge, followed by revenue (29%). AI can help small companies make more-informed financial decisions. Using predictive analytics and automation, Maskey says that, with AI, small businesses can curb organizational spending and drive sales growth, all while expanding their customer base.

"By harnessing AI's predictive capabilities, businesses can accurately forecast sales trends, anticipate customer demand, and optimize inventory levels, thus minimizing overstocking or stockouts, and reducing associated costs," he explains.

Also, Maskey points to automation as a way to streamline processes, and identify and address any defects occurring during the manufacturing process — which in turn, helps to mitigate waste and lower production costs. "Additionally, AI-driven automation streamlines the end-to-end customer service journey, predicting user needs and preferences to offer efficient and personalized support, ultimately enhancing customer satisfaction and retention," he says.

When small businesses integrate predictive analytics and automation, they can make data-driven decisions, optimize resource allocation and foster sustainable growth while effectively managing expenditures. And Maskey says all of these components can help small businesses be more successful.

If you're thinking about taking the plunge with AI, it can be easier and more effective to start with certain areas first. Keep in mind that data forms the foundation on which AI rests. As such, Maskey recommends starting in data-heavy departments. "HR, finance and logistics — it's easier to access a host of data, train algorithms on those datasets and extract valuable insights," he explains. And the datasets can be historical, transactional or behavioral, Maskey adds.

For example:

• In finance, AI algorithms can analyze historical financial data to predict future budgets with greater accuracy.

• In HR, AI-powered tools can streamline payroll processes by automating tasks such as time tracking and payroll calculations, reducing errors and improving efficiency.

• In logistics, AI can optimize inventory such as laptops based on data on the types of devices used across departments, how many devices are used, predicted talent churn and anticipated new hires.