Bringing solopreneurs up to speed with AI

The solopreneur has always operated at a disadvantage when it comes to managing his/her business. But technology is evolving to level the playing field for lone workers and small business owners.

Videoconferencing, collaborative applications, software-as-a-service offerings and other enabling tools are doing their part to help staff-less operations keep pace. The next iteration is the application of artificial intelligence and machine learning.

Roy Pereira, CEO, Zoom.ai

Roy Pereira, CEO of Zoom.ai, a Toronto-based startup that has developed an AI-enhanced digital personal assistant, says the current interest in machine learning is no surprise. “Almost every tech company is getting into it or should be. The reason is that AI gives businesses insight to users that they wouldn’t normally have access to.”

Zoom.ai uses AI on the back end to automate frequent, lower level tasks such as calendaring, travel arrangements, initiating outreach to customers and sourcing contacts to help small businesses and solopreneurs run more effectively.

Through the new machine learning wave, end users will not even be aware of technology change since much of the machine learning work being done is on existing platforms. Microsoft, Intuit, Google, Salesforce and others are gradually layering on machine learning to create a world in which a business need is met before an end user even has to ask, Pereira said.

“The interesting thing about machine learning is that it won’t be something the user will see,” he added. “They won’t know it’s happening. All of a sudden they will get information delivered and shown to them and simply wonder how the solution figured it out.”

He likened the surprise element to the first time an iPhone tells you at 5:00 it will take 30 minutes to get home. “How did it know you were leaving right now? Because you always do. The best part is that machine learning gets better over time and very quickly.”

This rapid improvement is not an unfamiliar trajectory. Cloud and mobile have both contributed to the solopreneur’s ability to conduct business at an elevated level. “Cloud was really interesting for the small business owner who couldn’t afford to install and maintain software or hire an IT staff person,” Pereira said. “With a cloud solution you don’t’ have to install anything. You just pull out your credit card and you can change how you work.”

There are two reasons why this latest AI evolution is gaining traction, Pereira explained. “One is that machine learning technology has improved greatly. Secondly, companies have been amassing huge amounts of data. Even the smallest company’s information – every event, every keystroke – is stored in the cloud and becomes a data point. And the one thing machine learning loves is data. Now you can throw machine learning algorithms out there and get insight into what you have been doing all along.”

Given that the solopreneur is rapidly becoming a sizeable force, new levels of support are especially timely. This past December, Intuit released a Canadian study in partnership with Emergent Research, The Rise of the Self-Employed Economy, examining new patterns of entrepreneurial operation in a new economy. It found that full and part-time freelancers, independent contractors and on-demand workers are expected to make up 45 percent of the workforce by 2020. The reasons for the shift range from a desire for greater work-life flexibility (47 percent of respondents), to a desire to supplement salaried income (41 percent), to a desire to work during retirement (19 percent).

Sasan Goodzari, EVP and GM, Intuit Small Business Group

Self-employed workers and small businesses globally represent the largest drivers of the economy, said Sasan Goodzari, executive vice president and general manager of Intuit's Small Business Group. Intuit’s goal in applying machine learning to its existing financial platform is to “bring the power of all the apps they would ever need to have access to at their fingertips. Whether it’s PayPal, Square, or CRM in conjunction with the apps we develop, we can help users focus on running their business by doing everything in the background.”

Some examples of how Intuit’s application of machine learning can improve efficiencies include:

  • Loan applications: Based on available data, machine learning algorithms can gauge the health of a business and provide insight within minutes into its customers, including who they are, if they pay on time and their credit rating. This allows approvals to be processed within minutes versus weeks, as well as improve the odds of success. (Currently 70 percent of loan applications are declined, Goodzari said.) “The power lies in the fact that machine learning knows about the business and the customers around them.”
  • Categorization of deductions: Once it has learned your patterns, machine learning can automatically categorize business or personal expenses, such as mileage based on the routes you take.
  • Pricing: “It can be challenging for solopreneurs to know if the prices they pay are right,” Goodzari said. Applying machine learning benefits users in helping them understand what others are paying in their markets so they can better compete or manage costs.

These additions will all take place over time and with little fanfare, Goodzari said. “It’s less about big launches. It’s about working on a monthly basis. As algorithms get stronger, the machine learning gets stronger. The beauty of machine learning is that it can be improved upon every day.”

1 COMMENT

  1. It will be interesting to see how AI can and will benefit those persons who have irregular patterns of thought, feeling, and behavior. Even these irregular patterns have patterns AI could easily recognize, modify, strengthen, or eliminate-BASED ON USER PREFERENCE.

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