Is it any wonder that artificial intelligence remains controversial? After all, consumers are still complaining about self-checkout machines in retail a good 20 years after their inception – and that’s a technology most laypeople understand.

When it comes to true artificial intelligence, even experts are sketchy on the full impact of the technology. How will it impact the job market, and what are the dangers of all that shared data? A significant 37 percent of experts surveyed by the Pew Research Center in 2018 still said they believe people will not be better off from AI-related technology by 2030.

“Without significant changes in our political economy and data governance regimes [AI] is likely to create greater economic inequalities, more surveillance and more programmed and non-human-centric interactions,” Institute for the Future Executive Director Marina Gorbis told Pew in response to the survey, “Artificial Intelligence and the Future of Humans.”

The Covid-19 epidemic might help quash some mistrust of AI, however. Scientists can do so much more than mathematically plot the expected spread of a disease. Thanks to AI, computing power can be used to account for compiled data of such variables as people’s actual movements in areas of dense population, creating enhanced progression forecasts. AI has also been utilised in the rapid development of new antiviral drugs and vaccines, which can be created by algorithms in just 12 months compared to 4-5 years through traditional research.

Vital developments such as these only reinforce what many in the tech sphere have known for some time: Artificial intelligence is no longer technology of the future, but instead AI is the tech of the here and now. It just might not be taking the form many expect.

Famed science-fiction author Isaac Asimov might have explored the world of AI through his depiction of robots beginning in the 1940s, but by 1950 at least one eccentric mathematician, Alan Turing, foresaw the ability to create artificial intelligence outside of a mechanical body. Turing wrote about the potential for software run on a virtual computer that could observe the environment and learn new things, whether those lessons be in mastering chess or understanding human languages.

“We may hope that machines will eventually compete with men in all purely intellectual fields,” Turing predicted in his article, “Computing Machinery and Intelligence.”

Fast-forward 70 years, and Turing’s predictions have come to life. AI now allows machines to learn from experience and perform cognitive tasks. It’s use in business is without question, whether it’s analysing data to the nth factor – making predictions that only the most gifted mathematicians previously could hope to forecast and saving countless productivity hours performing mundane tasks. The same technology that can predict hurricanes can also be used to quickly and accurately balance a budget or create a successful marketing strategy.

Still, many hesitate because they don’t fully grasp just exactly what AI means – and how it can work for them.

Simply put, AI is the ability of computers to observe, deduce, learn and assist in decision-making tasks to solve problems. These can be either problems based on data too advanced for most people to accurately analyse or problems that require productivity, time and money to complete.

So that’s what AI does, but how does it work? Large amounts of data are combined with intelligent algorithms, series of coded instructions that allows software to analyse and learn from patterns and sequences it locates within data.

People have been trying to understand algorithms since Google first began touting its superior Page Rank method of determining search engine results. How does the algorithm work? The answer transcends what the average user comprehends, and Google remains mum on the precise formula and its many updates.

Fortunately, explanations of other complex algorithms are available. HostScore, for example, explains in detail how its scoring system ranks web hosts. Its algorithms weigh factors including uptime scores, speed scores, editor’s scores and user’s scores, all based on frequently updated real-time data. It even explains exactly how each of the scores are derived and combined for a final rank.

Similar software and algorithms can complete a whole host of tasks and solve complex problems in almost any sphere, but AI is currently taking the small business world by storm. In fact, when HubSpot conducted a survey of 1,400 global consumers, it found that 63 percent of respondents were already using AI without knowing it.

Just as they embraced cloud technology to solve everyday storage and collaboration problems, small businesses frequently are relying on AI to automate mundane tasks, solve problems and boost productivity, including in the following 10 categories:

 

1.    Personal Assistants

Any small business owner can vouch that time is money, and so it’s really no surprise that more are relying on the power of AI to serve as their personal assistants, automating tasks such as emailing, text messaging, scheduling and taking notes. X.ai, for example, is a personal assistant designed for scheduling. The tool monitors the user’s schedule and availability, manages appointments and meetings, creates notifications and even responds to emails. Other virtual assistant apps complete a more extensive array of tasks. Extreme Personal Voice Assistant, for example, claims to be as helpful as Tony Stark’s JARVIS voice assistant, connecting a variety of apps while understanding and responding to questions and commands.

 

2.    Customer Relationship Management

The whole point of CRM is improving business relationships, but the recipe for doing so often remains elusive. Thanks to AI-powered software and apps, that formula is a lot easier to decipher. By using AI to analyse company and industry data, small business owners can gain vital understanding into their internal and external customers’ needs, wants and drivers. Crystal, for example, helps contact sales leads in the best possible method based on their personalities. It integrates data from LinkedIn, Salesforce, HubSpot and more sources, then evaluates anyone’s personality based on their virtual persona. It then provides personalised advice on the best way to contact, communicate with and market to each lead.

 

3.    Legal Advice

Few small businesses will ever get by without any need for legal advice, whether it’s analysing and understanding contracts, abiding by applicable laws and regulations, controlling liability or avoiding litigation. Lawyers, however, are costly – legal lawsuits alone cost U.S. companies $150 billion a year – and often not in the operating budget. Now, a variety of AI-based tools can provide needed legal advice at a fraction of the cost. Legal Robot, for example, is an AI tool that can understand complex language. It compares thousands of legal documents to create a legal language model and analyse any sort of contract. Likewise, Intraspexion relies on a deep learning platform that acts as an early-warning system that can prevent litigation.

 

4.    Cyber Security

Users have been relying on specialised software to protect their online properties and identities for decades, but now that cyber attackers are relying on AI, it only makes sense to employ it in cybersecurity efforts. Small businesses turn to platforms like Recorded Future to provide real-time threat intelligence that helps them proactively defend their entire companies against cyberattacks. Its security intelligence can accelerate detection, decision and response times thanks to a combination of machine and human analysis based on open source, dark web, technical sources and original research.

 

5.    Human Resources

Balancing human resource-related tasks with other everyday operations can be a challenge for a small business. Fortunately, AI tools now can automate much of the process. Resources like TextRecruit employ text messaging and live chats to interact with job candidates, customising the content to a company’s brand and voice. It also assists newly hired employees with onboarding tasks. Meanwhile, AI tools like Zenefits streamline and automate a variety of HR-related functions, such as payroll and benefits.

 

6.    Lead Generation

According to the Harvard Business Review, companies that rely on AI tools for sales increase their leads by more than 50 percent. Platforms like OptinMonster offer a variety of AI-based marketing and sales tools. Used by more than 1 million websites, OptinMonster has been responsible for 217 million conversions since its 2013 inception thanks to campaigns like exit-intent popup forms, scroll boxes and footer boxes. It uses AI technology to analyse factors like site visitors’ mouse gestures and velocity to determine the exact moment a user is about to leave a site, then prompts them with a targeted campaign.

7.    Customer Service

According to Oracle research, 80 percent of leaders within sales and marketing already use or plan to use chatbots on their websites. These forms of AI rely on natural language processing technology to decipher customer inquiries based on key terms. Tools like FlowXO’s chatbots employ AI to respond to common customer service requests, based on a company’s own documentation – saving valuable human productivity time for more in-depth issues. Those that also implement augmented messaging technology, such as Salesforce’s Service Cloud Einstein can even identify opportunities when a human agent should become involved. Sentiment analysis tools go a step further and identify necessary escalations based off the emotion expressed by a customer.

 

8.    Data Analysis

AI-based data collection and analysis tools can help small businesses compete with larger companies when it comes to using that data to make critical business decisions. Data collected from business systems including sales, customer service, marketing and accounting can be integrated into actionable business intelligence. Insight Squared, for example, compiles and analyses historical data from a company’s various internal systems to generate recommendations for improved sales, marketing and staffing. Likewise, IBM Cognos Analytics’ AI-powered technology can not only help small businesses visualise performance with a variety of customisable dashboards and reports, but it also helps users interpret their data, complete with actionable insights.

 

9.    Accounting

Balancing the budget is a vital aspect of any small business, but not one at which all small business owners are skilled. They can save money spent hiring an accountant thanks to AI-based technology. Companies like Xero provide accounting software that doesn’t just compile and report information, but also automates tasks like reconciliation and analysis. Even Quickbooks, which small businesses have relied on for accounting and bookkeeping software for decades, has introduced AI technology that uses predictive modeling to help companies better manage their cashflow.

 

10. Content Strategy

No matter a company’s size or industry, content remains king in terms of marketing. How many small businesses, however, have the manpower and the budget to employ a professional content strategist? Various AI-powered tools now enable small business owners to develop a successful content strategy and increase their revenue. Tools like Market Muse can analyse content and compare it to the competition, advising users how best to edit and expand upon early drafts while optimising for traffic and lead generation. Cortex, on the other hand, helps determine the best timing and channels for publishing content on platforms like Facebook, Twitter and Instagram by analysing competitors’ content and its efficiency.

It’s an exciting time for small businesses to embrace AI-powered tools. Is there a favorite you’ve already employed, or were you using an AI business tool without even realising it?