Chatbots, deep learning, neural networks, oh my! The thought of making artificial intelligence (AI) part of your small business might sound like science fiction, but AI in business looks very different from its portrayal in the movies. Artificial intelligence can give your business a competitive edge by automating tasks, interacting with customers, screening job applications, and so much more.
This primer on AI will be useful if you’re looking for ways to operate your small business more efficiently, particularly as you map out your five- or 10-year plans. Read on to learn more about this evolving technology and what its adoption might look like for you and your team.
Gartner defines artificial intelligence as technology that applies advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take action. Artificial intelligence software can be defined as software with intelligent behavior that works by reproducing abilities such as learning, reasoning, problem-solving, analyzing, and representation of useful insights.
Before delving into the ways artificial intelligence can benefit your small business, it’s important to understand the three different types of AI: Narrow AI (also known as weak AI), general AI (also known as strong AI), and superintelligent AI.
DeepAI defines narrow AI as an AI system that handles a singular or limited task. Right now, this is the type of artificial intelligence that your business would adopt. Narrow AI applications include email filtering, robotic vacuum cleaners, and Netflix’s ability to recommend shows based on your viewing history.
Amazon’s Alexa is another example of a narrow AI application. Alexa is useful when it comes to specific tasks such as turning on lights or playing music, but her abilities are limited—for instance, she can’t do both of those tasks with one command. She can order a pizza for you, but she can’t call emergency numbers since she isn’t connected to a phone line.
While terms such as narrow AI or weak AI may draw attention to those applications’ shortcomings, this sort of AI technology is still massively helpful when it comes to helping people and businesses such as yours to complete daily tasks. Next time you check to see which route will get you home from work the fastest, or use a scheduling tool to find a meeting time that works for everyone, you can thank narrow AI.
Neither general AI nor superintelligent AI is a reality yet, so they aren’t relevant to you as a small business owner. But because they tend to be what people envision when they think about artificial intelligence, we’ll provide an overview of each.
Gartner defines artificial general intelligence, also known as general AI, strong AI, or AGI, as the hypothetical intelligence of a machine that has the capacity to understand or learn any intellectual task that a human being can (full content available to Gartner clients). Through general AI, machines exhibit awareness, sentience, sapience, and consciousness, similar to the operating system in the movie “Her.”
Gartner estimates that we’re at least 10 years out from seeing any general AI applications, but research on this emerging technology is underway. The timeline is less clear for what will be the most advanced form of AI: Superintelligent AI, also known as superintelligence.
Superintelligence is defined in AI researcher Nick Bostrom’s book “Superintelligence” as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest.” This is the type of AI that is often portrayed as a havoc-wreaking robot in movies such as “The Terminator.”
With this sort of representation, it’s understandable why some are apprehensive about superintelligent AI. Inventor and futurist Ray Kurzweil offered a more positive outlook in his keynote speech for the 2019 AI for Good Global Summit, submitting that superintelligent AI will look more like a harmonious coexistence with machines rather than a takeover.
So to recap, when we talk about artificial intelligence in business, we’re referring to narrow AI and its applications, as it’s the only form of AI that your business can adopt right now. With that in mind, let’s discuss what AI adoption might look like for your small business.
AI is one of the top two tech trends that small business leaders told GetApp in our 2021 Top Technology Trends Survey* that they’re planning to adopt in the next 12 to 18 months (the other is virtual reality). It’s the future of work, and you’ll want to get on board.
Let’s discuss some ways that AI adoption can make everyday operations easier and more efficient for your small business.
According to McKinsey Global Institute, the best candidates for RPA are tasks that involve physical activities in highly structured and predictable environments, as well as the collection and processing of data:
Sewing, sorting, and assembling parts in manufacturing trades.
Filing paperwork in an office environment.
Making menu items such as salads and pizzas, and flipping burgers in fast-food restaurants.
Processing payroll in any industry.
Gartner predicts that 90% of large organizations globally will have adopted RPA in some form by 2022 as they strive to make operations more efficient. But RPA is extremely useful for small businesses as well, in that it gives you and your staff more time to focus on higher value work.
RPA uses machine learning to complete tasks faster than if they were done manually and without error, and machines don’t get tired, bored, or distracted like humans do.
Machine learning is an umbrella term for algorithms composed of many technologies (such as deep learning, neural networks, and natural language processing), used in unsupervised and supervised learning, that are guided by existing information. Examples include image recognition, speech recognition, and predictive analytics.
This doesn’t mean we’re all doomed to lose our jobs to robots. According to McKinsey, less than 5% of occupations consist of activities that are 100% automatable. Plus, people will need to continue working alongside machines to meet global demands.
Artificial intelligence can enable your business to provide better, faster, and more informed customer service. From Forbes, here are some ways businesses can leverage artificial intelligence to result in happier customers:
An AI chatbot can quickly answer customers’ most frequently asked questions.
Through deep learning, AI can study customer behavioral patterns (what they buy, when they buy, and how much they spend), and use that information to predict trends.
Through natural language processing, AI can gauge a customer’s level of frustration and speed up the response time to queries and complaints by identifying the need and displaying the necessary information to the agent. It can also manage a high volume of queries in a much shorter time.
Artificial intelligence can be used to address simple technical issues, such as resetting a password.
One particularly useful AI tool for restaurants is the ability to measure wait times.
Deep learning is a subset of machine learning that attempts to mimic the human brain, enabling systems to cluster data and make predictions. It eliminates the data labeling and processing that supervised machine learning algorithms require. One example is driverless cars, which depend on the ability to operate and make decisions based on unlabeled and unpredictable variables, such as a pedestrian in the road.
Veena Jetti, founder of Vive Funds, says it best: “The best utilization of AI is not to replace human interaction, but to enhance human interaction and decrease the friction in the customer experience.” However you choose to implement artificial intelligence to improve customer service, make sure your customer interactions still have that human touch. We all know how frustrating it is to dial zero until we’re connected to a representative. Make sure customers have the option to speak to a human if they prefer.
Marketing involves understanding customer needs, matching them to products and services, and persuading people to purchase those products and services—three tasks that artificial intelligence can execute quickly and efficiently.
AI marketing is similar in a lot of ways to AI-enhanced customer service in that it uses chatbots, behavior analysis, and predictive analytics. The reason artificial intelligence is useful from a marketing standpoint is because it helps bridge the gap between customer data and actionable next steps.
Marketing Evolution provides the following tips for implementing AI to improve your marketing strategy:
Identify areas for improvement: What are your marketing goals, and how do you foresee AI analytics helping you reach those goals? Then, establish clear KPIs.
Ensure that privacy standards are programmed into your AI platform to protect sensitive information.
Have the data ready. This will enable the machine learning algorithm to identify customer trends, behaviors, and preferences. Data can be taken from your website, or it can be second- or third-party data.
Note: Working with and gathering insights from large amounts of data is challenging. It’s also important that your customer data is standardized and error-free, otherwise the insights won’t be useful. It’s a good idea to consult a data scientist, or a third-party organization that specializes in AI to assist with your data collection and analysis.
Anyone who has ever sat through a job interview would agree that there are some aspects of the recruiting and hiring process that are best completed by humans. A machine can’t provide a reassuring smile or handshake, nor can it empathize with personal experiences.
What artificial intelligence can do to make recruiting and hiring a less time-consuming process for your small business is manage interview scheduling, screen application materials for keywords, and assist with applicant tracking.
Artificial intelligence can also shed light on and help eliminate bias in hiring practices. One thing to be aware of, however, is algorithmic bias, which can occur when the data used to train AI contains biases that pose a disadvantage to diverse candidates (full content available to Gartner clients). The most infamous instance of algorithmic bias occurred in 2018, when Amazon discovered that its machine learning-based recruitment program was biased against women. Algorithmic bias can also occur with systems that search for candidates by geography, which can inadvertently produce racially biased outcomes.
To avoid algorithmic bias, the onus is on both the vendors building AI-based hiring platforms as well as the companies using them to assess whether hiring outcomes are more equitable.
With any AI solution you choose to implement, keep these recommendations in mind (full content available to Gartner clients).
Create a shortlist of use cases that demonstrate why an AI solution is appropriate for your small business, and gather some data for them.
Choose the AI solution that’s the best fit for your use cases, data, and skill level.
Ensure that you have staff who understands and can implement the AI program you’ve selected. If not, consult a third-party organization.
To learn more about artificial intelligence and how to leverage its capabilities for your small business, check out our other articles:
GetApp 2021 Top Technology Trends Survey
This study was conducted to better understand the technology usage, needs, challenges, and trends for small businesses. The research was conducted between August and October 2021 among 548 U.S. respondents from the education, financial services, healthcare, IT, manufacturing, media, natural resources, retail, and telecommunications industries.
Respondents were screened for the job categories of President, CEO, Owner or Sole Proprietor, General Manager, C-Level Executive, Business Unit Manager, Vice President, Director, Functional Lead (Manager & Above), and Office Manager, and had to have some level of influence on software and technology decisions. Additionally, participants’ companies had to have been in business for 12 months or longer, have between two and 500 employees, and earn between $5 to $250 million in revenue.
Disclaimer: Results of this study do not represent global findings or the market as a whole but reflect sentiment of the respondents and companies surveyed.
Note: The applications mentioned in this article are examples and are not intended as endorsements or recommendations.
Explore by topic