Artificial intelligence has been around since at least the 1950s, but it’s only in the past few years that it’s become ubiquitous. Companies we interact with every day— Amazon, Facebook, and Google—have fully embraced AI. It powers product recommendations, maps, and our social media feeds. But it’s not only the tech giants that can employ AI in their products. AI solutions are now accessible for many businesses and individuals. And it’s becoming clear that understanding and employing AI is critical for the businesses of tomorrow.
Of course, for most companies, there are a number of challenges to overcome before incorporating AI into their infrastructure, the greatest of which is probably the talent war for data scientists and machine learning engineers. That being said, according to a Harvard Business Review article by AI expert Kathryn Hume, in equal demand are business professionals who soundly understand AI and the problems it can solve. Spotting opportunities and working with machine learning teams to solve them is crucial to actually applying AI.
Right now if you’re looking to build your business knowledge, understanding AI should be top of the list. It’s changing every aspect of business and technology. And it’s applicable to many of the new jobs that are being created.
Before we look at some of the ways that AI is changing business, let’s go into the history of AI and also understand some of the key definitions.
What Is AI?
In the last 20 years, there have been major changes in technology—notably the advent of mobile. But the innovation that’s on par with inventing electricity is artificial intelligence.
In March 2017, a worldwide survey of internet users found that three out of 10 people polled had heard of AI, but didn’t know much about it. With so few people understanding the tech, it makes sense that they’re also wary of it: 41% of respondents in a 2017 Forbes poll said they couldn’t cite an example of AI that they trust. (This changes with each passing month, though.)
So, what is AI? Artificial intelligence describes a machine that mimics human behavior in some way. AI can make the user experience similar to interacting with a human. The human part is the output. The input is huge amounts of data. That’s what allows the AI to learn and adapt. It takes in reams of information and data and processes it. If it encounters a problem, it learns from the situation and recognizes a pattern.
There are many different terms being used, sometimes interchangeably and sometimes incorrectly, to describe AI. AI is an umbrella term encompassing several different forms of learning. The main buckets are machine learning, deep learning, and neural networks.
Machine learning is a subset of AI and is a set of techniques that give computers the ability to learn without being explicitly programmed to do so. One example is classification, such as classifying images: in a very simplistic interpretation, for example, a computer could automatically classify pictures of apples and oranges to go in different folders. And with more data over time, the machine will become better and better at the job.
Andrew Ng, one of modern AI’s pioneers, offers this helpful table on what machine learning can do:
Deep Learning and Neural Networks
Deep learning is a further subset of machine learning that enables computers to learn more complex patterns and solve more complex problems. One of the clearest applications of deep learning is in natural language processing, which powers chatbots and voice assistants like Siri. It’s the recent advent of deep learning that has particularly been driving the AI boom.
And all of these are based on neural networks, which is the idea that machines could mimic the human brain, with many layers of artificial neurons. Neural networks are powerful when they are multi-layered, with more neurons and interconnectivity. Neural networks have been researched for years, but only recently has the research been pushed to the next level and commercialized.
Conceptually, here is a comparison of a simple neural network to what a multi-layered neural network in deep learning may look like:
AI Business Benefits
Now that you have a conceptual understanding of artificial intelligence and its subsets, let’s get to the heart of it: what can AI do for you and your business? We’ll explore highlights within five areas: human resources, accounting, legal, marketing and sales, and customer support.
Artificial intelligence poses a significant opportunity in process automation. One example would be recruitment and human resources. For instance, tasks like onboarding and administration of benefits can be automated.
Human resources is often responsible for maintaining internal employee resources. According to the Harvard Business Review, artificial intelligence can make it easier to maintain “internal sites for answering employee questions on topics including IT, employee benefits, and HR policy.” One of the reasons is that artificial intelligence can power natural language search for finding information related to specific queries. And AI learns over time to answer queries more quickly and accurately.
The dutiful accountant, languishing over the bookkeeping—it’s a classic image. But now many of their services may not be needed. In fact, many traditional bookkeeping tasks are already being performed by AI. Areas such as accounts payable and receivable are taking advantage of automated data entry and categorization.
AI is also able to reconcile billing failures by extracting information from multiple document types. AI and humans working together can extract information and validate the results, sometimes being three times more consistent and twice as fast as human-only teams. There are even some cases where, using AI, Deloitte can do in a week what used to take four to five months.
Even further, many auditing and tax analysis tasks can now be automated through platforms like Blue J Legal.
It’s not hard to imagine that in the future, we won’t have as many accountants—at least not doing what they currently do.
Some of the most fascinating advancements in AI are related to law and legal technology. Specifically, AI can now read “legal and contractual documents to extract provisions using natural language processing.” Blue J Legal’s website touts the platform’s ability to assist with employment law. The Foresight technology “analyzes data drawn from common law cases, using deep learning to discover hidden patterns in previous rulings.” In short, cases can now be analyzed much faster, insights can be drawn from across a wide array of legal knowledge, and therefore business decisions can be more accurate and confident.
Another interesting development: it is becoming easier to get funding for legal action. The litigation financing industry has been around for some time, but it is being rapidly pushed ahead. Startup Legalist is making it easier for people and small businesses to access funding (the average per case is $100,000). They pick which clients they will take on based on a constantly improving algorithm. They search thousands of cases and calculate the likelihood of a case succeeding. One example is a Massachusetts ice cream sandwich manufacturer that sued its vendor for providing low-quality ice cream but couldn’t afford to continue its case alone. Legalist covers the cost of these suits and receives repayment only if the case is resolved successfully.
Sales and Marketing Analytics
Analytics can now be done far more rapidly with much larger data sets thanks to artificial intelligence. This has profound impacts on all sorts of data analysis, including on business and financial decisions.
One of the quickly changing areas is marketing and sales applications. AI makes it easier to predict what a customer is likely to buy by learning and understanding their purchasing patterns. It is also easier to automate the personalized targeting of ads to buyers based on their trends, their browsing history, and many other aspects of their persona. What’s telling is that, according to Forbes, already “87 percent of current AI adopters said they were using or considering using AI for sales forecasting and for improving email marketing.”
You’ve been there. Waiting forever on a customer support line. Perhaps with a cable company or a big bank. Luckily, AI is about to make your life easier, if it hasn’t already.
According to the Harvard Business Review, one of the main benefits of AI is that “intelligent agents can offer 24/7 customer service addressing a broad and growing array of issues from password requests to technical support questions—all in the customer’s natural language.” For customer support, a combination of machine and deep learning can allow queries to be analyzed quicker.
A main manifestation of AI for customer support is an intelligent chatbot. These appear on websites and support forums as humans, but are often operated by machines. One estimation holds that chatbots will power 85% of customer service by 2020. And there are real impacts on that investment. Chatbots are expected to cut business costs by $8 billion by 2022.
One of the most interesting companies in this space is Ada Support. They have a simple but ambitious mission: to automate most customer support inquiries. On their hompage, they cite 30 million customers engaged, $100 million in savings for clients, and 1 billion minutes of reduced customer effort.
Customer support is probably one of the clearest areas where AI can make an immediate difference.
With AI becoming even more pervasive, having a fundamental understanding of it is a must for continued business success. Whatever role you hold in your business, understanding AI may help you solve problems in new and innovative ways, saving time and money. Further, it may help you build and design the products and services of the future.
Find out more about Springboard’s AI / Machine Learning Course, the first of its kind to come with a job guarantee.