When most people think about artificial intelligence, it often conjures images of sentient robots and outlandish science fiction movies. AI is viewed by many as something futuristic, if not altogether unattainable. However, the reality is that at least one form of artificial intelligence is actually already available — and most people are regularly using it. Whether it is a phone menu that you can talk to, suggested photo tags on social media, or recommended products on ecommerce sites, AI permeates much of the modern user’s online activity.

Nowhere is artificial intelligence more beneficial than in business. There are now more than 2 billion smartphone users worldwide, and just as many active social media users. As such, social media marketing spending is expected to exceed 17 billion U.S. dollars in 2019. Increasingly then, businesses are using AI in order to keep up with this ever evolving consumer base — one that increasingly lives online. But what are some of the specific ways in which businesses are doing this, and exactly how does artificial intelligence work to boost a business?

There are three main stages of artificial intelligence: machine learning, deep learning, and natural language processing. First, let’s dive into some of the science behind the current version of artificial intelligence. To understand AI, you have to understand the technology known as machine learning. Machine learning is what drives current AI. Essentially, machine learning is the phrase used to describe the complex way in which modern computers can learn from data, with minimal programming (no need to write code, for example). The more data the computer is fed, the smarter it gets at recognizing patterns and predicting outcomes.

Take this even further, and you have deep learning. Deep learning is able to use more complex algorithms to carry out tasks with little or no human supervision. An example of deep learning in practice would be apps that can use facial recognition to identify people in photographs. Natural language processing (NLP) is another form of machine learning that is able to recognize and apply language and grammar rules in large data sets.

Given that 90% of the data in the world today has been created in the last two years alone, each of these facets of machine learning combine to create a kind of artificial intelligence that is particularly useful in today’s online environment. This is especially true for businesses, who are looking to reach their customers in a more meaningful and mutually beneficial way.

It is no wonder then, that businesses are jumping at the chance to use artificial intelligence to better understand their customers. Using this AI technology, businesses can achieve a more complete view of each customer than has ever been possible previously. Usually harnessed through a customer relationship management (CRM) platform, AI tools can collect and analyze customer data across all channels, learn insights, predict outcomes, and recommend — or even perform — next steps.

With this in mind, it is easy to see how AI can streamline the running of a business, and indeed affect just about every aspect of modern ecommerce. Through predictive analytics gleaned through artificial intelligence, marketers are able to place ads more effectively, sales reps know which leads to focus on, and customer service is able to answer questions without having to rely on human expertise or support.

AI Can Optimize the Sales Process.

Of all of the areas in which artificial intelligence can be applied, sales is arguably the most prominent. In fact, high performing sales teams are 3.4 times more likely than underperforming teams to currently use AI. There are a number of ways in which AI can be used in a sales setting. Consider the following:

  • Smart insights gleaned from past results can be used for training purposes, and training or coaching programs for sales reps can be crafted to fit each individual, using AI.

  • AI can help managers to identify exactly where their sales teams are struggling, long before they would normally be able to, allowing them to take action before any real problems occur.

  • Sales teams can more effectively direct their time and effort, allowing them to get the most out of every work day. Because AI gives them a better understanding of their customers, they are able to know how to most effectively reach them; furthermore, AI can tell them which leads are most likely to progress down the pipeline, allowing sales teams to direct their focus in the right places.

  • The predictive analytics provided by CRM platforms that use this kind of AI also aid in connecting sales and marketing, to provide a fuller view of each customer, and a more unified multichannel experience.

Of course, in order to take advantage of the possibilities AI represents, your business needs access to the right tools. Salesforce Einstein, the most advanced AI for CRM brings intelligent automation solutions to business.

Salesforce Einstein is AI for the modern business world. Developed for and fully integrated into the Salesforce Customer Success Platform, Einstein provides intelligent data analysis and predictive forecasts, learning as it goes. With Einstein, you can put your data to work for you, and from that data, you can enjoy the benefits of a built-in, intelligent advisor in all aspects of your business.

Einstein can be used with other CRM solutions across sales, service, marketing, commerce, analytics, apps, and so on, to aid each business in making smarter decisions — and ultimately provide a more complete experience for customers.

So although artificial intelligence might have previously seemed like something we would only ever see in movies, it is actually a real and usable tool for businesses today. In fact, the estimated market for AI solutions is projected to be more than $153 billion by the year 2020 , so now is the time to get ahead of the curve.
Artificial intelligence might one day expand to include sentient robots and other scifi greatest hits, but until then, the AI tools that we do have are well worth exploring.
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