Learn AI Fundamentals
- Understand the very basics of AI.
- Articulate the fundamental shifts AI is having on the customer experience.
- Recognize how AI can impact your business.
For most of us, everything we’ve learned about Artificial Intelligence (AI), we’ve learned from Hollywood. There are the time-traveling robots trying to kill us before we can have children who will someday lead the future rebellion against said robots. Or evil machines using humans as batteries in giant factories, providing a power source to said evil machines. Killer robots, blue and red pills, evil machines—it all sounds scary, right?
But unless we’re talking about summer blockbusters, that’s not what AI is really about. Instead, AI is about making your daily experiences smarter, by embedding predictive intelligence into your everyday apps, like this:
- Siri acts as a personal assistant, using voice processing
- Facebook provides recommended photo tags, using image recognition
- Amazon provides recommended products, using machine learning algorithms
- Waze (a GPS and maps app) provides optimal routes, all at the click of a button
Still not convinced? Think about it like this. Since the industrial revolution, humans have created tools to augment human capabilities. Sure, you can get across Europe in a horse-drawn carriage, but an airplane is a tool that gets you there much faster. AI is just another tool that’s here to help you go faster. With AI, we can harness the power of data so that we can expand the reach of human expertise to solve unforeseen problems.
But more than that, AI represents a massive change in technology. You might call it a “paradigm shift” or “disruption” or we could just stick with “massive change.” What we’re trying to say is, AI is kind of a big deal. And just like the arrival of the personal computer, cloud computing, and the mobile smartphone, AI is going to fundamentally change the way things work, forever.
AI is not killer robots. It’s killer technology.
At a high level, AI is the concept of having “machines think like humans.” You’re starting to see examples of AI in your everyday life because we’re at an evolutionary tipping point. AI isn’t a new concept—we’ve had the theoretical models for a long time—but it’s finally possible thanks to the access and increase in large amounts of data combined with the low cost of high-power computing.
Try out this simple formula: Lots of data + cloud computing + good data models = smarter applications.
It’s been a long road to get here. You probably know about some of the high points on this timeline, like the Turing test or that computer that played chess.
|1842||Lovelace||Programmable mechanical calculating machine|
|1956||McCarthy, Minsky, Rochester, Shannon||The first AI conference|
|1957||Simon, Shaw, Newell||General Problem Solver|
|1961||Devol, Engelberger||Industrial robot “Ultimate”|
|1965||Weizenbaum||“ELIZA” and the first expert system|
|1980s||Various||Commercial expert system|
|1993||Horswill||“Polly” (behavior-based robotics)|
|1996||IBM||Deep Blue chess-playing computer|
|2011||Apple, Google, Microsoft||Mobile recommendation apps|
|2013||Various||Machine learning, deep learning|
|2016||Google DeepMind||AlphaGo beats Lee Sedol in Go board game|
|2018||Google Duplex uses Google Assistant to call and book appointments|
No one is expecting parity with human intelligence today. But AI has big implications on how we live our lives, and the disruption is happening quickly.
Autocorrect mishaps aside, whenever you pick up your smartphone, you already are seeing what AI can do for you, from tailored recommendations to relevant search results. And with each experience you have, AI is systematically retraining you to expect more from every app you use and website you visit.
Here’s an example. Meet Wendy, an account executive in a metropolitan area. Wendy uses Uber to get around town, and when she has a question, she asks Google for help. In other words, she’s pretty tech-literate. Now imagine Wendy walks into her favorite store to buy a new dress.
The way Wendy experiences technology, she would expect that the retailer:
- Would have her information in the system, because she bought something online
- Would know her historical preferences based on her last purchases
- Would recognize her when she walks in, and perhaps even suggest the right dress to try on
But what if that store is still on a mainframe computer system? Think there will be a customer disconnect? You bet!
This is the expectation that AI is starting to create. Consumers are now expecting that companies they interact with are going to anticipate their needs and reduce the friction of doing business with them.
Back to Wendy. As mentioned, she often uses Uber to get around town. So how can a company like Uber leverage AI to better serve loyal customers like Wendy? Well, Wendy might take an Uber every day at the same time and to and from the same location. Uber could easily send her a car, unprompted, because it knows the patterns that she follows every day. Wendy could then choose to accept the ride or reject it as needed.
In this way, AI makes it even easier for us to interact with the apps that we’re already using every day by understanding our patterns. Said another way, AI is doing the work for us, so that we can use technology *without using technology* to become more connected to experiences that matter.
So far, we’ve explored AI’s impact on customer expectations. So how can AI affect how companies sell, service, and market to the customer? For this, we have to look at the impact AI has on CRM systems like Salesforce.
Let’s look at another story. Let’s say a bank has a custom banking application built on Salesforce’s Lightning Platform. We already know that machine learning algorithms can understand how human agents diagnose and solve customer problems by learning from historical data over time. So what if we surfaced an agent-like assistant powered by machine learning in the bank’s mobile app?
The AI assistant would know who the customer is, their historical banking activity, and the best way to answer their question based on past inquiries. Now, that customer can get their question answered faster all from their mobile device, without having to make a phone call or visit the bank’s website. This means:
- Customers get their questions answered quickly, in a self-service manner with fewer touchpoints
- Support agents get more time back in their day, allowing them to provide 1:1 customer support for top tier accounts
- Customers are happier, and happy customers = higher revenue retention = more money for the bank
It’s not just about support though, it’s also about sales, marketing, and every other function in CRM.
AI has benefits for all parts of the business. Sales reps no longer have to enter sales data manually. Marketers no longer have to use manual A/B testing to select the best social media images for their next campaign. And customer service managers no longer have to sift through long lists of incoming service calls to prioritize their time.
Need a few more examples?
- Automatically capture sales activities
- Automatically log customer data
- Suggest next-best actions and recommended email responses
- Automatically classify and route cases
- Recommend solutions and knowledge articles
- Self-service communities and automated assistants
- Automatically score likelihood to open an email or subscribe to a newsletter
- Deliver the next best product, content, or offer
- Send messages at the right time, when a customer is most likely to engage
Now that you've learned the basics of AI and how it will transform CRM, we want to get a bit more technical and share some of the science behind AI. We'll head there next.