What is Artificial Narrow Intelligence?
The term “artificial intelligence” often evokes images from science fiction movies. However, AI technology isn’t fiction: it’s real, and it’s gaining wider usage. Three types of AI are widely recognized in the technological community: narrow, general, and super.
Artificial narrow intelligence (ANI or narrow AI) refers to a computer’s ability to perform a single task extremely well, such as crawling a webpage or playing chess.
Artificial general intelligence (AGI) is when a computer program can perform any intellectual task that a human could.
Artificial super intelligence (ASI) is an AI that surpasses human intellect.
Today, most experts would agree that ANI is still maturing, AGI is at least a couple of decades away from being perfected, and ASI is even farther off. Apart from being an exciting technological innovation, ANI has numerous useful applications, and is becoming more prevalent in our everyday lives.
ANI and bots
The rapidly growing field of bots serves as an excellent example of narrow AI at work. In its simplest form, a bot is a piece of software that can run automated tasks that are generally simple and repetitive in nature.
Bots can provide answers to questions like, "What’s the weather going to be like today?", "Where should I go for lunch?", "How many visitors came to our website last week?", and so on. Bots pull data from larger systems and deliver just the answer you’re looking for – whether it’s from a weather site, a restaurant recommendation engine, or a web analytics platform.
Companies like Google, Facebook, and Slack are leading the charge in bot development, striving to create more accurate, user-friendly bots for a wider variety of purposes.
ANI’s implications for customer engagement
Bots powered by ANI can be used to automate repetitive service tasks, such as searching a knowledge base, looking up product details, shipping dates, order histories, and performing countless other customer requests. In customer interactions, bots can deliver consistency, accuracy, and speed – and unlike humans, they don’t get bored doing the same task over and over. Bots are a boon to customer experience management.
For instance, say you’re in charge of customer care at a cosmetics company. A customer wants to re-order her favorite foundation product, but she doesn’t remember which shade she ordered last time. In the past, she would have had to find the receipt from her last purchase (or guess which shade she needs). Today, she’s probably logging onto your website and hunting through her order history. Tomorrow, she can simply ask a bot. She could text, hop on a self-service web chat, or use Facebook Messenger to ask, “What shade of foundation did I order last?” The bot can quickly match her identity, find her order history, understand which product she’s referring to, and tell her. What’s more, she could even ask the bot to re-order it for her.
In addition to providing consistency and speed, using bots for repetitive customer requests can positively impact customer care staff. With bots handling more requests, customer-facing teams have more time to engage the customers they talk with, proactively educating them and heading off future questions. When agents are freed from the boredom that comes with answering the same questions over and over, they are more engaged in their work.
Brands are beginning to embrace the power of bots, recognizing the potential of narrow AI to drive considerable business value and help them scale. After all, who wouldn’t want a more consistent brand experience, quicker answers, more satisfied customers, and more engaged employees?