Artificial intelligence (AI) is a term that was recently popularized by Alan Turing, though it was initially coined by John McCarthy in 1955. The initial characterization of artificial intelligence was of a “machine that is simulating intelligence and human logic.”
Today’s AI systems are about more than merely extending human logic. In the video below, one of the founders of modern AI provides a simple explanation:
Artificial intelligence is a very broad term. For starters, we can separate it into two big categories:
- Narrow AI: Usually involves training a model or group of models to accomplish a narrow task or to predict future outcomes within a narrowly defined field, based on data from that narrow field. Most AI today can be defined as narrow.
- General AI: Involves training a computer system not only to perform tasks and predict outcomes within a narrowly defined field but also to generalize beyond that field and learn to operate in new verticals without (much) oversight. General AI is the holy grail, but we’re a long, long way from it.
We can also break AI down into three component fields of research:
- “Artificial Intelligence”: While in the past AI covered an area ranging from rule-based expert systems to computers that use advanced computational statistics at scale, today, AI is more of an umbrella term for more precise fields of research (below). The term “AI” is often bandied around and used improperly when the application is merely fancy data analytics.
- Machine Learning: Machine learning is a subdomain of AI, which focuses on training computational-statistical models to learn from a known dataset A such that it can understand a future dataset B. For example, if you “train” a model to learn the difference between cats and dogs in a slew of images, by breaking down “cats” and “dogs” into the pixelated features that comprise them, your model can then look at other pictures of cats and dogs that you haven’t labeled and more or less accurately identify them.
- Deep Learning: Deep learning is a subfield of machine learning. It’s loosely inspired by the way brains process information. They use a “neural network” architecture of neurons organized into layers, which can be hidden or “deep,” each of which helps the overall network better understand the data that it’s being fed. Deep learning is essentially a neurologically-inspired form of machine learning that’s right on the cutting edge of AI research.
5 Ways to Implement AI in Your Business
Reading about AI and implementing it are two very different things. However, since you’re reading this article, there’s no harm in exploring the most effective ways of turning your company into an AI-advocate.
Here are some of the best ways to apply AI to your business and create positive outcomes.
1. Use AI for Customer Service
To take your customer services to the next level, you must give your customers the satisfaction and pride of being heard. You need to hear their screams, their problems and their needs, and you need to deliver a solution quickly.
AI bots are already popular among social channels. When you start a conversation with a brand, you will frequently receive an automated answer from a bot. That bot can have artificial intelligence, and it will answer according to what he has understood from your words and intention.
When you call a bank, for example, you get to talk to a robot. The robots serve as filters, but also as automation tools that significantly optimize the speed and the efficiency of the bank employees.
2. Automate the Boring Stuff
Automation is the art of making work happen on its own. If you’re able to automate a process, you’ll be able to focus on different processes or on the development of additional automation systems that will cut even more responsibilities, costs and energy waste.
AI is an ideal means by which to make our work smarter. Nowadays, every sort of automation is possible. Therefore, start thinking about your biggest time-wasters and your most annoying responsibilities. Then, try to imagine an “ideal” solution, a “smart” solution that would automate those tasks. If you find an answer, it means that the solution can become accessible through the use of (narrow) AI.
3. Improve Management
If you want to grow the impact and revenues of your company, while gaining more insight into your business processes, AI is something you should consider.
AI can replace your “gut instincts” as a manager and a leader with evidence-based and data-generated insights. And while “business insights” from mere data analysis shows you the patterns and lets you make sense of them, a properly used AI model can take it one step further, highlighting certain paths you might take, certain decisions you may want to make, based on patterns or anomalies in your data.
4. Next-Level Marketing and Advertising
If we have better control over data, user behavior and complicated patterns, what stops us from exploring the clues we discover and turning our marketing and advertising campaigns into profitable sales machines?
The answer is nothing. AI is already giving us the possibility to write and rewrite content in a matter of seconds, assign different bots to engage with our audience and automate other simple yet time-consuming tasks.
5. Better Personalization
Machine learning enables you to learn from and contextualize potential customers—people who visit your site. A properly-tuned AI application could detect patterns in your potential customer’s interactions with your website, guess when they’re about to fall off, or when would be the best time to serve them specific offers or forms of content. And you can feed the outcomes of those attempts into a continuous learning process that refines itself over time.
Nowadays, there are all sorts of digital marketing apps that have started to integrate AI in their algorithms and applications. Soon enough, identifying, classifying and using data will be a single process rather than three different ones.
As you’re probably noticing already, the AI industry is constantly changing and shaping its angles. What’s certain is its direction. It’s moving forward, and our business environment and the world itself is rapidly adapting to every new perk that technology brings.
AI is the next major breakthrough—just like the Internet or TV. It will change the world forever.
That being said, we have a long road ahead of us. We’ve climbed the first mountain of AI, and now we can see all the others yet to climb as we pursue the elusive ideal of a general AI that could work alongside humanity.