Pandemic-era lockdowns and mobility regulations have increased the popularity of ecommerce businesses.
Even as the world slowly recovers from the COVID-19 pandemic’s social and economic impact, the ecommerce industry’s increased demand did not dwindle.
Companies have looked for various ways to deal with the influx of clients.
Using AI in ecommerce operations is one of the methods these businesses utilize to make their processes more efficient.
With AI solutions, they can easily handle large volumes of orders and cut down on the time it takes to receive, confirm, and deliver them.
Defining AI
AI – short for artificial intelligence – refers to both the branch of computer science concerned with the creation of intelligent machines and the products of this field.
These intelligent machines have a wide range of practical applications across various fields.
Developers generally program AIs with a focus on three cognitive skills – reasoning, learning, and self-correction – they are excellent tools for tasks that deal with massive data processing.
Some AIs, like Apple’s Siri and Amazon’s Alexa, are used as digital assistants in smartphones and other “smart” devices.
There are also AIs used in automating work processes, particularly those that tend to be repetitive and lean more towards data processing.
These types of AI significantly decrease the time spent on repetitive tasks and lessen the occurrence of errors.
There are a total of seven different types of AI.
Four of these are based categorized according to their functionalities, while three are based on their capabilities.
AI-based on functionalities
These are the AIs classified according to their functions:
Reactive machines
These are the most basic types of AI.
As implied by the term “reactive,” this type of AI doesn’t store past data or memories it can use for reference in making future decisions.
An example of a reactive machine AI is IBM’s Deep Blue, a computer system famous for defeating chess grandmaster Garry Kasparov.
Limited memory
In contrast with reactive machine AIs, limited memory AIs can store memories, but only for a limited time.
One of the most useful applications of this type of AI is seen in self-driving cars.
The limited memory systems in self-driving cars store real-time and recent information about other nearby vehicles. These include their speed, distance, and other pertinent information like speed limits and present location.
The AI system uses all these information to navigate safely without human intervention.
Theory of mind
Theory of mind AI systems aren’t yet developed, but researchers and developers are sparing no effort in developing these machines.
These types of AI are expected to understand human emotions, behaviors, and beliefs and interact socially with people.
Self-awareness
Like the theory of mind AI systems, self-aware AIs aren’t yet a reality and remain a theoretical concept to date.
However, experts posit that self-aware AIs are the future of artificial intelligence.
These AIs are theorized to be more intelligent than humans and have their own thoughts and consciousness.
AI-based on capabilities
Below are the AIs categorized according to capabilities:
Weak or narrow AI
These types of AIs are the most common and are programmed to perform only a specific task.
Due to their limited functionalities, these AIs are referred to as weak AIs.
Deep Blue is an example of a narrow AI programmed for the sole purpose of playing chess.
General AI
Developers see general AIs as capable of executing complex tasks with the same efficiency as humans.
These AIs on par with humans’ cognitive abilities are still under research and may take a long time to bring into reality.
Super AI
Super AIs are the successors of General AIs.
In short, these machines are superior to humans in terms of intelligence and can execute any task better than a human can.
Like its supposed predecessor, Super AIs do not yet exist today and may take much longer to develop than General AIs.
How do businesses use AI in ecommerce operations?
In the ecommerce industry, AIs provide a better customer experience and streamlined processes.
Artificial intelligence helps collect consumer data and other business intelligence (BI) that help companies make better data-driven decisions.
Using AI in ecommerce also makes it easier to segregate customers into different categories based on available data.
Aggregating customers makes ecommerce marketing campaigns more effective as the materials will reach a better-targeted audience.
Aside from making customer and data aggregation easier, AI is also used in the ecommerce sector to provide customer support without relying too much on humans.
Ecommerce companies often use AIs to handle basic FAQs over chat support channels and field orders with minimal to zero human supervision.
Benefits of utilizing AI in the ecommerce industry
Integrating AI solutions in ecommerce business operations bring in plenty of advantages, and below are just a few of them:
Better marketing and advertising
Utilizing AIs allow marketers to create better-targeted marketing campaigns using AI-aggregated data.
With access to more efficient and personalized marketing and advertisement, ecommerce companies can bring in what customers really want based on their purchasing history or search data.
Process automation
AIs automate repetitive processes that don’t require heavy human interactions like – cart checkout reminders, order confirmations, product recommendations, and low-tier customer support.
Improved sales process
Ecommerce businesses also use AI automation to improve their sales processes.
As mentioned above, AIs send reminders about unchecked-out carts and make purchase recommendations based on available customer data.
Marketers also use AIs to nudge customers along the buying process by having chatbots engage with them for simple questions.
