The idea of artificial intelligence often feels like a fantasy for people outside the tech world. It sounds like something you hear in movies like The Matrix. But in reality, artificial intelligence for the real world is part of almost every human endeavor.
You can use AI in business, entertainment, telecommunication, healthcare, and several other industries. But despite the current hype around AI in the tech world today, we can only limit our focus to business-related aspects of the technology.
So, let’s check out the main types of artificial intelligence and how companies can gain from them. We will also discuss the impacts of an AI developer on a company’s business strategy.
Three types of artificial intelligence
In terms of business, AI can be applied in various aspects of a company’s strategy. But instead of listing all these areas, we’ve compressed them into three main categories: automation, insights, and engagement.
AI and machine learning algorithms are essential for acquiring useful insights into a company’s activities. With the help of artificial intelligence applications, you can do the following:
- Make predictions on consumer behavior
- Predict upcoming market trends
- Spot risks and system vulnerabilities before they become critical
- Automate marketing and advertising initiatives
- Provide accurate predictive models for products and services
Cognitive insights obtained by machine-learning algorithms offer more accurate real-time insights. And with advanced technology like deep learning, you can replicate customer behavior using recognizable behavioral patterns.
Companies and startups often use cognitive engagement technologies to interact with their customers and employees. At the moment, most companies rely on artificial intelligence algorithms to reply to generic messages and address frequently asked questions. However, the AI still needs supervision from a human AI developer to address more complicated user concerns. For example, customer service still needs humans to provide solutions to customers because deep learning has not advanced to the stage of mimicking all human emotions and adaptive problem-solving capabilities.
The rise of automation is the driving force behind the current digital transformation. Every process that cannot be automated is considered redundant and non-productive. Currently, physical tasks and administrative responsibilities are now automated using robotic technologies. These robot programs are called Robotic Process Automation (RPA) technologies.
And with the help of these robots, the speed and accuracy of data processing are ensured across all tasks and departments. At the same time, RPAs also handle redundant and repetitive tasks. Although they might be expensive to implement and integrate, they can help companies to reduce hiring costs significantly.
Despite worries that robots will put humans out of work, the results have shown the opposite. Besides, RPAs require constant monitoring and maintenance by certified AI developers. This, in turn, opens up new employment opportunities.