Video | Agriculture | Confidence | Economy | Energy | Employment | Finance | Media | Property | RBNZ | Science | SOEs | Tax | Technology | Telecoms | Tourism | Transport | business intelligence tools offer this technology through a range of features that enable companies to make better decisions and automate multiple managerial tasks. Here we tell you how.
For decades now, human judgment and intuition have been the main driver of decisions in the business landscape. However, with the amount of data being analyzed growing exponentially, the possibility of human error becomes a latent threat. AI-driven decision-making assists businesses in making faster and more accurate strategic, operational, and tactical decisions without the risk of human error or biases that can affect the human mind. By putting AI systems as the main processors of large amounts of data, companies can extract accurate insights from their information and make more consistent and objective decisions such as the inventory that should be sold, which financial investment is best to make, or even which ad is most effective based on the audience.
Due to their intelligence level, AI models can work on real-time data to make accurate predictions and recommendations. For example, an AI-based algorithm can analyze customers’ purchasing data and automatically suggest related products to recommend to a customer and increase purchases. On the other hand, natural language processing technologies powered by AI, enable businesses to analyze the sentiment behind social media comments and answer accordingly to boost engagement.
That said, there are three main areas in which AI is being used by businesses, let’s look at each of them briefly:
Assisted intelligence: This area is placed at the lower end of the AI spectrum as it is used to automate simple tasks in business operations that need to be performed faster and more cost-effectively. These are often well-defined and repeatable tasks such as assembling lines in a production plant or collecting data to generate reports.
Augmented intelligence: On the other hand, augmented AI goes a step further from automating a repeatable task to proposing new solutions and augmenting human capabilities. It does this with the help of machine-learning technologies, natural language processing, predictive analytics, and neural networks that learn from human input to propose accurate solutions. Humans then use this information to make decisions such as predicting customer preferences by identifying trends in the data and offering targeted services and experiences.
Automated intelligence: The most advanced form of AI, automated intelligence relies solely on machines, bots, and systems to act on their own without human intervention, for example, autonomous cars. However, there is still a lot of ground to be covered in this area and it is not always considered a great asset in all industries, especially in the ones where the best outcome is harder to quantify. In most cases, businesses use fully autonomous technologies as “consultants” with the final decision relying on humans.
All the aforementioned points do not mean that human judgments should be completely removed from the analysis process. While having automated data processing saves businesses a lot of time and money, there is a wide range of decisions that need to rely on more than just structured data. Factors such as market conditions or company values are things that affect the decision-making process and that AI systems cannot process. This, paired with the fact that ensuring security and reliability in AI systems requires a lot of effort, makes it fundamental to complement both human and machine processing to make the decisions that will lead the business to grow. Just analyzing the data is no longer enough to set yourself apart from competitors, organizations that rely on advanced technologies like AI are set to skyrocket their performance.
© Scoop Media
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