Not all AI are alike. In fact, what is considered artificial intelligence has shifted as the technology develops. Today, there are three recognized levels in the AI spectrum, all of which we can experience today.
Assisted intelligence – This refers to the automation of basic tasks. Examples include machines in assembly lines.
Augmented intelligence – There is a give and take with augmented intelligence. An AI learns from human input. We, in turn, can make more accurate decisions based on AI information. As Anand Rao of PricewaterhouseCoopers (PwC) Data & Analytics puts it: “There is symmetry with augmented intelligence.”
Autonomous intelligence – This is AI with humans out of the loop. Think self-driving cars and autonomous robots.
AI and Business Decisions
Marketing Decision-Making with AI
There are many complexities to each marketing decision. One has to know and understand customer needs and desires, and align products to these needs and desires. Likewise, having a good grasp of changing consumer behavior is crucial to making the best marketing decisions, in the short- and long-run.
Customer Relationship Management (CRM)
Artificial intelligence within CRM systems enable its many automated functions, such as contact management, data recording and analyses and lead ranking. AI’s buyer persona modeling can also provide you with a prediction of a customer’s lifetime value. Sales and marketing teams can work more efficiently through these features.
Recommendation systems were first implemented in music content sites. This has since been extended to different industries. The AI system learns a user’s content preferences and pushes content that fit those preferences. This can help you reduce bounce rate. Likewise, you can use the information learned by your AI to craft better targeted content.
Automation Efficiency and AI
The automation efficiency lent by artificial intelligence to today’s business processes has gone beyond the assembly lines of the past. In several business functions, such as marketing and distribution, AI has been able to hasten processes and provide decision-makers with reliable insight.
Social computing helps marketing professionals understand the social dynamics and behaviors of a target market. Through AI, they can simulate, analyze and eventually predict consumer behavior. These AI applications can also be used to understand and data-mine online social media networks.
Opinion mining is a kind of data mining that searches the web for opinions and feelings. It is a way for marketers to know more about how their products are received by their target audience. Manual mining and analyses require long hours. AI has helped shorten this through reliable search and analyses functions.