What Should You Know About Applied Intelligence vs. Artificial Intelligence?

Although artificial intelligence (AI) has made headline after headline regarding the optimization of business processes, there are still some common myths out there that need to be set straight.

When people hear the buzzwords artificial intelligence or machine learning (ML), they tend to jump straight to the thought of robots taking over the world, replacing the workforce, stealing labor, and controlling everything around us.

Yes, there are some remarkable examples of robots performing human work. Still, the vast majority are redundant tasks that help employees focus and be more productive in specialized areas. If applied correctly, the best way to think about robotic process automation (RPA) is as a digital sidekick – perhaps, a digital Robin to your Batman or any other sidekick examples you can think of.

It's important to note that artificial intelligence does not operate in a vacuum. Data is crucial to AI systems (like an insight engine) and needs to be utilized to make them more intelligent and equipped to handle users' on-the-spot needs.

Artificial Intelligence

Per Investopedia, "artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving."

Applied Intelligence

On the other hand, applied intelligence is the use of artificial intelligence. It becomes applied when artificial intelligence leaves the lab and sees the light of day, helping workers with their everyday tasks in various functional areas. In simple terms, the decision to "use or not to use" separates intelligence from applied intelligence. Innovative business and IT leaders are the ones that will decide to apply and leverage these systems for use cases throughout their organization.

Being Smart in Your Approach

As we know from our previous blog series, there are critical steps to consider before rolling out an AI solution, such as an insight engine. Deciding to innovate processes and go in blindly is not a recommended approach by Mindbreeze or any other digital transformation leader in the space.

To refresh your memory, you can view part one of the mentioned blog series with a simple click.

Once deployed, advanced applied AI will go well beyond automating tasks and processes but feed users' knowledge and insights within their workflow – adding context, meaning, and value to their current project.