latest trending artificial intelligence news

Artificial intelligence has gone from being a “moon shot” project to something with real-world applications.

There is a lot of hype around what artificial intelligence can do for business, but practical applications are in use today. 

When speaking about the utility of AI, it’s best to think from a business perspective rather than technology.

AI helps automate business processes, gives insight through data analysis, and keeps customers and employees engaged. 

Automate Processes

The most common type of artificial intelligence in use right now is automating digital and physical tasks.

Advanced task automation uses robots executing code written to re-create human labor. Think robot arms on a car assembly line or robot forklifts that can deliver freight on their own. 

Examples of other processes that can be automated using AI include:

  • Data transfer from one system to another
  • Replacing lost or stolen ATM cards
  • Reconciling billing systems and extracting information
  • Parsing legal and contractual documents

Of the three major AI use cases, process automation is the easiest and least expensive to implement. It also brings a high return on investment because it frees up employees to perform other tasks. 

One thing to note – process automation is the stepping stone to real artificial intelligence. Most process automation involves executing code written by a human developer.

That gives process automation a very minimal learning capability for improving the process once coded.

Cognitive Insight

The second-most common type of artificial intelligence uses algorithms to detect patterns in data.

Looking at data from several points of reference gives businesses a laser-focused look at their business model. 

Machine learning is used to train these algorithms by feeding data to search for patterns.

These algorithms can be used for business applications that include:

  • Predicting customer buying patterns
  • Identify consumer fraud – credit and insurance
  • Analyze warranty data for manufactured products
  • Personalization of digital ads to generate leads
  • More detailed actuarial modeling

Cognitive insight is a data-heavy form of artificial intelligence that needs new data to create new models. Using new data to make predictions helps train algorithms that improve over time.

Machine learning trains the models the algorithms do, and they’re meant to mimic how the human brain recognizes patterns. 

Data curation is usually labor-intensive, but machine learning can train algorithm models that operate many times faster than humans performing the same task.

Cognitive insight AI can improve performance on jobs that machines already perform better than humans. 

Cognitive Engagement

Keeping customers and employees engaged with the business by performing HR tasks is another way AI is evolving in business settings.

Some examples of cognitive engagement AI includes chatbots, intelligent agents, and internal employee wikis. 

This type of artificial intelligence is the least common among the three, but it is rapidly growing.

Examples of how cognitive engagement can assist a business include:

  • Chatbots to answer a wide array of questions
  • Natural language assistants for technical support
  • Employee Wikis for HR and IT questions
  • Product and service recommendations
  • Health treatment recommendation systems

Most businesses use cognitive engagement AI to interact with their employees over customers.

However, applications for the consumer side are growing. One example is an intelligent agent that can answer most customer support questions in natural language.

The technology is very new, however, and it doesn’t always get it right. 

Is AI Right For Your Business?

Determining whether AI can assist you in any of these three areas may require an internal evaluation.

Implementing new process automation may require a redesign of some or all of your business operating procedures. 

The primary purpose of incorporating any AI in a business application is efficiency.

Cognitive technologies are in their infancy, but they may result in untold productivity and work satisfaction among both employers and employees.

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