Artificial Intelligence in Business

Robots and humans made an agreement. / Photo by: Willyam Bradberry via Shutterstock


The IBM Senior Vice President for Research Solutions, DR. John Kelly III said, “the success of cognitive computing will not be measured by Turing tests or a computer’s ability to mimic humans. It cured and lives saved.”

AI isn’t the end but it is actually the beginning of an era of efficiency, effectiveness, better opportunities and innovative capabilities. Moreover, this is very evident in many industries that are now adopting artificial intelligence into their day to day operations.

A survey by Tech Pro Research points out that up to about 24 percent of businesses are now implementing or are still planning to use artificial intelligence in their operations. This is more evident in the sectors of health, automotive, and financial services.

Talking of financial services, the PWC has assembled huge amounts of data from US financial data, the US Census Bureau, and several other public licensed firms to build secure -- in a large scale of about 320 million American Consumers -- financial decisions.  This is designed to aid financial service companies, map buyer behaviors, mimic “future selves,” and predict customer behavior.  It has played a big role in helping these financial services companies come up with real-time business decisions in a matter of seconds. 

In the automotive sector, on the other hand, artificial intelligence has achieved great milestones from designing motors to supporting sales and marketing decisions. For instance, artificial intelligence has led to the designing of smarter (like driverless) vehicles, equipped with several sensors that can learn and understand patterns. This is made practical in the add-on features of safe-drive that have the ability of warning drivers of lane departures and possible collisions.  

Just like in financial services, artificial intelligence is used to give rise to a model in automobiles.  In the automobile ecosystem, there are bots that can map the decisions reached from automotive players like manufacturers, car buyers, and transport service providers.  This has seen companies predicting the adoption of driverless and electric vehicles and the development of non-restrictive pricing schemes that perform on their target market. It has also enabled the industry to come up with better advertising decisions that catch the eye of prospects.

The main point here is how artificial intelligence has the ability to run more 200k go-to-market scenarios instead of running just a handful. The benefits are optimized services that bring revenues to the maximum.


The same case is also thriving in the fields of retail, sales, and marketing. John Bates, the Adobe Marketing Cloud product manager, said, “For retail companies that want to compete and differentiate their sales from competitors, retail is a hotbed of analytics and machine learning.”

The application of artificial intelligence development has equipped marketers with new tools that are more reliable in predicting the market, automating the process, and making decisions.

Artificial intelligence and decisions in business

Prior to the emergence of artificial intelligence and its breakthrough in financial application, people had to rely on incomplete and inconsistent data. With artificial intelligence, people now boast of data-based models to turn to.

Rao from Pwc reiterates, “ there is an immense opportunity to use AI in all kinds of decision making.” Limitless outcome modeling is among the biggest milestones achieved in the current AI systems.

Current AI systems begin with zero and feed on big data. This is super intelligence at work that eventually equips executives with a sophisticated model that plays a big role in their decision-making.

Many AI applications better decision-making abilities. These are some few examples

Marketing Decision-Making in marketing with AI

Many complex things need to be considered in every marketing decision. Businesses need to understand their customer needs and their desires. They also need to align their products with the customer’s need and desires. On the other hand, having good knowledge of the changes in customer behavior is critical to coming up with the best decisions in as far as marketing is concerned.

AI simulation and modeling techniques give business executives insight into their buyer personas. These techniques help to predict the behavior of consumers. Using a decision support system, the business’ AI system can support decisions through up to date and real-time data collection, forecasting and analyzing trend.

Customer Relationship Management 

A robot helping a human. / Photo by: Willyam Bradberry via Shutterstock


Artificial intelligence in customer relationship management systems enables many functions like contact management, lead ranking, and data recording and analyses. AI buyer persona modeling also provides a prediction of the lifetime value of customers. The teams concerned with sales are able to work more efficiently through these features.

Recommendation System

Recommendation systems were originally made for music content sites but have been introduced to different industries. This system learns what users content prefer and pushes content that matches those preferences. This helps in reducing bounce rates. It also helps to design better-targeted content.