Digital and IT

The Business Applications of Artificial Intelligence

  • Antonios Kondis
  • February 02, 2021

What are the implications of AI for business strategy?
Forty percent of jobs will be replaced by AI within the next 15 years, says Kai- Fu Lee, one of the world’s most prominent experts on AI. Today, we know there are some problems AI can solve well and others that present more of a challenge.

What is AI?
The term artificial intelligence was first used in 1956, when the idea was to describe every aspect of learning or any other feature of intelligence so a machine can be made to simulate it. The team working on inventing AI also wanted to make machines use languages, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. This formed the basis of what is now called artificial general intelligence (AGI): a computer that is as smart as a human.

Nowadays, what is most referred to in the press is artificial narrow intelligence (ANI or AI), which is a computer program that was designed to excel in one very particular task. Machine learning (ML) is a subset of AI, which uses data to answer questions by making predictions.

In most cases, the low-hanging fruit within your organization will fall under supervised learning. This kind of machine learning has proven itself to be efficient within two areas:

Classification

    • Will we lose this subscriber within the next 6 months?
    • Will a consumer buy this item this month?
    • Will a client default on their next payment?

Regression Forecasting 

    • What revenue are we expecting this month from this POS?
    • What is the amount a particular consumer is willing to pay for this add-on?
    • When will this software or equipment fail if left without repairs?

Any process within your organization with the following characteristics is a good candidate for an AI project:

Profitability
Like any other sizeable project, the process must be important in terms of revenue to justify spending resources on it.

Generation of big data
Data related to this process must exist in multiple, large databases populated almost daily. It surpasses human ability to make sense of it.

Expert opinions
The problem is usually solved by resorting to experts who make decisions using intuition rather than data. No matter how good the experts are, AI can go much deeper in understanding the relationship between inputs and outputs.

You may have concluded that a B2C environment is more likely to offer opportunities for AI projects. Let’s review what they might look like both with and without AI.

artificial intelligence for business leaders

3 Easy Steps to Make Use of AI in your Organization 
After all this, you might think you need to hire people with PhDs in Statistics, invest in high-end AI databases and software, or enlarge your tech team with machine learning experts. But first think about which problems actually need to be solved. If you feel that there’s a gap for an AI project in your organization, find someone to mediate between business, IT and analytics teams—this may be a data scientist, but generally, the person you are looking for should have the following skills:

Business
Has their eye on the prize of profit increase rather than interesting correlations. Consulting experience or an advanced business degree would be a plus (if not a must), along with strong business sense.

IT
Understand how data is captured and structured in databases and be able to explain to an IT team how to better support you in providing the right data without creating too much workload. Understand how ML works (algorithm training, testing and evaluating vs. scoring) in order to be able to see the big picture, from solution exploration to productization.

Analytics
Know basic statistics in order to understand concepts like sampling and error metrics.

It’s a great time we live in; AI is finally within business reach. With careful planning, you can take advantage of it to increase profits and secure your competitive advantage today.

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