4 Reasons To Bring In Artificial Intelligence: Examples From Cameroon

If you see artificial intelligence in Cameroon like deploying Skynet in the Terminator movie, for sure, you’ll hesitate. You might even want to fight back like John Connor.

But based on the 2019 Gartner CIO Survey, 14% of organizations employ AI and nearly 50% intend to do so in 2020.

In Cameroon, UBA’s Leo is a good example. Leo will help you:

Open an account online
Transfer funds to your UBA account
Transfer to another account holder
Transfer to UBA prepaid card
Purchase telephone credit
Pay invoices
Introduce and follow up complaints and claims.

Another Cameroonian example is AgrIA.

AgriIA will use artificial intelligence in Cameroon to determine the best period for seeding. Their device deals with calculations relating to soil humidity and temperature, as well as climate predictions, in order to give the probability of a successful sowing in a given space and over a given period.

What is Artificial Intelligence?

Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry.

5 Reasons Why You Need to Adopt Artificial Intelligence to Grow Your Business in Cameroon

1. AI is not as expensive as you think if you start small like UBA

Like UBA, benefit from process automation.

Of the 152 projects Harvard Business Review studied, the most common type of AI was the automation of digital and physical tasks—typically back-office administrative and financial activities—using robotic process automation technologies.

Robotic Process Automation (RPA) is more advanced than earlier business-process automation tools, because the “robots” (that is, code on a server) act like a human inputting and consuming information from multiple IT systems. Tasks include:

transferring data from email and call center systems into systems of record—for example, updating customer files with address changes or service additions;
replacing lost credit or ATM cards, reaching into multiple systems to update records and handle customer communications;
reconciling failures to charge for services across billing systems by extracting information from multiple document types; and
“reading” legal and contractual documents to extract provisions using natural language processing.

While RPA is the least smart, it is also the least expensive and easiest to implement of cognitive technologies. Be sure at least of a quick and high return on investment.

2. Put a customer-first mindset into practice.

Businesses like to preach customer centricity, but when it comes to putting that ethos into practice… well, easier said than done.

Well, artificial intelligence has come to help.

Robotic Process Automation like in the Leo example above can help you deliver a true one-on-one customer experience.

“AI presents the opportunity for businesses to automate routine tasks so that humans can better use their time to provide higher value contributions.”
— Ellie Mirman, CMO of Crayon.

3. Use Data for business management and strategy

There is more information than ever because of digitalization. Web 2.0 has connected people in Cameroon like never before. As a result, businesses are collecting troves of data.

But the rate at which we collect data barely matches with analysis. As a result, an estimated 60–73 percent of this data is sitting unused, even though that data could contain information integral to the optimization of a business’ operations.

Utilizing machine learning in the collection and processing of data will help you better extract value from these large datasets, which in turn will allow you to identify new opportunities to “grow revenues, product lines and offer differentiated customer experiences,” says Barry Matthews, head of UK, Ireland, and the Netherlands at ISG.

4. Data, IT & Security Concerns

Hand in hand with data collection is data protection. There’s an increasing amount of sensitive and personal data collected and stored on the web and online servers.

This access to data means companies and people are becoming more vulnerable to threats such as identity theft, fraud, phishing, and other attack vectors. These threats are becoming smarter and increasingly more difficult to prevent, detect and resolve when security is breached.

Humans alone no longer have the capabilities necessary to prevent these attacks themselves and must engage with AI and ML to help combat these threats.