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What you need to know about Artificial Intelligence

A few years ago, the innovation was dominated by few and large corporations. Recently, the use of solutions based on Artificial Intelligence (AI) advances in the market with exponential growth. The time is ripe for investments by companies of all sizes. And with the most varied objectives, from improving the internal management of the business to expanding knowledge about the markets, with the use of new analysis tools. Now we invite you to time take and reflect on how innovation will help your business grow.

What is Artificial Intelligence (AI)?

Artificial intelligence is real. Increasingly influential, solving simple and complex problems from our commands. It is the combination of machines and systems, working together, to allow computerized systems to process data and information and generate strategic knowledge for people and organizations. AI helps to: improve customer service, increase efficiency, empower employees, innovate and expand business networks.

Now, we invite you to take the time and reflect on how innovation will help your business grow.

How do I know if my organizations is mature to apply AI technology?

"Every corporation will be a technology company." - This was one of the predictions of futurists at the end of the last century.

The vast majority of companies already use systems to manage their production. Availing maturity, organizations today have mastered AI-related capabilities. Right now, all companies have the power of hardware and software at their disposal. Most of the company has enough data and systems to evolve to AI-based platforms.

If, on the one hand, the obstacles of infrastructure and access to technology are mature, on the other hand, there is a need for people capable of thinking and applying AI. Cultural transformation and training become necessary to accelerate and bring faster implementations. How do you look at the problems you are experiencing in the organization? Are you concern about efficiency? Is there something that can be automated with intelligence?

Case: AI applied to Insurance

Problem: Fraud activities cover a wide range of improper transactions to obtain favorable outcomes from insurance companies, from incident reporting, misrepresentation of situations, and false extent damages. These practices have accompanied insurance companies since their inception, and their forms have evolved along with the development of the industry. Insurers face several difficulties caused by the issue, namely: customer dissatisfaction due to prolonged investigation and payments being delayed; the cost of investigation and pressure from insurance regulators for late payments is high; and finally, potential overpayments can reduce companies profits.

Solution: The health insurance industry is embracing new technologies to address Fraud. Artificial Intelligence and Machine Learning can help in the rapid detection and prediction of fraud claims with greater accuracy. This can save the insurance company a lot of money and also ensure a better customer experience/cx for those non-fraudulent.

How shouldn’t we apply AI?

A big challenge when talking about exponential technologies, like AI (Artificial Intelligence), is also knowing what not to do. There is a great expectation in the market that everything can be automated with Intelligence. Then, suddenly, we will no longer need humans for anything. We at DdF believe that we are still a long way from that. Automating processes with intelligence to make all decisions is, at least, negligent in addition it can cause big problems for the organization.

"Understanding this fact, is a must to make a responsible AI strategy and really applicable! You cannot ignore the 'Human in the Middle’” Said Arian Saddam Hossain, DdF Co-founder.

What many people don't know is that: process of solving and automating through AI is a process for excellence by human. It is not possible to remove 100% of human bias from the process. In this way, it is necessary that automation continues to be monitored and adjusted, so that it maintains and keeps improving the standards of accuracy in the processes.

The main challenges of applying AI?

There are several challenges to apply artificial intelligence (AI) in companies. The first concerned point discussed above, the maturity of the company: its digitization of process and data readiness. Although many companies have data, it is often scattered and not so ready to use. It is necessary to analyze the data, clean it and prepare it for the application of AI. And often the company does not have this internal professional to do it. That's because it takes super qualified professionals in Business, BIg Data and AI to do it. Being the outsourcing of these professionals and technology is a great way to evolve fast.

And another important point is the change in organization culture, which implies a change in the mindset of people within the organization. It's needed to have people looking to problems with curiosity and ability to explore how the new technologies help solve problems. Otherwise, companies will not open up to improvement and innovation. It is necessary to develop people to have the cognitive flexibility to explore these possibilities and the agility to implement them.

“What we have seen is that many organizations, even working with innovation, when implementing new solutions, are unable to think about exponential technologies to change how they have being doing for ages. They fail to see the organization as a whole.” This limited ability to understand problems generates possibilities for automation as a patch and not as a process of true company transformation. They use technology keeping very restricted and limited, not extracting the best of technological possibilities. Again, it is the human who blocks the process of excellence of transformation.” Júlia Ramalho, DdF Co-Founder.

All these difficulties can be removed with a process of changes and implementations. It is possible to develop the solutions in stages. But if the organization does not take this seriously, it will never reach this maturity. It will continue doing things as it has always been doing, falling behind in the process of digital transformation.

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