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11/27/2020
By
MJV Team

Waiting can be expensive: why to invest in artificial intelligence.

Organizations from all sectors are investing in Artificial Intelligence (AI) tools and techniques to, among other actions, automate processes and serve their customers better.

Data from a Markets and Markets survey estimate the AI ​​market to reach $191 billion by 2025. You have certainly seen this movement, and you may be wondering if Artificial Intelligence is important to your business and why to invest in it.

This article brings that reflection. Keep reading to understand the importance of investing in AI, how to get this technology into your business, and more!

What is Artificial Intelligence

Let us start by remembering the concept of Artificial Intelligence. 

Gartner defines AI as: “a technology that seems to simulate human performance typically learning, reaching their conclusions, seeming to understand complex content, engaging in natural dialogues with people, improving human cognitive performance (also known as cognitive computing ) or replacing people with non-routine tasks.”

In summary, we can say that this technology’s central challenges include programming devices (computers, machines, objects in general) and applications (systems, platforms, etc.) for specific characteristics, such as knowledge, reasoning, problem-solving, perception, learning, planning, ability to manipulate and move objects, etc.

What benefits does Artificial Intelligence offer?

Perhaps the most apparent and short-term gain that Artificial Intelligence offers companies is taking automation to an even more powerful instance. Artificially intelligent solutions increase performance, optimize the operational routine, and provide more time to take care of the strategy.

The following is a breakdown of the main benefits of AI for companies.

AI powers business decisions

An Artificial Intelligence software can provide synthesized courses of action and present them to the user. In this way, users can use it to eliminate the possible consequences of each action and simplify the decision-making process.

This is the case with the use of mechanical vision systems to identify potential cancer cells. In this way, radiologists can focus on genuinely critical points, communicate with patients, and coordinate with other doctors.

Makes machines learn and evolve

Machine learning is often used in systems that capture large amounts of data. For example, intelligent energy management systems collect data from sensors attached to various assets. 

In this case, the data sets are contextualized by algorithms and delivered to human decision-makers to understand energy use and maintenance demands better.

Another example is the reinvention of Amazon’s call center workflow and layout. It was achieved after the introduction of robots and optimization algorithms based on machine learning.

Facilitates fraud detection and increases machine autonomy

Another breakthrough brought by AI is deep learning, a more powerful version of machine learning that relies on neural networks to engage in nonlinear reasoning. 

Deep learning is essential for the performance of more advanced functions, such as fraud detection, for example. This can be done by analyzing a wide range of factors at once. 

Another example: for autonomous cars to work, several factors must be identified, analyzed, and answered at once. Deep learning algorithms are used to help autonomous vehicles to contextualize information captured by their sensors, such as the distance from other objects, the speed with which they are moving, and a prediction of where they will be in 5 to 10 seconds. All of this information is calculated side by side to help the vehicle make autonomous decisions, like suggesting a lane change to the driver, among others.

Takes information security to the next level

Artificial Intelligence is an indispensable ally for looking for security breaches in the computer network. Due to scale and increased complexity, cybersecurity experts are being replaced by automated AI platforms.

Increases intelligence in the systems

AI is also changing systems in general, making them more powerful and smarter. This is the case with customer relationship management (CRM) platforms. 

Standard CRM software requires massive human intervention to stay current and accurate. But when you apply Artificial Intelligence to these platforms, they become systems of self-realization and self-correction that remain in control of the relationship with the target audience.

Modernizes financial services

Another example of the versatility of Artificial Intelligence is in the financial sector. For example, TD Bank recently worked to integrate AI into regular banking, such as mortgage lending and customer support. 

The bank created a chatbot that uses AI combined with transaction data to provide information on spending, credit cards, help with everyday transactions, and answers to frequently asked questions.

Artificial Intelligence and data governance: a perfect combination

Finally, in addition to understanding the advantages listed above, you must think of Artificial Intelligence in a bundle with data governance. This will help you understand the importance of investing in this technology.

As we know, data governance helps manage five things better: availability, usability, integrity, and security of its data. By using the right technologies, like Artificial Intelligence, data governance can drive values ​​and support business transformation. Technically speaking, it includes:

  • Data security: protect your data against unauthorized use with solutions that do not require human intervention;
  • Data loss prevention: your customers trust you to manage their data. You need to ensure that confidential data is not lost or used outside of your company. Imagine that Facebook is sharing its data with its client and doing things with his data against his will? Oh… never mind! You don’t have to imagine.
  • Data integrity: ensuring that data is accurate in systems and usable;
  • Data integration: combining data residing in different sources and providing a unified view of them;
  • Data lineage: tracking the data source;
  • Data completeness: analyzing how complete is your data?

In short, Artificial Intelligence is not a simple investment; it is a long-term competence. Therefore, it is important to seek specialized help to understand how to include this technology according to your business.

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