How Does AI Work?

Artificial Intelligence (AI) works by processing large data sets with its advanced algorithms. The way that artificial intelligence is progressing, its goal can be summarized as building software capable of understanding and learning from human and data inputs and explaining a result with its output. In the process, it can discover patterns or features in the data. Artificial intelligence actually has many subdivisions, including:

Machine learning: This type of artificial intelligence makes use of neural networks to analyze data thoroughly and find hidden insights. This differs from normal programming because these networks are not really programmed or told what to look for or to reach specified conclusions. Machine learning operates through the discovery of patterns in data with programs and gradually improves the ‘intelligence’ of the machines over time.

Deep learning. Deep learning is similar to machine learning in the way that it also makes use of huge neural networks with multiple layers in order to comb through unimaginable amounts of complex data. The difference between deep learning and machine learning is that deep learning is generally used for much larger data sets containing complex data and more layers.

Cognitive computing. Cognitive computing tries to emulate human interaction with machines. The most visible applications of cognitive computing can be found in robots that are able to see and hear and respond to human behaviour.

Computer vision. This subset of artificial intelligence uses pattern recognition and deep learning to process hundreds of thousands of pictures and videos. Using pattern recognition, computer vision is able to understand the contents of the picture of the video. This also enables machines to be let out into potentially dangerous environments that are difficult to access for humans and take pictures or videos in real-time while also interpreting their surroundings.

To understand more about the implementation of AI in your business and how it can improve core processes with automation and machine learning, please reach out to IT Support New Jersey.

Top 4 Tips for Easier AI Adoption

Familiarity with AI

This essentially involves having the right kind of buy-in from employees at different levels of the organization. It is important for companies to remember that these people come from different backgrounds and work in varied job profiles, many of which may not be technical. But it is essential for all of these people to understand why artificial intelligence is required and must be implemented in the organizational infrastructure. They need to understand exactly how this will spur growth and help the company expand its services/ products at many different levels. They also need to understand exactly what the technology can achieve and how it is likely to move forward. This can be done in a top-down approach where the team leads familiarize themselves with the technology first and then implement a process of knowledge sharing so that everybody else on the team can get on board as well.

Detecting problems accurately

Once everyone on the team is on board with the basics of the technology, the organization should spend some time boiling down to the central issues and problems where AI can be used to chart out solutions. In fact, teams should try to brainstorm and explore the problem with different solutions in order to help integrate the current process with new ones. However, before adopting a new solution, the company must spend some time vetting the demonstrable value of the solution. This could be done in many ways, including finding used cases for similar AI implementation in the same industry or similar business. Managed IT Services New Jersey has more information on this.


Like any other technology a company may choose to invest in, AI needs to provide the business with ample financial value to justify its cost. With AI, a company may not be able to generate returns for quite sometime after its implementation - that's provided that the implementation itself has been successful. It may be overkill to estimate that the pilot projects may generate some revenue in such cases. At the same time, companies do not need to invest much in order to float pilot projects, and they always have the option to outsource it to AI and ML service firms. The experts at these companies can also help you determine the type of data that you should be collecting at higher volumes and even help you know your current gaps. Analysis may take time, but it paves the path for higher returns in the future with a strong knowledge base.

Make use of data-driven decision making.

A critical part of AI adoption in any company is the ability of a company to infuse data-driven smart insights into everyday processes and operations. This means that a company needs to invest time and energy into training people who carry out those processes and let them understand how data can make their lives and jobs easier. This applies across levels and ranks at any organization. With the right strategy for AI adoption, companies can expect their employees to be able to enhance their skills and be able to make better decisions thanks to algorithmic recommendations and an enhanced ability to achieve a better outcome than before. However, to achieve this, employees need to be able to trust the AI tools at their disposal and have adequate flexibility and empowerment to make decisions on their own. IT Consulting New Jersey can help with employee training as well as adopting the right strategy for AI implementation in your business.

About Chris:

Chris Forte is the President and CEO of Olmec Systems, which provides specialized managed IT support in New York City, New Jersey & GA areas. Chris has been in the MSP work space for the past 25 years. He earned his Master’s Degree from West Virginia University, graduating Magna Cum Laude. In his spare time, Chris enjoys travelling with his family. Stay connected via LinkedIn.