AI and IT: A Natural Match

Cybersecurity

Artificial intelligence is being used to make automated systems smarter. As this automation ?learns? how to be most effective, it can be used for a litany of purposes. One of the main purposes where AI is already being utilized is in cybersecurity. The results have been mixed thus far, but one could see how AI?s role in cybersecurity will be profound in the future. The truth is that since the technology is still very much in its infancy that the application viability with something as complex as cybersecurity isn?t helping mitigate some of the most dangerous threats.

That?s not to say that today?s AI doesn?t offer some value. According to the Ponemon Institute, AI is already affording businesses cost savings, a reduction of data breaches, and higher productivity tied to system viability. They found that companies have been able to cut their cybersecurity budgets by nearly 65%. Another benefit AI is currently providing businesses is that it makes up for what is a long-standing industry shortage in talent. With companies relying on so few IT onboarded technicians, simple issues can be quickly remedied before they become problems; and, coupled with analytics it can help the IT professionals that companies rely on, pinpoint where (and what issues) to analyze further.

Operations

Most businesses today rely on their IT to conduct operations. Distribution companies that rely on asset and fleet management, to manufacturers that use dedicated supply chain management, to the office where customer relationship management solutions are typically used to sync business with the demands of their customers, all need powerful software solutions to help keep costs down and keep business moving fast. AI is beginning to help these automated systems work more effectively.

Most of AIs work within these constructs has to do with managing data and its analysis. Since so much data is created within these systems–especially in systems that also deal with the dissemination of services- it is hard for people to sort through it all. AI-enabled analytics systems are now being used that can automatically go through the mounds of data to find helpful information that can be used in the day-to-day application of business.

Another place AI has begun to be utilized is in payment systems. For all the tech that many businesses use, their supply procurement and customer invoicing strategies are largely paper-based. When all other parts of a business is streamlined, having such crucial parts wasting time, being rife with errors, and causing inefficiency is not helping the business. AI systems are being used to sift through the documents and properly invoice customers in ways that were only capable through human labor only a short time ago.

How Can I Use AI?

This question is both laughable and sincere, much like the technology we are talking about. AI is nowhere near what you may think it is, but that hasn?t stopped some businesses from looking to incorporate artificial intelligence for IT operations (AIOps). The truth is that AI–that is, artificial intelligence–probably won?t help your business right now. The technology is way too new and it?s only been in the last couple of years that major software developers have been interested in creating products with modern-day AI technology.

That shouldn?t alter your strategies to find the best solutions you can to eliminate business problems, and if they incorporate AI technology, then great, but rolling out your own AI to solve operational inefficiencies, is currently rare, since the AI isn?t particularly ready to build the kind of cost-saving automation that many vendors are currently advertising.

If you cannot wait, however, the key to making AI systems work for IT operations is that you need a plan. Gartner suggests that any business looking to incorporate AIOps should plan an implementation that focuses on four phases. They include:

• Establishment Phase – This is where the company selects a small number of key business applications and properly inventories the data sources that flow into them.
• Expansion Phase – Expand the number of applications under the AI?s thumb while setting up systems to share data and analysis both outside of IT (reporting) and with business administrators.
• Reactive Phase – Build a structured database of all processes, implement visualization and language access to data, while also deploying statistics-based analysis.
• Proactive Phase – Implement data streaming and ingestion to conduct root-cause analysis of complex business problems and engage in predictive analysis.

We get if this is way over your head. If you are good at your job (and you aren?t an AI expert), you probably don?t need to understand any of it. The point is that AI is a growth industry and that you should leave these technologies to the experts. At White Mountain IT Services, we look forward to the day where business-friendly AI helps our clients do much more for less, but until them we will be here to support you with the innovative solutions you expect from your one-stop IT provider.