AI - The Introduction
Your cloud initiatives are humming along, moving to the cloud. You are seeing a greater uptime, faster response times for your client's portals, easier to deploy security services and your advanced cloud initiatives such as adopting AWS RIs for steady-state usage and Azure Kubernetes for better container management. You feel good. You sleep better knowing that you finally have a handle on this cloud thing. And then you wake up, get on your Linkedin, and see an article about AI. And another on Edge Computing. More about IOT and 5G. And you say to yourself, "well, the cycle of tech innovation has marched on once again." and you drink your coffee (or tea) and get ready to dive back into learning. I would like to help and this series of articles is meant to get you thinking about the wave of technology we are in.
Welcome to the Intelligent Era.
AI (Artificial Intelligence) has been an idea that has been around for a long time. Science Fiction promised us AI for such a long time that it is almost viewed as flying cars, a dream that may never come to full fruition. And if it did, it would be disappointing. Well, flying cars still aren't there, but AI is. Years ago, many companies invested billions into machine learning in different areas such as data analysis, real-life object recognition, and process improvement. Machine Learning is the first stage of true AI, it is teaching machines how to learn based on methodologies such as teaching it the rules and letting it decide how to follow them, or telling it the desired result and watching the path it gets there. These investments into machine learning can take years to produce any kind of return on the investment but they now have now come to fruition providing vehicle automation, task automation, and optimization, while also finding patterns and analytics from data that no one ever realized was there. AI can even create people that don't exist.
With these advancements and the wide breadth of services offered by AI it can be daunting to see how best it fits into your current ecosystem. The first step to answering that question is to decide what you want AI to do for you. Are you looking for a virtual assistant to help visitors to your website where AI can use natural language to interact and direct your clients? Or are you looking to streamline your ticket system and have AI discover what is the most commonly asked questions to solve, and then have AI automatically solve those tickets for clients, or escalate them if human interaction is needed? Or are you looking for AI to identify issues in your infrastructure or streamline your internal business processes?
Make sure to define your issue before looking for an AI solution.
Once you have defined the problem you would like to solve, you have to be prepared to have data collection be in place or access previously stored data as the more information AI applications can collect the better they will get. However there is a new push to center Big Data and by extension, AI, to have a more meaningful collection of data to analyze. As data collection has become more and more pervasive, users are becoming more educated about data privacy and are pushing back on mass bulk data collection. Users are willing to give up data, they just want to make sure you are only collecting what you need and that the user receives something in return. In addition, analyzing large datasets can become such a task for AI that by the time you start seeing results, the scenario has already changed and the information becomes outdated before it could even be implemented. When exploring AI vendors, ensure that they understand the concept of meaningful data collection and have taken steps to control their data collection without handicapping their AI. Less is more.
AI has now reached a stage of production that you don't have to start from scratch with machine learning to best utilize AI. Companies like Computer Associates - Operational Intelligence uses AI to provide a better IT infrastructure management solution, identifying possible issues before they crop up and help you reach the root cause of an issue faster than before. Combined with a tool like Streamweaver gives CA a full view of your infrastructure even from datasets that don't integrate easily into a single platform. Improving your business processes can be as easy as contacting Arago to implement their AI which will integrate and learn before offering optimization recommendations based on the algorithms developed via its machine-learning phase.
AI is a technology within the reach of your company and can become a true source for change within your organization.
Cross-posted at EA Team - Digital Experts