29 Nov Should I Use Artificial Intelligence In My Project?
Artificial Intelligence or AI is a hot topic right now and will be for some time. Every day we read new articles or hear news stories that talk about another company adding AI to their platform, product, or service. The hype is real, but is the value real?
AI stands for artificial intelligence. It is the idea of building a program that can handle tasks by itself and can solve problems without any human interaction. The technology has come a long way from years past were we only dreamed of what could be done with AI. Nowadays, we still dream but the dreams are becoming more real with every passing day. You see AI being used in so many places: email, navigation, ordering, ads, finances, and even in determining the proper formula for the best cup of coffee. It seems AI can do no wrong and if your project is to succeed it must be added in. This can be a dangerous thought process as adding AI into your project for no other reason than simply to have it would not be a proper implementation and may cause the ultimate failure of the product you hoped would change the world.
Make no mistake about it, AI can be a very useful tool and if implemented correctly can, indeed, change the world. The danger here is not having a proper direction for your implementation and simply trying to force AI into your project when the user is not quite ready for it yet. For AI to function properly it requires a long learning and training process. This requires either a lot of data or a very long list of questions and answers or sometimes both. AI should only be added where it can add value to the end user, and not be used as a buzzword for selling services.
What are the qualifications to look for to determine if AI will add value to my project? First off, would the AI be interacting directly with the user in some form or fashion? If so, what differences would the AI deliver compared to standard pre-programmed results? Do the results delivered by the AI add significant value to the end user over the pre-programmed results? These are questions that can help determine the proper implementation of AI within your project. An AI that does not interact directly with the end user can still be properly implemented. The main question to ask is: is the end user benefitting greatly by the results delivered by the AI over results without the AI?
Once you’ve determined that having AI added into your project is a benefit to your end user it’s time to take a look at how to actually get AI implemented and what would the cost be. AI done properly is not a cheap addon. It will take an experienced team to develop the training steps and build the AI platform. Building an AI platform from scratch is extremely expensive, but there are options. Platforms such as Watson or Apache UAM offer an AI as a service type platform that can make it cheaper up front to develop an AI and get it working on your platform. Talking to an experienced team is a great first starting point to finding out the various options that may be available to you on your specific AI implementation.