Why do most AI projects fail? Something which many people do not know, is that up to 90% AI projects lead to failure. And this is not only for AI, this is for IT projects in general.

This might sound weird coming from a company specialising in data science and AI. But that’s the reality, and this is why the Tesseract Academy was created: to ensure that all organisations can enjoy the benefits of data science and AI, ,without the risk of implementation.

So, let’s see some of the reasons that lead to most AI projects being unsuccessful.

Not having a data strategy in place

This is probably the number 1 mistake that organisations and leaders make. Not having a data strategy roadmap, is the equivalent of starting to go on a trip by travelling towards some random direction. A data strategy roadmap ensures that the organisation has set in place the northern star, the KPI that the data science project is going to optimise. This can be anything, from improving efficiency to solving a particular challenge. It is also important to understand whether your goal with data is to play offense or defense, something which we discuss more about on this post.

The Tesseract Academy is also running a free on-demand webinar on data strategy which you can watch here.

Lack of a data science culture

Data science culture is one of the most important aspects of any company that wants to use data science. This is why the Tesseract Academy has been evangelising the importance of culture in data science for a long time. Many leaders are confused by the difference between data-informed and data-driven, something which we talk more about on this infographic.

In any case, having the right culture in place, means that you can rip the benefits of working with data scientists. If this is not set in place, then it is likely you will end up wasting time and money. That’s why we are also covering the topics of building the right culture and hiring/managing data scientists in one of our online-assisted courses (which also includes 1 free our of coaching).

Not being really understanding what AI can and can’t do

Many leaders are simply lost, and are not sure what data science and AI can do. Quite often they have the wrong expectations: they either expect way too much, or they expect the wrong thing.

The only way to cure this problem is through education and ownership of the data science process. This is why the Tesseract Academy is providing so many different valuable and free resources to help decision makers (from executives in FTSE100 companies to solo entrepreneurs), correctly identify the potential of data science and AI.

If you go to our free resources section you will find links to both the AI Case Studies Bible and the Decision Maker’s Handbook to Data science. Or you can simply register to our newsletter below and get instant access to both documents.