Q1: In order to build a recommendation system, I need an artificial intelligence engine that will take a look at my data and discover the recommendation patterns for me automatically.

Answer: False. Recommender systems can be based on business knowledge that your staff already have, a visual pattern you discover while browsing the data, or some kind of algorithmic machine learning process. All three can provide meaningful recommendation patterns for your business applications.

Q2: Recommender systems can only be applied in an Amazon-style retail environment, where you have a massive amount of data to base your recommendations on.

Answer: False. Recommendations are useful in many different business domains, not just retail product recommendations. Fraud detection systems (I recommend that you put this person in jail) are just one example of a business application that has nothing to do with retail but that will use the same pattern matching capabilities for detecting these more complicated fraud cases.