The age of AI is upon us and many companies begin to start their AI journey and reap the full potential of AI in their respective industries. But, some still consider AI as an immature technology with plenty of ways for it to go wrong. Therefore, before starting your long AI journey, there are some pitfalls you should avoid in implementing and developing AI solutions. They’re a result of the anecdotal, personal and published experience of AI projects that could have gone better.

1. Building AI systems that have become industry standards

Reinventing the wheel, that’s the reasonable words to describe building an AI system that has become an industry standard. It is a waste of your company’s time and resources. Instead, buy it from a company that has done research and development for years, and has launched a product that has been used and trusted by ample of users. Embrace their solution because this buy decision can get you high-quality AI services at a fraction of the cost and time that it would take to develop in-house. Because building an AI system in-house is a costly and risky endeavor, only do it if the AI system is quite specialized to your business and allow you to build a unique defensible advantage, something that can differentiate your company from its competitors.

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