Artificial Intelligence, or what popularly known as AI, is successfully used in many specialised domains. Great AI begins with great data. AI is beneficial as it deals with real-world problems. However, building AI is highly challenging as it’s an iterative and evolving process where one size does not fit all. AI gives the best results when it continually learns from and is trained with an enormous amount of data and human feedback. This means an effective AI-based platform must continuously learn for the correctness and maximal value.
AI-based platforms and services also face a few non-technical issues. These are some possible challenges:
- Understanding AI’s limitations
AI is only as good as the data we feed it with. Data sets may have biases and exceptions. AI generally learns from historical data and patterns. So, when there is no data or pattern, there is no AI. Take the global pandemic COVID-19 for consideration. There was no way to predict the timing of the pandemic outbreak.
Companies need to decide in what way to adopt AI. Replacing humans with AI can work in some instances, but it also has the potential to backfire when the variables and range of services defer from one client to another.
- Lack of understanding among non-technical employees
For a successful application of AI, business understanding is as important as technical knowledge. Unfortunately, it’s either former or the latter. This hinders the adoption of AI in many fields. Many small and medium enterprises fall short of the budget to outsource an expert team. The ones that can deploy an in-house team are skeptical about the technical knowledge and skill set of the candidates.
- Assessing vendors
Lack of technical knowledge might result in vendors without any expertise trying to mislead companies. The ideal thing to do would be to conduct thorough research to identify leaders in the industry before hiring one. One can start by examining the portfolio of the vendor. Some vendors also have demo sessions as workshops to help organisations make buying decisions.
Solutions with huge benefits don’t come easy. All one has to remember is that the more familiar you are with the technology, the better. Once you have a well-thought strategy in place to decide what business problems can be solved with AI’s assistance, the whole process of AI implementation becomes smooth and easier.