5 Challenges Faced by Enterprise Artificial Intelligence

 

“The pace of progress in artificial intelligence (I’m not referring to narrow AI) is incredibly fast. Unless you have direct exposure to groups like Deepmind, you have no idea how fast—it is growing at a pace close to exponential. The risk of something seriously dangerous happening is in the five-year timeframe. 10 years at most.” —Elon Musk wrote in a comment on Edge.org

 

And now, it is proven with the hundreds of enterprise applications around us. How stunning changes they have made in the way we operate, monitor and do business. Yet, I would still say – This is just a start of Artificial Intelligence, it is a baby phase which is yet to see the peak days!

 

But as we grow our AI capabilities and applications, what are the odds that business owners are still facing. Let us see the core five challenges that come in the way of AI to make an impact!

 

 

 

 

Customer expectations

What is the ultimate goal of any technology – it is to make a difference in their customers’ mind and experience in a positive way. Hence, it is important to build the trust that will ensure your customers of an easy yet enhanced experience.

 

 

 

 

 

 

 

 

 

Lack of quality data

Data is the fuel of Artificial Intelligence! AI improves itself with deep learning and quality data. But, quality data is not as easy to gather. And, even if you do gather, the consistency is not maintained. Rather, a lot of data could be just filled due to the sake of obtaining an access to specific data.

 

 

 

 

 

Implementation time

AI applications are not easy to deploy! The amount of resources and time consumed is huge for AI applications. Industry needs to overcome this development-to-market time to make actual impact ROI-wise.

 

Governance and regulation

Artificial Intelligence is set to take over the work and jobs of their human associates. Building a world where a robot can do a job is not something that our world is ready for, especially when many are still trying hard to increase employment rates.

 

Lack of supporting IT infrastructure

As AI grows, its infrastructure needs grow as well exponentially! Thus, it is important to support it with the appropriate infra. The infrastructure should be cost-effective and scalable for longer run use! There are very few such options available. IBM offers enterprise servers named Power Systems that are especially designed to support AI applications.

 

Thus, for any AI application to run as expected the functionalities, quality data input, policies and infrastructures should be thought through, enabling a successful enterprise project!

 

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