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What’s Holding Back Enterprises from Adopting AI?

By Redapt Marketing | Posted on January 9, 2020 | Posted in AI/ML

Artificial Intelligence (AI) has graduated from buzzword to technical reality. For many enterprises, however, large hurdles remain in actually adopting AI into their businesses.

There are a number of reasons these hurdles exist, but they can all be summed up with a single statement: adopting AI is hard. Not just technically, but culturally as well.

Here are three reasons enterprises are being held back from adopting AI, and steps you can take to get past the obstacles.

Download Now: The Enterprise’s Guide To Beginning The AI Adoption Process

1. A mess of data

AI requires a large data set to be effective.

While cloud platforms have made storing and utilizing data much more efficient and cost-effective than most on-premises solutions, ensuring your data is properly organized and findable can be a challenge.

The key to remedying this problem is to take deliberate steps to make sure your data is squared away before launching an AI project.

4 steps to cleaning your data:

  1. Make a plan to figure out what data sets you want to use
  2. Analyze those data sets to drill down on useful data and identify any gaps you need to fill in
  3. Fill in missing data, either on your own or through a third party
  4. Monitor your data sets regularly to ensure proper organization and new variables can be included as your business evolves

2. Going too big too early

Many AI initiatives get their start with data scientists, which tend to be on the smaller scale. But there’s also a tendency for enterprises adopting AI to try to accomplish too much at the beginning.

AI isn’t something you simply throw at a problem. Properly adopting and implementing AI takes a series of steps, from pinpointing what exactly you want it to achieve to ensure you have the right infrastructure and platforms in place to scale properly.

Your first AI project should be something on the smaller size, such as chatbots to assist customers or analysis for certain data sets. These projects should be isolated and specific until your enterprise has the expertise and foundation in place to expand AI usage. Remember, adopting AI is a marathon, not a sprint.

3. Internal culture

AI is complicated to implement effectively. It can also be complicated to explain, especially to areas of an enterprise that are not the most tech savvy.

To get over this cultural hump within your enterprise, you should lead with the business benefits for AI, such as:

  • Automation taking over mundane and repetitive tasks like data entry or updating records, which frees up more time for employees to be creative.
  • Data analysis via AI to efficiently sift through large amounts of data to help drive better business decisions and products for customers.
  • Improved and more cost-effective customer service with AI-driven chatbots to answer questions quickly and at all hours of the day.

Gain clarity on AI adoption by downloading our free eBook, The Enterprise’s Guide To Beginning The AI Adoption Process.

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The Enterprise Guide to Kicking Off the AI Adoption Process

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