A study found out AI adopters finds businesses face challenges in critical aspects of data management: preparing and cleaning data, integrating data from diverse sources, training AI models, and ensuring data governance.

Over the last couple of years, Adoption of AI is rapidly increasing businesses are pursuing embracing AI for their forces, yet it accompanies its own challenges AI has made its way to almost every boardroom discussion and very prominent brands across industries are leveraging it to drive significant revenues.

Essential Key challenges are:

Data quality and quantity-

Unstructured data, meaning a mass of data points with no explanation as to what they represent. This lack of context and categorization makes the data redundant for machine learning.

Successful AI initiatives depend on a large volume of data from which organizations can draw information about the best response to a situation.

AI/ML solutions cannot be created without data, a lot of data that is clear, correct, structured, and accessible. However, while enterprises do have volumes of data, it often falls short in terms of the other characteristics.

Enterprises are pursuing a range of AI initiatives and modernizing data infrastructure tops the list.

Right People and Talent

Finally, successful AI/ML adoption depends on having a skilled team of professionals who can work to create the right solutions.

I take time to evolve and requires constant creative and material investment till it matures and starts providing a level of acceptable accuracy. So not only do we need expert technological resources, but creative brains as well who can innovate the use-cases for the technology.

Solution

Be willing to challenge the status quo and more importantly build a culture where business teams can think about the use of AI in day-to-day operations.

Picking a task that fulfils any one or more of the above criteria is a great use case to test out your first AI/ML solution. That’s because, in each of these cases, a successful solution deployment will lead to very tangible benefits — better decision making, near-zero errors, or reduction in operating costs by eliminating resources employed in repetitive processes.

TransOrg Analytics can help to solve these areas Switch to the solutions discover more.

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