Outsourcing Web Hosting Support: 6 Reasons Why It Makes Sense
Posted on Jun 20, 2019
by Nitin Bhosekar (Head Analytics, Artificial Intelligence, BI Practice & Executive Vice President)

Artificial Intelligence and Advanced Analytics

For organizations, Artificial Intelligence (AI) promises a world of actionable insights and business improvements like none of the other technologies in the past. Sectors like technology, banking, financial services and retail are testimony to this, reaping the benefits as first movers in a tech-pervasive world.

“Data is the new oil,” says Intel’s Heiner Genzken. “On its own, data is boring. What you do with data is what makes it interesting.” Using artificial intelligence and advanced analytics, organisations are beginning to recognize potential hidden within data.

“Lack of identifiable data” and a “lack of skilled resources” remain key factors that slow down AI adoption within many organizations. These organizations need data scientists and machine learning experts to start with AI technology adoption.

These factors are followed by another challenge of “difficulties identifying use cases.” For such organizations, there remains a general lack of understanding of the latent benefits for AI to solve real-world business problems. Therefore, the focus shifts largely to adopting AI as a technology rather than applying AI as a tool to solve existing business problems.

Just as with any new technology, organizations are also in need of help to identify right use cases that could be considered as best-fit areas for development of AI solutions.

At Aress, we have worked with several organizations to identify use cases/ real-world business problems where AI/ advanced analytics could be applied. This includes identifying functional areas/ processes where AI application would provide better benefits e.g. in banking and financial services companies we have worked with, we have seen higher adoption rates for finance/ accounting functional areas whereas health sector companies use AI primarily for R&D and revenue tracking/ monitoring areas.

Few of the organizations we are interacting with are undertaking due diligence exercise to assess new business demands, prioritize technology application areas per use case, seek recommendations to choose building block technology/ies & resources, plan proof of concept and subsequent phased implementation.

For more information about AI/ advanced analytics and benefits of implementing it for your business, visit our website page for Artificial Intelligence and Advanced Analytics. And ask for free consultation by our AI/ advanced analytics experts or email us at AI@aress.com.

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Category: Analytics, Artificial Intelligence, Big Data and BI

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