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How Do You Get Started With AI as a Business Initiative?

Whether you’ve newly started a business or are looking to improve your existing operations, you probably didn’t wake up one day and think, “I could really use some artificial intelligence.” More likely, as a manager, executive, or other business user of technology, you’re looking for ways to leverage data insights to help you make better decisions, manage your team’s priorities, and get an edge on the competition.

All too often though, business leaders find themselves or their teams sorting through disparate data and rolling up reports and dashboards, only to come up short on actionable insights. Enter AI, the disruptive force that promises to change industries over the next decade.

Getting Started With AI

But how do you navigate through the vendor hype and industry claims around AI and machine learning to actually transform your data, systems, and platforms into actionable data intelligence and insights?

You may also be wondering: How do I get started? Is my data ready? Do I have good quality data to support new models? Do I have to perform a big data re-engineering project? Do I have to do an enterprise data transformation? The answer to all the above is a resounding “no.”

Strategic Business Goals Still Drive Where We Focus AI Efforts

We are going through another fundamental shift in enterprise technology solutions. Enterprise systems such as ERP, HCM, and CRM were designed to be a system of record for entering data and creating dashboards and reports. At the turn of the century, the advent of cloud, social, and mobile provided a more agile system of engagement and opportunity for collaboration, as well as access to data anywhere — though user adoption can still be a challenge.

Today, by leveraging machine learning and data analytics, these systems can now give back to the end user with a higher degree of automation in the form of recommendations and notifications. By driving a better end user experience, this in turn creates a virtuous cycle, as adoption improves. When the systems are providing value and feeding actionable intelligence back to the end user, they are more likely to use the system as intended. With better end user experience and better business outcomes defining our efforts, we can confidently embrace the transformative and predictive power of AI and machine learning.

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