Future of Business Analytics: Invisible Analytics and Embedded AI

Entrepreneurs can make informed mission-critical decisions on-the-fly using invisible analytics and embedded artificial intelligence (AI).

Businesses leverage data to capture remarkable insights about consumers. However, now it’s not the actionable data that matters the most for forward-thinking business leaders. Today’s cutting-edge executives one convenient access to information at the point of decisions.

Now, you can access invaluable insights when it matters the most. Invisible analytics and embedded AI can take you beyond using data to create compelling visualizations for later analysis. These latest big data innovations can help you react to events as they unfold.

The Current State of Embedded AI Analytics

Traditionally, organizational leaders review mission-critical business intelligence based on data analysis via a standalone dashboard. Now, invisible analytics and embedded AI are the newest best practice tools for mission-critical data evaluation, and there’s an entire vertical emerging around the practice.

Executives who use invisible analytics and embedded AI tools can access complex, granular analyses in real-time. The reports that the innovations generate are just as visually appealing as traditional big data visuals. However, these latest tools are a solution for accessing critical information right when it’s needed. Embedded AI is not only fast – it’s nearly instantaneous.

Traditional big data analyses have several drawbacks. For instance, it takes time to interpret the reports, no matter how visually compelling. Resultantly, they only appeal to a specific group of users who have expertise in using such reports for making strategic decisions.

Furthermore, traditional big data analyses are an entirely separate workflow for workers. In other words, employees must stop what they’re doing to perform a separate set of tasks required to review and use the information. Now, however, embedded AI systems present reports within existing workflows so that decision-makers have real-time insights into the current state of their business environment.

The Next Iteration of Analytics

To get a clearer understanding of how embedded AI works, think about what happened the last time that you browsed Amazon. As you navigated through the site, Amazon’s underlying technology presented useful information to guide you through the buying journey, and it wasn’t just random information. The Amazon AI system offered suggestions based on your behavior, and more than likely, the information influenced your decision making.

Now, apply this concept to the business environment. Embedded artificial intelligence can provide you with ideas to do your job better, in real-time and within existing applications. For instance, embedded AI or invisible analytics technology might suggest your next work activity or give you benchmarking information regarding your peers.

This kind of “suggestive analytics” has proven to improve employee performance considerably. Furthermore, it can also help organizations reveal effective best practices. So far, the technology has led to exciting discoveries.

In healthcare, for instance, care provider organizations are using machine learning to diagnose conditions such as skin cancer with greater accuracy. Furthermore, diagnostic equipment – when combined with artificial intelligence and other data sources – dramatically increases the quality of predictions.

Information Where It's Needed Most

Many healthcare organizations have realized the potential of invisible analytics and embedded AI. However, other verticals are just beginning to realize the potential of invisible analytics and embedded artificial intelligence. Still, the developers of analytical apps are beginning to leverage embedded analytics to deliver vital insights to enterprises.

Many of the business beneficiaries of the technology are acting on embedded analytics reporting without ever viewing an executive dashboard or data visualization. In a hectic work environment, few staff members have the time to break from their work to review a data analytics report.

Data that isn’t consumed and acted upon holds no value. Most employees want better information, but they need that information embedded within the workflows that they already access. Embedded AI empowers workers with actionable information, without the need to disrupt regular work.

Organizations that adopt data-centric practices reap phenomenal benefits. Most often, business leaders see returns in the form of increased employee productivity.

Invisible analytics and embedded AI will provide even more significant returns than big data systems. By presenting information when and where it’s needed, employees can take advantage of fast fleeting opportunities before they dissipate.

As enterprises become increasingly reliant on business intelligence, many employees will need to upskill employees to align their talent with organizational needs. Working professionals can bring their skills up-to-date by earning an online business analytics degree.

Lack of skills is one of the biggest problems that organizations face in adopting advanced data analysis systems. Fortunately for business leaders, they already have a wealth of existing personnel that they can upskill to lead their organization forward to a prosperous future using advanced data analysis tools.

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