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.