OnPassive GoFounders For LIFE

There are hundreds of ways
AI and Machine Learning are being applied in today’s companies to drive more
employee engagement. From extracting insights from current performance data to
automate tedious tasks to eliminating bias and enhancing diversity in the
workplace, today’s companies are quietly being revolutionized by the proactive
and pragmatic application of AI.

The adoption of Machine
Learning and Artificial Intelligence into the boardrooms of the major
corporations has given rise to a new era of business leadership, one
characterized by accurate and timely decision making, real time execution of
key priorities, and increased profitability. This is particularly exciting for
smaller companies that have traditionally had trouble achieving top levels of business
success due to the “learning curve” associated with the evolution of
management principles and business culture.

The future of Employee
engagement

Companies that are best
suited to embrace Machine Learning and AI will most likely be those with the most
expertise in working with a wide variety of people, tasks and information. They
will also need to be rapidly adapting to changes in labor economics-the gap
between demand and supply in labor markets that have been generally flat over
the past fifteen years is increasingly narrowing, even in the face of global
competition.

Additionally, companies
with a strong competitive advantage will enjoy solid returns on investment
because they can pass on higher labor costs to their customers. For these
reasons, top executives at large companies have spoken candidly about the need
to focus on improving employee engagement. If these leaders are to be believed,
then we may soon witness a wave of major corporate initiatives centered on
solving some of the most fundamental challenges associated with engaging
employees and building organizational culture.

Gauging Employee Engagement

Currently, many of the
largest companies in the world have been measuring employee engagement through
the employment relations function of human resources departments. While this
has proved to be an effective way for firms to determine whether or not their
workers are satisfied with their jobs, this type of survey does not provide
enough details for executives to make informed decisions about engagement
levels. For example, it does not indicate what types of activities and
relationships within the organization foster greater employee engagement.

This gap is expected to be
addressed by newer organizations like ONPASSIVE in the future. These consulting
firms are currently collaborating with artificial intelligence technology
developers to build new technologies that will allow businesses to determine
more specific aspects of employee engagement. In this way, organizations can
begin to address problems like low employee participation rates without taking
the potentially complicated steps of implementing complex logistical plans.

Understanding the rift in
employee engagement with AI

Companies that can measure
and improve their supply chain performance can better anticipate problems
before they occur, which can prevent a number of issues such as over-producing
or under-utilizing key materials or services. Ultimately, firms that make use
of detailed logistics data can reduce the potential impact of policy changes
and operational glitches on their businesses, allowing them to better manage
their operations and avoid costly mistakes that impact employees.

Organizations can also use
detailed logistics information to learn about worker demographics and
behavioral patterns. Data from a variety of sources can allow managers to
evaluate and create work environments that promote overall engagement. It has
been shown that employee turnover rates increase when certain factors are
present such as an unhappy work environment. According to Kornblum, A.I.
software can be used to collect information from various types of sources,
including social networks, online surveys and off-site visits by employees.

Surveys for employees

To that end, organizations
can also use A.I. software to provide an employee survey that collects
information on the experiences of new hires. A survey like this can gather
information on the types of problems employees have encountered while working
at the organization as well as how these problems were handled, the
relationships with management and other co-workers, and overall satisfaction
with the organization. Kornblum believes that a comprehensive survey can help
managers identify areas in need of improvement, as well as provide insight into
the reasons why employees leave companies for other opportunities. Measuring
organizational burnout and engagement can help managers prevent organizational
crisis, such as what happened to Yahoo! recently, or what led Microsoft into
the arms of the cloud, according to Schaufeli et al.

Conclusion

It is
needless to say that employees make the backbone of any organization. It cannot
sustain with a set of unsatisfied employees. With intricate data curation to
understand the psych of an employee and improve every experience, AI can bring
in a new level of employee engagement. There are various HRMS tools like
ONPASSIVE O-Staff that come with special features to address employee concerns
and run survey while accumulating data to understand every employee needs. If
you are a business and have employees that you depend on then it is a good idea
to scale up with a great tool for employee engagement assessment.

The post Driving Employee Engagement with AI first appeared on ONPASSIVE.