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Artificial Intelligence (AI) has long been regarded as the basis of science-fiction
fantasy. But technological advances in recent years have given rise to AI applications
in everything from automobiles to personal digital assistants. As the technology
continues to evolve, companies are finding new ways to use AI to help automate parts
of their businesses. It only makes sense, then, that AI is poised to have a huge impact
in automating business process management.
Corporate executives and managers at all levels
of the enterprise need to ask themselves how
they can streamline and automate processes
throughout the business in order to increase
productivity and respond quickly to shifts in the
marketplace. Digital transformation is widely
regarded as table stakes for any company that
wants to survive, much less succeed. But the
creation of competitive advantage goes much
deeper than simply making sure you have the
latest technology at your disposal. It means
finding ways to automate processes and reduce
redundancies at all organizational levels − from
the C-suite to the front line − in order to make your
business more efficient and responsive to change.
When done right, it creates the foundation for
a more agile organization that can adapt as
technology, society and competition evolve.
AI is often considered to be the future of
computing and possibly the greatest driver
of innovation in the next decade. Already it
is showing up in autonomous vehicles, voice
controlled digital assistants and devices with facial
recognition. This is just the beginning. The power
of AI to augment human capabilities and change
our perception of business problems is gamechanging
when we look at how it can be applied
to processes throughout an organization.
In many ways, AI is a natural partner for business
process management efforts. AI can help automate
routine tasks, improve user interfaces and analyze
large amounts of data. The data analysis, machine
learning and predictive analytics capabilities
of AI make it possible to automate many basic
decision-making processes in an organization.
The consultancy McKinsey & Company estimates
that AI can automate as much as 45 percent or
more of any particular job, allowing workers to
focus on higher level mission-critical activities that
cannot be as easily accomplished with technology.
But what problem is AI really trying to solve? The
traditional top-down business model no longer
applies in today’s fast-changing business climate.
Each person within an organization needs to be
able to solve their own problems. This means that
companies must empower a broader group of
workers in the organization to develop solutions
to meet their business needs. By moving this level
of decision making further into the line of business,
companies streamline deployment of efficiency
and creativity. Employing AI in this process makes
it possible to predict what needs to be done and
be proactive in the process by analyzing patterns
in historical data and anticipating any roadblocks
or constraints in the process.
There are a number of barriers to implementing
AI on a wide scale. Most notably, the cost of
developing AI applications is prohibitive. With
fewer than 10,000 accomplished AI scientists
in the world, the cost of employing AI specialists
is beyond the reach of most IT organizations.2
Instead, companies like Google, Microsoft and
Amazon, which have the resources to pay the
high salaries commanded by AI engineers, are
leading the industry in developing the complex
AI algorithms and the APIs that will allow business
software developers like K2 to integrate the
technology into their own platforms.
Using these tools to add AI to existing BPM
tools helps reduce the amount of time spent on
certain tasks, improving customer experience and
reducing costs − without building a pool of data
scientists and data modeling toolsets in-house.
This cost-effective approach opens up at least two
broad categories of AI benefits to users deeper
in the organization: natural language interfaces,
and data-driven insights derived from the larger
context in which the business exists.
AI-driven natural language interfaces make
interacting with the application easier and speeds
up the process. The AI interface could automate
many of the steps just by understanding the words
spoken and the business context of the request. In
addition, AI and machine learning make it possible
for the application to learn from each interaction
and streamline the process for the next time.
One major advantage of AI is its ability to employ
natural language responses, conversational
dialogue and language translations along with
the ability to gauge intent to streamline and
automate common tasks such as filling out
forms. AI can analyze key phrases within the text
of a user’s request to get an idea of a person’s
intent and automatically fill in a form with the
AI’s machine learning component will have a huge
impact on productivity. With each interaction, the
system acquires more data about how decisions
are made and applies statistical analysis to develop
rules around decisions and how they are made.
Productivity gains are achieved because machine
learning looks at historical data and uses predictive
analytics to spot trends and make business
decisions based on this data.
It is helpful to look at how this technology might
play out in a practical application. The primary
critical asset of any company is its workforce.
The amount of paperwork involved in managing
employee schedules and processing time off
requests can be a challenge for even the most
efficient human resource departments. This is an
area that AI can help improve efficiency. Instead
of having to sit down and manually complete
a form, employees can simply speak to their
computers or devices and specify the dates they
want to take personal time off. The AI interface
will understand the context of the request, access
data regarding an employee’s schedule, approve the request and automatically complete and
submit the form. The AI-enabled business process
management (BPM) application can also access
data regarding upcoming events, such as critical
customer meetings or other potential conflicts, and
suggest alternate dates that would be a better time
for the employee to take time off.
In this case, AI goes beyond simple voice
recognition. It must actually understand the context
of the request and take into account an employee’s
life, schedule and their role in the company and
apply the appropriate business process rules
to the situation.
BPM for healthcare is another area that AI can
have a huge impact by helping doctors and nurses
capture information about a patient’s symptoms,
medications and other health issues, organize this
information, and fill in the appropriate forms. With
natural language processing, doctors can simply
speak to a device that translates and interprets
the information and automatically fills in the
appropriate forms. By eliminating the need to
manually enter the information, AI would improve
productivity by saving time and reducing errors
and ultimately saving lives.
While AI still has a long way to go before
it becomes completely integrated into
business processes, organizations need
to take steps today in order to be
prepared to successfully implement AI
in the future. The key to this success is
data. AI depends on data − lots of it −
and companies need to digitize their
processes today to capture as much
of that data as possible for tomorrow.
Companies already using the K2 platform
will be able to integrate the historical
data captured within their applications
to populate future AI applications.
Combining the power of K2’s process
automation platform with AI interfaces
empowers business managers to develop
their own solutions while freeing up IT
resources to focus on higher-level issues.
As AI continues to move out of the
realm of science fiction into real-world
applications, companies that embrace AI
as part of their ongoing digital evolution
will be the real winners.
How will AI help transform your business
processes? Let’s find out together.
For more information or to request
a demo, visit K2.com.