Intelligent Automation Week Chicago Blog
There are undeniably a ton of questions about IA Centers of Excellence (CoE) within the intelligent automation (IA) space.
Check out the three case studies below to find out how artificial intelligence and machine learning technologies are being used to drive more intelligent business decisions.
Let’s take a look at why certain RPA initiatives may fail and what you can do to course-correct to avoid further challenges.
The use of data analytics will only continue to grow in the future, as it is a necessary tool for organizations to use when it comes to making big business decisions.
Let’s take a look at five AI-based tech advancements that are driving intelligent automation to be even more intelligent.
Effective change management can reduce the delivery risks of implementing IA technologies such as artificial intelligence, machine learning and robotics process automation. To ensure the success of your intelligent automation program, try leveraging these tested change management strategies.
Despite today’s digital-first world, companies struggle to process the vast number of forms, scanned images, and more that move between businesses and customers every day. Organizations spend roughly $57 billion on data entry each year, and that number is growing.
Regardless of what industry you are in, the potential for intelligent automation is massive.
Ever notice how the personalities and dispositions of circus and carnival performers often resemble co-workers in an organization?
A managerial movement is now in motion and picking up steam. It is the application of business analytics for organizations to gain insights to determine good decisions and the best actions to take.
Cloud computing has been in existence since 2000. The goal of it is to allow users to take benefit from all of these technologies, without the need for deep knowledge about or expertise with each one of them. There are three main models of cloud computing and many benefits.
Analytics is becoming a competitive edge for organizations. Once being a “nice-to-have,” applying analytics is now becoming mission-critical.
The first thing you need to assess is what your largest issues
are currently which have the potential to be addressed with automation.
Machine learning is a sub-field of artificial intelligence. Its goal is to enable computers to learn on their own. A machine’s learning algorithm enables it to identify patterns in observed data, build models that explain the world, and predict things without having pre-programmed rules and models.
What we talk about when we talk about automation is reducing the need for humans to be involved in a particular task. This is for a variety of reasons: increasing safety, increasing precision, reducing cost and increasing output.
A Conversation With Our 2018 Keynote Speaker: Michael Rogers, MSNBC’s “The Practical Futurist” (Part 2)
In part 2, get to know one of the nation's leading experts on the
impact of technology on business and society a little bit more. You'll hear his thoughts on bots, AI bias, and more!
solutions utilizing AI and machine learning can greatly reduce the amount of
time needed for threat detection and incident response. These technologies help
reduce and prioritize traditional security alerts.
A Conversation With Our 2018 Keynote Speaker: Michael Rogers, MSNBC’s “The Practical Futurist” (Part 1)
Get to know one of the nation's leading experts on the
impact of technology on business and society – who was the keynote speaker at
Intelligent Automation Week 2018. Mr. Rogers is the
Futurist-in-Residence for The New York Times Company, as well an interactive
media pioneer, novelist and journalist. He also writes the popular Practical
Futurist column for MSNBC.
China and the United States are ahead of the global competition to dominate artificial intelligence (AI). However, China is aggressively executing a thorough vision for AI — and in some areas, has clearly pulled ahead of the United States.
Process mining, a relatively new and innovative technology, has the capability to solve challenges associated with process management and improvement.
As automation displaces a traditional accountant’s work it is important for those affected to have a positive and an optimistic attitude and consider the newly created upside potential for them to perform fulfilling work and higher cognitive tasks.
Organizations are slow at adopting progressive methods. This is true for CFOs, CPAs, and accountants. The accounting profession needs to prepare for change due to the disruptive digital technologies transformation in progress called the “digital revolution”.
Organizations are becoming more ambitious with IA investment plans, but often overlook the full costs.