Every day, there is a batch of AI announcements that are sent out—and many of them are mostly fluff. It’s kind of comical.
But of course, some are worth paying attention to. For example, consider one from IBM and ServiceNow, which have announced an expansion of a strategic relationship. For the most part, it is focused on what matters—that is, driving measurable results that scale across organizations.
To this end, IBM plans to leverage its AI-powered hybrid cloud infrastructure with ServiceNow’s intelligent workflow systems. By doing this, companies will be able to automate the prevention and correction of IT issues, which is certainly no easy feat. This will not only mean more time for service representatives to devote to value-add items but the AI will provide valuable recommendations. These will also get better over time.
Note that there is evidence that Watson AIOps has been able to reduce resolution times by 65%. And something else: According to Aberdeen, unforeseen IT incidents and outages can cost a company $260,000 per hour.
“The digital demands of today’s business environment are unprecedented,” said David Parsons, who is the Senior Vice President of Global Alliances and Partner Ecosystem at ServiceNow. “As a result, organizations that struggle to deliver cross-functional workflows that create great experiences for customers, employees, and partners will be left behind. Digital transformation is no longer optional for anyone, and AI and digital workflows are the way forward.”
This is definitely spot-on. And IBM and ServiceNow are showing that AI can be more than about small projects that do not move the needle in a significant way.
“The four keys to success with AI are the ability 1) to automate IT, 2) gain deeper insights, 3) reduce risks, and 4) lower costs across your business,” said said Parsons. “Together with IBM we are equipping companies with all of the tools they need to achieve each of these factors. The first phase of this extension to our strategic partnership brings together IBM’s AIOps software and professional services with ServiceNow’s intelligent workflow capabilities to help companies meet the digital demands of this moment.”
When it comes to AI, things can quickly get confusing. The category is wide-ranging and moving fast. There are also a myriad of subcategories like machine learning, deep learning, NLP (Natural Language Processing), computer vision and so on. Having a good understanding of all this is crucial for success.
“When we talk about AI, we mean AI for business, which is much different than consumer AI,” said Michael Gilfix, who is the Vice President of Cloud Integration and Chief Product Officer of Cloud Paks at IBM. “AI for business is all about enabling organizations to predict outcomes, optimize resources and automate processes so humans can focus their time on things that really matter.”
Note that IBM Watson has handled more than 30,000 client engagements since inception in 2011. In other words, there are some key learnings. According to Gilfix, they include: NLP is at the heart of AI for business, as this technology can parse and understand huge amounts of unstructured data; there needs to be trust and explainability with the models so as to get adoption; and then there should be true automation of IT and business processes.
“We believe that every company is going to become an AI company and AI adoption is accelerating,” said Gilfix. “The global pandemic has made it abundantly clear that AI can help with vast issues facing businesses today—from driving digital transformation to keeping customers and employees informed and engaged.”
Tom (@ttaulli) is an advisor/board member to startups and the author of Artificial Intelligence Basics: A Non-Technical Introduction and The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems. He also has developed various online courses, such as for the COBOL and Python programming languages.