If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The expanding universe of artificial intelligence includes many terms and technologies. That naturally leads to overlap and confusion. AI and machine learning are mentioned together so often that some people – non-technical folks especially – might think they're one and the same. They're related but not actually interchangeable terms: Machine learning is a subset, or a specific discipline, of AI. Start adding other terms and technologies into the mix – deep learning is yet another subset of machine learning, for instance – and the opportunities abound for further misconceptions.
The technology we use at home is slowly converging with the enterprise environment. The innovation taking place within the virtual assistant (VA) market -- and its potential to create an entirely new workplace reality -- is particularly exciting to see. Artificial intelligence-powered, voice-controlled assistants like Alexa, Google Assistant, Siri, and Cortana are already commonplace in many homes. This popularity is building pressure to integrate VA functionality into enterprise technology, as well, which could significantly reconfigure and enhance the employee experience. By 2021, Gartner, Inc. predicts that "25 percent of digital workers will use a virtual employee assistant (VEA) on a daily basis. This will be up from less than 2 percent in 2019."*
The use of virtual assistants (VAs) in the workplace is growing. By 2021, Gartner, Inc. predicts that 25 percent of digital workers will use a virtual employee assistant (VEA) on a daily basis. This will be up from less than 2 percent in 2019. The contact center was the pilot and testing ground for many adopters of VAs, but with the democratization of artificial intelligence (AI) and the development of accurate and clever conversational UIs, different types of VA have arisen: virtual personal assistants (VPAs), virtual customer assistants (VCAs) and VEAs. "We expect VEAs to be used by an increasing number of organizations over the next three years," said Annette Jump, senior director at Gartner.
It's one thing to bring conversational bots and robotic process automation (RPA) into business applications. But the strongest opportunity for innovative companies is in combining these capabilities. I discovered how some market leaders have already found this exponential power during one session at the recent SAPPHIRE NOW and ASUG Annual Conference. "It's the convergence of these technologies that provide the opportunity for a better experience, as well as the ability to apply machine learning technologies to create an ever-learning enterprise, applying knowledge and skills acquired from that machine learning technology to create the Intelligent Enterprise," said Shawn Brodersen, global vice president and SAP CTO at HCL Technologies Ltd. One pharmaceutical company improved workforce engagement with intelligent RPA and conversational artificial intelligence (AI).
Sifting through this year's chat bot and AI predictions, it's clear that conversations have finally shifted from human versus computer, (so last century), to the exponential value of people plus machines. If researchers can be believed, a new breed of chat bots has emerged, smarter than ever, with stronger benefits for companies and their customers. Most noticeable was the cascading impact of AI. We can expect a bit of upheaval market-wide and across workforce practices, all the way down to some groundbreaking opportunities for software developers. Starting at the topmost view, IDC predicted the market for automated customer service agents will total $2.2 billion by next year.
As the curtain rise for 2019, do expect to see major changes in how organizations use Artificial Intelligence (AI) in the new year. AI has shown immense potential to make our lives much easier, a fact which does not stop in our homes, as businesses constantly come up with new ways to use AI to engage with customers, make processes easier and pull revenues to new highs. The effectiveness and popularity of AI-powered chatbots in recent years has catapulted an increased interest in how artificial intelligence is deployed to improve the results of ad campaigns. Forrester Research says that 2019 will see the rise of new digital workers with an increased competition for data professionals with AI skills. What is next in business for AI and how can it further boost the success of businesses in the new year, here is what to expect from Artificial Intelligence in 2019.
In fact, it's almost here as businesses enter either the implementation stage or begin seriously investigating it. The reason for all of this interest is twofold. Firstly, digital workforces have the ability to enable business operations teams to enhance, accelerate and customize key processes that deliver clear customer satisfaction and operational improvements. Secondly, global enterprises now have the chance to operate as smaller, faster and more agile companies while still maintaining their own advantages of scale and size. It is clear then that for business operations teams, this is great news as it allows them to focus on improving customer satisfaction and driving revenue.
"The robotic process automation (RPA) momentum started way before AI piqued the interest of enterprises," The Forrester analysts explain. "Until now, firms have been treating these set of technologies distinctly; i.e., RPA for automation, AI for intelligence. But to create breakthrough opportunities, we believe that an RPAplus-AI technology innovation chain will turbocharge your innovation efforts. Firms are already combining AI building block technologies such as ML and text analytics with RPA features to drive greater value for digital workers in four use cases: analytics that solves nagging platform issues; chatbots that boss around RPA bots; internet-of-things (IoT) events that trigger digital workers; and text analytics that lifts RPA's value."
It's difficult to make predictions, especially about the future, but we can be certain that "AI Washing" will continue to rise and flourish in 2019. That's what market research firm Forrester calls the hype and hooplah around Artificial Intelligence (AI), the latest set of technologies that is promising to "change the world." In its 2019 predictions, Forrester tries to temper the "irrational exuberance for AI adoption" with a dose of reality, looking forward by observing how companies automate their work today while experimenting with adding intelligence--artificial and human--to analyzing data and making decisions. Here's my summary of two Forrester reports published today, "Predictions 2019: Artificial Intelligence" and "Predictions 2019: Automation." It's the data, stupid: Most companies will find out that to realize their expectations from AI--exaggerated or not--they must invest in creating "an AI-worthy data environment."
There is a growing body of evidence to suggest that digital workplaces are not as "digital" as they might think or that organizations are introducing digital transformation strategies slower than was thought. Recent research from Gartner, for example, shows that many workers believe that the organizations where they work are not keeping up with their digital needs and are out of touch. It also showed that less than 50 percent of workers -- both IT and non-IT workers believe that CIOs know what technology workers want and need. It also showed that there was some difference between the level of awareness of technology problems between Europe and the U.S. Further research from Blue Bell, Pa.-based information management specialist Unisys showed that more than half (51 percent) of digital workers at "technology laggard" organizations expressed frustration with their employer, as compared to only six percent of workers at "technology leader" organizations. The Unisys survey is particularly telling in that it surveyed 12,000 workers in April 2018 across 12 countries to gauge the attitudes of today's digital workers on how the technology used in the workplace impacts their day-to-day lives.