Updated: Jun 27, 2019
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.
Digital Workers Are Frustrated
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. This level of frustration directly correlates with the threat of attrition. Workers at technology laggards (11 percent) were 450 percent more likely to want to leave to go work elsewhere, as compared to their counterparts at technology leaders (two percent).
While the research looked at attitudes to device use as well as ‘Bring Your Ow Device’ (BYOD) strategies, it showed that 65 percent of workers were downloading apps and accessing websites not supported by their organization, it also had some interesting findings about the use of artificial intelligence in the digital workplace.
According to the survey, 31 percent of respondents viewed Internet of Things (IoT) technology as the emerging technology with the most potential to transform their workplace environment in the next five years, with 27 percent citing artificial intelligence (AI) as a close second. However, while most respondents cited familiarity with these terms, only 24 percent and 20 percent, respectively, said they understood IoT and AI well.
Related Article: 7 Ways Artificial Intelligence is Reinventing Human Resources
AI in Digital Workplaces Now
Walter Van Uyten, CEO of Belgium-based Awingu points out that while AI may be key to building a digital workplace, it is only an enabler and needs to be incorporated into a wider view more holistic view of the digital workplace. A fully digital workspace should first and foremost enable mobile working from any device, anywhere. “Any digital workplace should stimulate productive working and collaboration with easy sharing, conferencing, chat functions and other digital tools. The solution should secure and facilitate compliance with centralized data and application access, rather than running and storing applications and files locally, and be platform agnostic while avoiding vendor lock-ins,” he said.
The problem, according to Katrin Ribant, chief solutions officer and co-founder of New York City-based marketing intelligence company Datorama, is that AI is still in its nascent stages of development. While there’s plenty of AI being used today in very specific areas of focus (e.g., fraud detection, billing systems, data integration, etc.), this will grow and spread. It’s just a matter of adoption and how long it will take for that to happen. “From the present day to the next three years, I foresee a lot of educating to aid the understanding of what AI really is capable of and how it can serve as a complement to business professionals,” she said.
She added that over the past few years there has been considerable pushback from people who have been sold on the narrative of man versus machine rather than man plus machine. “In the near term I see this thinking fizzling out as businesses begin to leverage AI to take care of the “heavy lifting” involved with number crunching and data wrangling."
Related Article: 6 Ways Artificial Intelligence Will Impact the Future Workplace
Organizations are Not Ready for AI
Although it is difficult to foresee what level people will be using AI to assist in their respective business challenges, it’s safe to say that AI will move from being something that’s considered advanced — today — to something that’s considered the norm five years down the road. Rather than just being tasked with doing the hardcore number crunching, AI will start to appear in other areas where it can assist professionals on the job. That may involve software acting within a certain set of parameters on behalf of a person so that the professional can spend more time allocating their daily routine to strategy over, say, doing manual data extraction.
The current state of play, though, is that most organizations are not ready for any generalized use of cognitive computing, according to Ajay Khanna, VP of marketing at Redwood City, Calif.-based Reltio, which has developed a self-learning data platform. There is quite a bit excitement about the prospects of AI and machine learning (ML), but most companies are still not ready for any serious level of cognitive computing. The key challenge is the quality of the data to attempt such an endeavor,” he said.
Machine learning requires a reliable data foundation to ensure that algorithms are acting on the right information. One challenge, not just for machine learning but for advanced analytics in general, has been the tediousness of synchronizing data models between operational applications and data sources, and downstream data warehouses and lakes that are being used as the data catalog for ML. Ensuring reliable data requires blending and correlating profile attributes across disparate siloed sources, applications, and formats. An immediate use case for ML is to help improve the data consistency, accuracy, and manageability for better data quality. ML helps with uncovering patterns and anomaly detection in data to make data stewards' jobs easy and effective. “In addition, there's still distrust in machine learning as black box magic. The initial phase of AI and machine learning must provide transparency about the rules that drive any decision, offer potential choices to the user and leave it up to users to evaluate,” he added.
AI to Help Customer, Employee Experiences
Luc Burgelman, CEO and co-founder of Belgium-based NGDATA points out that for the moment, most of the AI used in the organization is AI-based virtual assistants and chatbots, especially those in customer-facing industries, as examples of AI used to engage with and support customers. He believes that this is a trend that will continue. “We’ll see these companies add even more AI that results in more interactive experiences. Customers will have voice control over the chatbot, which will act as a client advisor via the computer, taking on the role of a real, human person,” he said.
However, he added that the most important part of creating AI-based technology like virtual assistants is having the data drive actions and decisions. This means considering all data — including real-time and behavioral data and learning from all channels to create connected experiences. Leveraging AI to continuously learn from this omnichannel data and empower customer interactions through the understanding of all this detail will be critical for companies moving forward.
At an organizational level, Boston-based LogMeIn’s Ryan Lester, director of customer engagement technologies says AI is playing a crucial part in shaping the way the digital workplace is organized. We are seeing AI show up in two very specific ways. In customer experience, AI is helping customer service teams create a high-quality customer experience. As AI continues to mature, it has the capability to connect with customers in a more human, personal and contextual way. It is constantly learning and is smart enough to know when it’s not smart enough and can seamlessly bring a human in to help.
AI-powered technologies like chatbots are helping customer service agents by removing low-value repeatable tasks from their day jobs, allowing them to focus on more meaningful and creative work. They also work on the backend prompting agents with recommendations that can help provide a more personalized customer experience.
The second area of course is employee experience. They are seeing AI show up in the digital workplace, as in employee experience where AI is helping internal departments like IT and HR onboard employees and answer frequently asked questions. With so much of the focus being on customer experience, the employee experience can easily get forgotten. AI is helping companies re-imagine how to deliver an awesome experience for their employees and improve the productivity of the modern workforce and those who support them.
That being said, adding AI to the digital workplace should not be about swapping humans for bots, but rather about creating a balance between the efficiency of a bot with the emotional intelligence of a human connection.
Jimmy Carroll, partner and director at Chicago-based TetraVX added that many companies are already using AI to improve functioning across their entire enterprise. In the unified communications sector, AI is changing the way companies structure their workflows, decision-making processes, and strategy planning. When coupled with analytics, AI programming helps leaders make better employee, customer, and production decisions based on both existing circumstances and AI-predicted future events.