AI is an unstoppable force.
As noted by Martech Today, AI is already "here and now," and three-quarters of companies that are using AI see improved revenue. The technology continues to make significant advances in both predictive capability and intelligent decision making — organizations are excited about the prospect of merging AI with existing people and processes to boost overall business outcomes.
What AI enthusiasts don’t want to talk about?
The immovable objective to its unstoppable force: employee experience.
Building Business Outcomes
Better employee experience creates better business outcomes. Research firm Gartner predicts that 30% of firms will adopt end-user experience monitoring solutions by 2020 as the link between staff satisfied with technology and overall productivity is more accurately described.
Why does employee experience matter so much?
Because end-users drive business success. Salespeople on the front lines, marketers creating new campaigns and C-suite members creating strategic objectives — while IT enables and empowers their jobs, their ability to leverage human innovation and ingenuity is what separates cutting-edge companies from also-ran competitors.
The emerging challenge for employee experience?
Navigating the world of digital dependence. From network applications to big data, mobile devices to cloud computing, IT services are now interconnected to such a degree that isolated failure can precipitate a chain reaction.
The result? Business slowdowns, customer frustration, employee dissatisfaction and ultimately revenue shrinkage.
Automating Experience Improvements
AI offers a promising way to tackle these end-user challenges.
According to Gartner, while the technology currently sits at the peak of inflated expectations and shows signs of slipping into the trough of disillusionment, there’s little doubt that it will be broadly adopted and refined on the plateau of productivity. Already, companies are leveraging AI to create intelligent chatbots designed to dramatically decrease sales cycle duration.
Given the broad-spectrum applications of AI and its ability to churn through historical data and deliver accurate predictions, it makes sense to set this tech loose on the end-user experience, particularly when it comes to reducing repair times.
Consider: For a company with 10,000 employees, application errors and performance issues result in 22 minutes per employee of lost time every day. AI tools can help diagnose and remedy many of these issues by looking at current and historical data of all user/app interactions and then suggesting appropriate remedies.
The next step for artificial intelligence?
Automation predictive experience outcomes. Instead of simply tackling break-fix issues, leveraging new capabilities to find better ways staff can accomplish common tasks, effectively moving beyond "good enough" solutions to deliver "ideal" outcomes.
Creating Context
So far, it sounds like AI offers the ideal remedy to employee experience issues.
Turns out, however, that despite the speed of AI development and adoption, just the tip of end-user experience objectives is visible above the waters of digital transformation and big data.
What’s the disconnect?
First, automation is actually more labor- and cost-intensive than many companies realize, leading to a situation where end-user gains may not match predictions. What really makes this an immovable object for AI’s unstoppable force is the need to "humanize IT" to add the subjective nature of human experience to the traditionally dry and practical expression of employees and technology.
Consider that tech failures have different impacts depending on human context. If file sharing fails during a customer negotiation, tensions run higher than if it is during a routine weekly call with other staff members.
The inability to print annual reports for a board meeting five minutes away is different than dealing with the problem of stuck printers for a flight boarding pass you don’t need for two days.
Right now, AI is prepared to deal with machines and humans that act like machines — entirely predictable and without emotion, but given the sheer number of contextual adaptations and revisions that human beings experience day-to-day that have nothing to do with technology directly but impact our perception of that technology — which in turn impacts performance — AI’s utility shifts from absolute to adequate.
The bottom line? AI is coming, but right now it’s not prepared to meet employee experience head-on. Ongoing development — with a focus on the subjective interpretation of IT events — should help this unstoppable force find a way to coexist with end-users’ immovable objective.
