Office worker requesting time off via AI assistant
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If the use of artificial intelligence in building top customer experiences has been well documented, its use in developing top employee experiences has, to a large extent, been overlooked. However, with the leadership in many organization beginning to realize that better employee experiences result in better customer engagement with the organization, they are now starting to look at their employee experiences and how to improve it.

One of the lines of reasoning at the moment is that if AI can improve customer experiences, and customer experience and employee experiences are closely linked, why not use AI to improve employee experiences as well. It’s an argument that has not been missed by the likes of LinkedIn.

Recently, the San Francisco based LinkedIn announced the creation of the LinkedIn AI Academy. The goal of the Academy is to equip employees across the company — in areas like engineering, product management — with the knowledge they need to deliver AI experiences to its members. In a blog post that accompanied the announcement by Craig Martell, head of science and engineering, LinkedIn outlined its vision for AI in employee experience:

“From features like People You May Know to the recommendations for LinkedIn Learning courses, AI helps deliver value to our members across their entire career journey by personalizing their experience... As we constantly look to improve LinkedIn, we’re finding more and more ways in which AI can bring additional value to our members and customers,” he wrote, drawing a clear line between employee experience and customer experience. 

Martell noted, that while use of AI in both these cases has increased recently, expertise in AI has not grown to keep up with the demand. “Today, top universities can’t produce graduates with the requisite AI skills quickly enough. Companies around the world compete fiercely for these individuals, without whom they can’t hope to remain competitive; LinkedIn is no exception,” he added. 

In fact so important to LinkedIn is this initiative that he said attendance at the AI Academy will become part of the employee onboarding process in the future.

Related Article: 7 Ways Artificial Intelligence is Reinventing Human Resources

Workers Don’t Fear AI

Despite fears about the impact AI will have on the workplace, research from The Workforce Institute at Lowell, Mass.-based Kronos Inc. shows that many employees see significant opportunity for AI to build a more engagement and empowering workplace experience. In fact, of the 3000 employees across eight countries that were surveyed for the report that was published in February 2018, nearly two thirds said that their biggest concern was not AI itself but the lack of transparency from their employers about its deployment and use.

The Engaging Opportunity: Working Smarter with AI survey conducted with Coleman Parkes Research explored how employees — both hourly and salaried from a variety of industries in Australia, Canada, France, Germany, Mexico, New Zealand, the United Kingdom, and the U.S. — believe emerging technologies should be used to improve the future. It showed that employees from all eight nations would welcome AI if it simplified or automated time-consuming internal processes (64 percent), helped better balance their workload (64 percent), increased fairness in subjective decisions (62 percent), or ensured managers made better choices affecting individual employees (57 percent).

However, 6I percent say they’d feel more comfortable if their employer was more transparent about what the future may hold in terms of working with AI and potentially being “replaced by technology” while 58 percent of organizations have yet to discuss this potential impact of AI on their workforce with employees.

“There’s a common perception out there that employees are scared by AI because they believe they will be automated out of a job. However, the research points out that only 35 percent of financial services employees are concerned about losing their job if AI is introduced in their organization,” Chad Davis, senior industry marketing manager at Kronos said.  Many see AI, however, as a way of all augmenting human interactions and workforce management for the better. Chad points to three particular areas where AI can help.

Smarter Staffing

AI helps ensure more accurate forecasts, which helps branch managers make sure they have enough employees working to meet demand for staffing. It also takes things a step further and matches employees’ level of experience and area of expertise with the specific customer needs. On the back end, branch managers can use the appointment data to match the customer’s needs with the most-qualified available employees based on their skills and experience to optimize service and sales.

Related Article: 8 Examples of Artificial Intelligence (AI) in the Workplace

Proactive Compliance

When it comes to managing labor compliance, the stakes just keep getting higher. The Department of Wage and Labor Division recovered more than $1.2 billion in back wages in the last five years alone. Proactive compliance solutions leverage AI and machine learning to continually project up-to-the-minute timekeeping data into the future, identifying and alerting managers to potential compliance risks hours or even days before an issue surfaces.

Personal Digital Consultants

These intelligent “advisors” use AI and machine learning to automate time-consuming daily decisions, freeing managers to spend more time on strategic initiatives. Personal digital consultants apply AI to analyze all applicable variables and rapidly make an informed recommendation to accept or reject the time off request. With intelligent decision support at their fingertips, managers can speed through administrative tasks and turn their focus to driving sales and service.

Smart Timesheets

Kari Foster is director of marketing at Journyx. She says research that they have done has uncovered all kinds of possible uses for AI, but one of the big one is timesheet management. Employees hate filling out timesheets, because it takes too much time. She believes that timesheet applications are in a unique position to not only change employees' view of tracking time, but reshape the way they work across teams, applications, and projects.

A smart timesheet, she said, is one that works on a foundation of AI and/or machine learning to automatically fill out the timesheet, using data from other software applications used during the course of the work day.  “Smart timesheets built using AI can most certainly affect employee experiences by making an oft-maligned task into something faster, easier, and more accurate,” she said.

Deep Content Search

Finland-based Valamis (formerly Arcusys) is the developer of a learning experience platform. The company recently developed a chabot powered by IBM Watson to supplement the platform. For Katy Roby, marketing manager for North America for Valamis, chatbots can answer questions and find materials quickly and without bothering other employees. “My experience as an employee using AI has been an improvement in my  productivity overall; I am way quicker at acquiring the knowledge I need, right when I need it and I don't have to bother or wait on a co-worker,” Roby said.

Selecting Leaders

Artificial intelligence has the opportunity to diversify boards and remove the bias of executives choosing who they know. The Risk Institute at the Ohio State University has done extensive research on using machine learning to hire and select board directors. Researchers studied over 41,000 newly appointed board directors chosen between 2000 and 2014 and found:

  1. By providing a prediction of performance, a machine-learning algorithm could expand the set of potential directors by identifying qualified individuals who may have been overlooked.
  2. Using machine learning to select board members could alleviate concerns that chosen directors do not always serve shareholders’ interests. The research also suggests that the suboptimal director choices are more likely to be male, have previously held more directorships, have fewer qualifications and larger networks. Machine learning holds promise for understanding the process by which existing governance structures are chosen, and has potential to help real world firms improve their governance.

Enriching Meetings

AI has the ability to shift meetings from an information exchange to a rich information source that can be used to better manage activity both for the employee and across the enterprise, according to Dave Damer, CEO and founder of Testfire Labs in Edmonton, Alberta. He said that Natural Language Processing (NLP) and Machine Learning (ML) are going to take us from recording meeting minutes to an enriched data set that hold the promise of making meetings more effective — delivering insights, and driving behavioral changes in the workplace.

“AI-based meeting assistants — such as Testfire’s Hendrix.ai and Voicera’s Eva — are already providing services to transcribe, summarize, and capture key data items such as action items from meeting conversations,” he said.

Sentiment And Emotion Analysis

In addition to converting what we say into notes, AI-based meeting systems promise universal language translation, identification of speakers, and emotional analysis. Natural Language Classification systems, for example, can not only detect sentiment and tone, but also can categorize emotions and intents and deliver insight on the moods and feelings of the speaker.

Problem Solving

Mavenli.com and the Mavenli application uses AI to intelligently match employees with questions and problems to those who are best placed to solve them. Sacha Nitsetska founder and CEO pointed out that they are using AI with strong NLP capabilities to help a major law firm enable their employees to quickly and efficiently find solutions to problems by connecting employees with a specific question — to the people who have done similar deals in the past without having to ask around or dig through piles of documentation.