Artificial Intelligence (AI) and Machine Learning (ML) are popular topics for just about any business function, in any industry. And that is not surprising as both methodologies promise to help us work smarter, faster, and with better insights and information. Let’s first align on the definition of these terms:
Artificial Intelligence (AI) is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
Machine Learning (ML) is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to “learn” with data, without being explicitly programmed.
ML therefore supports and empowers AI – further developing its intelligence beyond its original programming. However, since ML is considered a subset of AI, we will focus on AI. AI is widely applied in many industries. (After all, if you’ve ever interacted with a chatbot, you have experienced using AI.)
With unemployment at all time lows and many industries struggling to operate with severe labor shortages, making the most of the human capital we have is paramount in many businesses. AI can be applied to the human resources function to increase the speed and usefulness of available data and to increase productivity among HR managers, as well as to increase overall employee productivity as well. In fact, Accenture, in its Reworking the Revolution research, found that 20% of individuals will have AI as a co-worker by 2022.
Improving the Employee Experience
Marriott International, Inc. has an industry-leading app that allows guests to check-in and request special services without calling the hotel. Marriott took that same technology and created an employee app to emulate the customer experience. Employees interact with an AI-empowered chatbot to get information about the company, their benefits, and to answer other frequently asked questions. At Marriott, they understand the link between customer experience and employee experience. Says David Rodriguez, Marriott’s Executive Vice President and Global Chief Human Resources Officer: “At Marriott, we have created not only new HR roles but an entirely new department … charged with re-imagining our employee experiences to emulate and support our best customer experiences. In fact, Marriott’s new Chief Customer Experience Officer was Marriott’s Chief Talent Officer and worked in HR for 15 years before moving into Customer Experience.”
Getting Better Feedback
Many companies run an annual Employee Engagement survey to get feedback from employees. Unfortunately, a year is a long time and often the time between identifying a problem and solving it is too long for employee patience. While pulse surveys help with the time lag, AI goes even further. There are now employee feedback apps that allow, in essence, continual surveying. Think of them as digital and cloud-based suggestions boxes for the new generation of employees. These apps have AI-based analytics that comb through open-ends and comments to find phrases that indicate larger trends. By linking those comments to other quantitative metrics, managers can learn what employees like and don’t like. This allows leadership to proactively address emerging issues in order to enhance positive employee experience.
Facilitating and Improving Hiring Decisions
In many cases, the employee experience starts with applying for and being considered for employment. AI can be utilized there as well. Especially in large, multi-brand, or global companies, getting information about which job best fits a candidate is challenging. Marriott further leveraged its experience in developing its customer and employee apps to a chatbot on Facebook Messenger. Candidates can interact with the chatbot, which guides them to apply for openings based on their skills and experiences as well as their location. The chatbot also might guide them in learning experiences about Marriott’s brands, to further help them find openings that fit. As reported in Forbes, this app has been very successful: “As an indication of how engaging the job seekers find MC, 64% return later to initiate new conversations. Research reveals that 50% of job seekers do not hear back after submitting their resumes through traditional corporate channels, so one can see why MC has such a high return rate. Hilton has a similar employment app that they find speeds the hiring process significantly – while freeing up human recruiters for higher-value projects.
When, Not If
As with most new technologies, the proliferation of AI into all areas of business is not a question of “if” but rather “when.” To get started with effective AI implementation, start with a key business challenge – and rethink how it could work with AI. Especially with younger generations entering the workforce, acceptance of this technology as it integrates with human processes will be welcome.