Buzzwords like machine learning, problem-solving, and cognitive intelligence might help drive clicks to an article, but leaders do not care about fluff. Leaders want answers to real-life problems like, what will help me increase my bottom line? What will integrating Artificial Intelligence technology look like in the everyday routine of my employees? Will this sophisticated technology drive alignment and make things simpler, or will it make things more confusing? Here are some straightforward, real-life applications of AI that all companies can profit from.
Chatbots. Where do your employees go to get information about your company? Perhaps they go to a company intranet where resources like articles and documents are stored. Maybe they email an HR representative that can answer specific questions. Unfortunately, sometimes problems just go unsolved. Many companies are utilizing a chatbot to help employees find answers fast. Company policies, deadlines, and FAQs can be found by asking the chatbot a question. Want to find out how many sick days they get in a year, or if they’ve missed the deadline to enroll for healthcare benefits? Simply ask the chatbot and get accurate answers fast.
Analyze Surveys. Every company uses surveys to gauge employee sentiment. There are multiple-choice questions, yes/no, scales of 1-5, etc. These types of responses are easier to analyze, but not very insightful. What differentiates a score of 4 to 5 and why was it chosen? You might know how an employee is feeling but now why. This is the reason the “comments” section exists in surveys, a place where employees can explain themselves. But we run into a problem. This type of data is referred to as “unstructured data” because it’s more difficult to analyze for humans and computers alike. It would require someone reading through lines of commentary trying to organize the feelings of employees in a concise and understandable way that leadership can use. However, strides in AI and especially in NLP (natural language processing) are making this easier to comprehend. NLP applies algorithms to identify and extract the natural language rules so that the unstructured language date (e.g. a comments section in a survey) is converted into a form that computers can understand. Then computers can package it nicely for management to review.
Combining existing communication channels to understand employee sentiment. Odds are your employees are using multiple channels of communication to talk to each other; Slack, email, text message, Yammer, etc. This is where the real insights are. Although the technology to go read individual messages exists, laws and ethics do not exactly allow companies to dig that deep. However, companies may use AI to measure sentiment in a more general sense. Say you just held a sales meeting, you can presume that your sales team is discussing it on Slack. Whether they’re talking about how confused they were or how great it went, NLP can gather that information and deliver it to leadership who then take the appropriate next steps.
Recommendations and content curation. AI can combine information from all the capabilities mentioned above, to create content recommendations for those in leadership positions. Whether it be an update, newsletter, or announcement, AI can optimize them with recommendations based on employee sentiment, company policies, and more. AI can tell you that a title under 5 words gets more reads than longer ones, that including graphics increases clicks, that employees are talking about healthcare plans a lot this month, so you should mention this is your next newsletter.