Managing Employee Expectations After AI Deployments

3 minute read

Your employees might think that AI will do all their work for them. They’re wrong. AI and human labor will need to work in concert to keep your business running smoothly. Read this article to find out more.

If your company has adequately prepared its staff for an AI system implementation, your workers should be excited about what’s to come. You’ve likely debunked the myth that the AI system will steal their jobs, and you’ve gotten them to understand that the new platform is geared toward making their work lives easier.

Now that your staffers are optimistic about the potential for AI in the workplace, it’s time for you to perform a bit of expectations management. With many incorrectly touting AI’s sole purpose as replacing all human workers in every role, your employees are likely envisioning easy days with little actual work. They’re probably assuming AI will take over their more mundane, repetitive tasks, leaving them plenty of time to gab by the watercooler or on their phones. These are the kinds of myths that will need to be debunked as you move ahead with your AI implementation.

AI Won’t Solve All of Your Problems

No matter how powerful your AI system, there will still be unique and challenging issues that human labor will need to resolve. This is especially true during the first few months of your AI system deployment. Here’s why: AI systems are trained to accomplish specific tasks, and not to deviate too far from a company’s standard business processes. When a customer service issue is presented to an AI system, the system will determine if it can solve the problem or if it needs to be escalated to a human colleague.

No matter how powerful your AI system, there will still be unique and challenging issues that human labor will need to resolve.

At this point, your workers will need to retreat from the watercooler and head back to their desks to handle this escalated issue. Here’s the good news: Some AI systems, such as IPsoft’s Amelia, monitor these human-to-human interactions to learn how to resolve similar issues in the future without tapping into human talent. If the AI system monitors the interaction and realizes there was a pathway to a resolution within the confines of its purview, it will resolve the issue itself.

AI Deployment is a Step-by-Step Process

Your employees might think you’ve deployed a robot to field all calls, emails, and chat messages. While this may someday be possible, standard AI system deployments happen use case by use case, often directed toward solving specific business challenges or achieving strategic corporate goals. Typically, a company would start with a use case that’s repetitive and standardized, such as password resets, or account verification. While AI is learning and perfecting its ability to handle those initial use cases, employees will not have time for watercooler chit-chat, as the remaining use cases and service processes will remain firmly in human hands. In the initial deployment stages, human workers will still need to answer phones and chat messages from customers.

After succeeding with initial use cases, additional ones can be delegated to AI, and human workers can be assigned to more unique and complex tasks.

AI Systems Will Make Work Easier

Even if AI systems need humans’ time and effort to be effective, AI systems will still dramatically improve the lives of your workers. With AI fielding basic, repetitive calls, your workers will have less volume to manage. Thanks to AI’s ability to absorb and store massive amounts of data, your workers can use AI to find answers to questions for which they may not have immediate answers. AI can scale with spikes in call volumes, acting as a first line of customer support so human employees are not overwhelmed. In the end, AI will ultimately make human employees better at their jobs.

Deploying an AI system can bring fantastic benefits to any company, but it can’t get the job done on its own. It’s an important point for businesses to communicate to their employees so that expectations are line with whatever outcomes are achieved.


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