In the world of AI, autonomous agents are a popular tool for improving productivity. They streamline workflows and automate tedious tasks, freeing up employees to focus on more creative or strategic work. They can also provide valuable insights and identify areas for improvement, resulting in additional cost savings and improved performance.
In one study, workers who used an AI assistant to resolve customer service calls experienced a significant uptick in productivity—with chat resolution rates per hour rising by 13.8 percent. Other studies have shown similar gains. However, these results are not without caveats. A common issue found in these studies is role flipping, in which the agent switches between user and assistant roles without contributing to either function. To minimize these issues, programs need to incorporate a system that recognizes changes in the environment and proactively acts based on these changes.
Another problem encountered by some of these studies is the lack of data on the quality of the information received from the AI. This can be mitigated by including a mechanism that alerts a human to any errors in the data and by building trust with the agent through consistent behavior. Additionally, these programs need to ensure that the agent does not have contradictory goals or objectives. This can be achieved by incorporating a goal-oriented architecture and implementing the ability to proactively take on new tasks and improve over time.
While the future of AI is certainly exciting, it’s important to keep in mind that today’s technology doesn’t quite get us there yet. While we may one day have a team of robot coworkers like Jarvis from Iron Man, or the calm-under-pressure TARS from Interstellar, or even an amoral HAL 9000 straight out of 2001: A Space Odyssey, for now, our AI tools should be thought of as “eager interns” that help us do our jobs more efficiently.
With multichannel support, a one-size-fits-all approach to boosting agent productivity won’t cut it. Achieving higher productivity requires empowering agents with the right tools to handle each channel’s unique challenges, such as seasonal spikes and frequent escalations.
One way to do this is by providing agents with the ability to quickly generate comprehensive summaries of past customer conversations. These reports allow AI Agents for Productivity to see the full context of customer needs, which can help them provide more personalized and effective support.
Another powerful tool is the ability to create and deploy automation using a simple web interface. These workflows can help agents save time by eliminating the need to perform repetitive tasks, and they can also give managers a real-time view of how much work is being completed. For many businesses, this is enough of an improvement to justify the investment in artificial intelligence.
Wednesday, August 2, 2023