Looking to solve a productivity problem without adding headcount? Find an AI-powered solution! That will fix everything, right? Not so fast…
Artificial Intelligence is a term used to broadly describe the use of computational pattern recognition applied to decision-making in workplace software. Sometimes the patterns are based on simple true-false signals, while in other cases, a more complex set of rules are applied, like Natural Language Processing (NLP) where computers try to interpret text.
While smart tools have the ability to increase productivity by 40% or more, AI-powered technology cannot be blindly patched into any internal support function with the expectation that it will solve all of your workplace problems.
Sorry, it just doesn’t work that way.
There are, however, applications and scenarios where AI does dovetail nicely. Those applications are:
- Intelligent chatbots
- Request routing and triaging
- Predictive insights for optimizing operations
Let’s examine each application in more detail.
Slack is becoming the operating system of the modern workplace. On its own, the Slack platform is a powerful communication and collaboration platform. But its true superpower is in its extensibility. Enter the intelligent chatbot – a perfect application of AI for increasing productivity.
Chatbots can be injected into Slack, with little or no effort, and they are the perfect vehicle to introduce artificial intelligence into a platform built for communication and collaboration. Once sufficiently trained or integrated with internal knowledge and data, they can interact with support seekers to suggest non-human resources to aid in solving their problem. The chatbot’s application of AI can be rudimentary or complex, by applying Natural Language Processing (NLP). Consider some of these examples:
- Disco – a simple NLP bot that tracks words of praise in Slack conversations to track high performance
- Answer Bot – Zendesk’s NLP bot that suggests resources to support agents for newly opened tickets
- Obie – Intelligent NLP that provides knowledge when sensing questions in Slack conversations
AI-powered chatbots are a very low-effort way to accelerate the productivity of teams with very little investment and only minimal training. It’s important to note that these implementations of AI are less like a Siri or Alexa experience, and more akin to a virtual agent that acts as a steward for small but annoying issues in common workflows to increase overall productivity.
Routing and Triaging
A very simple but practical application of AI is in routing and triaging work that has been created by a request or support-related event. These types of “decision tree” events can be routed automatically with an AI-powered algorithm.
For example, when a support ticket is added to the queue, simple AI can be used to determine the required interventions for resolution including priority, agent assignment, or starting. More robust AI can be applied to actually automate the resolution. Consider a request containing a “password reset” request – a trained algorithm can send a reset link and instructions by email or Slack message to the requestor without having to get a human agent involved.
There is no shortage of low-value tasks that can be automated through the use of AI, especially in the various internal support functions. AI is more than capable in dealing with some of the following tasks:
- Sending email and notifications
- Updating status of tickets
- Categorizing requests
- Automatic approvals of low-risk or low-cost issues
The use of AI-powered routing and triaging can limit human involvement in issue resolution significantly. This frees up human resources from unnecessary or low-value work, and allows those agents to concentrate their productive time on higher-value outcomes.
The final application of AI is for producing forecasts and insights on existing operations to provide opportunities to optimize processes.
By collecting historical data on operational processes and passing them through an AI-powered algorithmic analysis tool, one could obtain key insights that could be used to direct valuable resources to different parts of the organization. One common scenario would be to identify knowledge gaps from frequently asked questions. Knowledge gaps cause massive loss in productivity and disrupt more than just the knowledge-seeker. Predictive insights can identify these types of gaps so that they can be prevented in the future.
Smart solutions can increase productivity
Artificial intelligence does increase productivity when used in the appropriate context. Smart tools can accelerate individual and team work by being inserted into scenarios that occur in high volume and have predictable resolution practices. Where these tools commonly fail to meet expectation is most likely in scenarios where the volume of occurrences is relatively low (this is of course a subjective interpretation) and the required intervention is highly variable or has quirks and eccentricities.
By consulting experts in AI, you can understand if your problem is one that is commonly solvable by a smart-tech solution.