Applying Artificial Intelligence in Project Management by Paul Boudreau

Author:Paul Boudreau
Language: eng
Format: epub
Publisher: Mercury Learning and Information

VIRTUAL ASSISTANTS

Voice-enabled solutions such as Alexa, Siri, or Google Assistant are helpful for finding information or creating a list of personal tasks. Chatbots (or virtual personal assistants) are frequently found in a messaging format on Web sites to interact with customers searching for information. The AI-based software can recognize and interpret sequences of words and analyze them so a response can be created. The request does not have to be exact because the AI software can classify different expressions with the same intent.

Voice recognition systems that can play music on command are being used with greater frequency in the business world. This is equivalent to being hands-free on a smartphone while talking to a database. AI software can be “fed” all the organization’s documents and then allow them to be queried by a voice-enabled chatbot. This is an excellent opportunity for project managers to load a scope document and allow team members the option of making verbal queries to instantly obtain data. The next step is to find a way to properly reflect the current project status, which requires defining an update strategy, typically as a batch-style update on a predetermined schedule or a streaming update in real time. Following this, a source that can apply project management logic to the data must be found.

The process of communicating with a virtual assistant starts with an utterance. An example of such an utterance might be “Is there training in the scope document?” The software accepts this input and determines the intent; it then searches for a relationship in the content. For this utterance, the algorithm needs to find training information. “Training” in this utterance is a noun. The AI searches the project document repository for the scope document, and within the scope document, it searches for the training section. Once the training section is found, it reads the words and replies by converting the text to a verbal response.

A company may be able to “feed” all of the project management plan documents containing project management logical connections and interpretation to a voice-enabled agent. The project manager can ask if a specific task due this week can be moved to the following week. The agent replies that this is possible because the task is not on the critical path but adds that a risk is attached to the task and will increase the risk probability from 20 to 30 percent. In this example, the agent identified that the task was not on the critical path and then identified that it was linked to a risk in the risk register. Finally, it gave the project manager an update on the risk changes. The project manager can investigate further or decide whether to move the task to the following week. This is a straightforward example of what is possible. It also illustrates the concept of ubiquitous project management. Ubiquitous in this context means a project manager can manage a project from anywhere at any time as long as there is access to the AI agent, usually by using a smartphone app.

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