The growth and hype around generative artificial intelligence (AI) have been remarkable in recent months. Generative AI can create content, including text, images, and videos, based on different forms of input data, such as text, images, and audio. 

One of the most popular examples of generative AI is ChatGPT, a Natural Language Processing (NLP) model that can generate human-like responses to queries which, in its latest version (GPT-4), can be in the form of images or text inputs.  

While generative AI shows great promise, it also poses several technical challenges and ethical concerns. This led to a recent petition signed by prominent tech leaders, including Steve Wozniak and Elon Musk, to halt further AI developments for at least six months. 

Potentials of Generative AI 

Project Management

Despite challenges and concerns, generative AI technologies have the potential to revolutionize many sectors and roles, including project management. Generative AI could make project managers more effective, increasing their work quality and automating tedious tasks. As a result, project managers could spend more time on the strategic part of their role, like managing stakeholders, motivating the team, and actively managing change and unexpected events. 

An example of an area where generative AI could help is project planning, project managers could input project requirements and constraints (such as available resources, dependencies, etc.), and the generative AI model can generate a range of potential project plans, each with their own advantages and disadvantages. This could help project managers to make informed decisions about which plan to pursue. 

Risk Management

Another potential application of generative AI is risk management. The AI model can generate simulations of project outcomes, which can help project managers to evaluate the potential impact of different risks and mitigations on project timelines, budgets, and outcomes. 

Project Monitoring and Communication

Generative AI can also be used in project monitoring and communication. A generative AI could generate reports and summaries of project progress and performance, which can help project managers to identify areas where the project is excelling or falling behind and streamline communication with teams and stakeholders. 

The model can also generate insights into project performance metrics, such as budget utilization and resource allocation, which can help project managers to optimize project performance and identify areas for improvement. 

In conclusion, I believe generative AI could greatly improve project management, but it has to be used, considering the potential implications and risks of using it.  

This article was contributed by our expert Marco Tosoni

Frequently Asked Questions Answered by Marco Tosoni

Q1. What potential risks are associated with generative AI and the various mitigation methods?

As in almost any AI application, there is a risk of having biased outcomes based on the data used to train the model. Identifying and correcting those cases might be difficult due to the lack of transparency in how AI arrives at its decisions. This is where the experience of the Project Manager responsible for the project can make a difference by identifying and correcting the bias. 

Q2. How can generative AI be used in project monitoring and communication? 

Imagine being able to connect a Generative AI solution to systems storing KPIs, project tasks, and communication data. You could ask the system to generate and send status updates, newsletters, and social media posts, build dashboards, and flag issues and risks in real-time. This could also enable complex data analysis, which requires expensive Business Intelligence systems today.