AI can analyze vast datasets, make perfect sense of seemingly unrelated information, and help teams make more informed decisions.
It can help the project manager understand the best path to deliver the project efficiently and give KPI-based recommendations for complex problems.
This can help eliminate any decision-making biases.
Based on historical data, AI-assisted tools could be used while working on project proposals. It could also help advisories predict the chances of winning the bid or the percentage probabilities of winning the proposal.
Based on the outcome, they could decide whether it’s worth investing time and effort in each proposal.
By using predictive AI tools, we can also find success in accurately projecting the monthly or annual financial performance.
A project has many moving parts, so planning and resource management can become complex. While it requires the intuitive thinking of the human mind, certain routine activities can be mimicked by the power of AI.
Building Predictive Analytical Models
AI can help build predictive analytical models to provide more accurate estimates of efforts, resources needed, and budget requirements for project activities. While each project is different, the parameters that influence the progress and success of a project are somewhat similar. AI-based tools can identify these patterns to reduce the deviation in the planned and actual scheduled dates.
Determine how many tasks an individual could complete in future projects by analyzing weekly productivity data in an existing team and using historical data to estimate similar tasks. We could build tools that automatically reassign duties if we imagine the possibilities.
The better the team’s knowledge of different technologies and other system components, the quicker we can implement these improvements.
Auto-scheduling & Tracking Project Plans
Make project plans more robust by enabling auto-scheduling by programmed logic and pre-designed rules. In addition, progress and task status can be tracked automatically and alert the project manager in case of a possible deviation.
Employee Training & Management
For resource allocation, we could review the working hours and time-off schedules of all the individuals available to work on a project. By comparing the required skills and the application on the career portal, we can recommend employee training or suggest hiring new team members. This could be a considerable step in augmenting the hiring processes in organizations.
AI-based solutions can forecast and predict the possible outcomes of different situations and increase the accuracy of estimates and plans, reducing errors and improving efficiency.
AI can help automate several routines and repetitive tasks without human intervention, leaving people to focus more on innovation and value add tasks, boosting the productivity of teams.
When PMs can study the throughput from team members and reassign work based on their capabilities, they can save significant time on the project. In addition, AI can analyze the project’s data and identify workflow gaps that could diminish the project's success.
AI can help reduce risk by predicting the expected impact based on similarities from previous projects.
By analyzing past data, AI can compare it to the current projects and forewarn the manager about potential delays. AI could also detect underperforming key metrics early in the project cycle and even give expert recommendations on the actions to bring the project back on track.
With early detection of any errors or risks, AI can mitigate those issues before they threaten the project. AI could also increase the quality of the end product and minimize the deviations in cost and schedule.
A chatbot is an AI software that can simulate human conversation with a user via mobile apps, websites, messaging apps, or by telephone.
Rule-based chatbots usually follow pre-established rules to respond to user questions. For example, when the user asks a question about the weather outside, the chatbot finds information from available sources and then responds to the user.
ML-based chatbots can process a user’s question and understand its meaning. They learn from every previous conversation with users so they can handle more complex questions in the future.
In project management, chatbots can perform repetitive administrative tasks like scheduling meetings, collecting data, reporting, sending out minutes of meetings to all stakeholders, and more.
This saves the project manager significant time to focus on more critical and complex business strategies and tasks.
Using conversational AI and chatbots integrated with third-party software can also save managers time by using voice recognition software to issue unique commands.