The AI-Powered Project Manager
Artificial Intelligence is programmed to follow rule-based workflows, improving project planning and helping PMs with real-time data. Learn more.
**The AI-Powered Project Manager**
<big>by GlobalLogic Marketing
</big>
Artificial intelligence (AI) has made waves across organizations and industries for quite some time.
Since its first adaptation in 1956, it brought a seismic shift in the digital space in every industry, from finance to commerce and IT.
Thanks to its unique capabilities, AI has become a game changer in project management.
There are numerous use cases for conventional AI, including more intelligent products and services which make processes more human-like and intelligent.
It can also automate repetitive tasks, predict future scenarios, use learning methods to find data patterns for intelligent recognition, and processes large volumes of data faster.
It will continue to fundamentally transform the very doctrines of traditional project management in the coming years.
People already use AI for administrative tasks like maintaining registers, logs, and automated meeting preparation. It can also help with booking rooms, emailing invites, drafting agendas, and keeping meetings for meetings.
AI-powered project management will eventually evolve to handle much more complicated tasks, especially large-scale and complex programs.
In this paper, you’ll learn about various use cases for project management teams and AI-assisted tool capabilities for creating knowledge domains.
**AI Use Cases in Project Management **
Business Insights and Decision Making
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.
Planning & Resource Allocation
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.
Scheduling Tasks
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.
Improving Productivity and Efficiency
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.
Risk Management
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.
AI Chatbots
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.
**Common AI Challenges in PM**
Often, teams enter limited data into their PM tools and may label their tasks and activities inconsistently. As a result, AI models may need help interpreting this disorganized data.
In this case, there would be a lot of missing or unstructured data entered into tools, making it unsuitable for AI integration. It would take too long to build the proper data infrastructure and prepare the data rather than create a machine learning model to run the data.
In addition, large data sets are needed for training any machine learning models.
The outcome of an AI-based system is only as good as the data provided.
So, to achieve success, we would need diverse data sets, or the results will be highly skewed. The datasets used in the ML models must be continuously updated with the latest data.
In addition, we need access to quality, unique datasets from past projects or metrics from previous programs for a successful model.
Since there’s demand and competition for influential AI experts, getting the right talent to build and work on AI-assisted models could be a concern.
**What the Future Holds**
Research from Gartner revealed that 80% of today’s project management tasks will be replaced by AI as early as 2030.
Technological innovations are advancing more and more every decade, and the PM functions will undergo a sea of changes in the coming years.
Issues that were once complicated and unimaginable are now easily automated.
However, other technological areas have become increasingly complex. In the coming years, we’ll be presented with intriguing discoveries and brand-new challenges to overcome.
So, will AI-powered technology replace project managers?
Luckily, no. While excellent at mundane, data-driven tasks, AI is flawed regarding creativity, social skills, and natural perceptiveness.
AI won’t be coming for project managers’ jobs anytime soon. It will be a while before technology evolves to the extent where that could be a possibility.
According to a recent study by KPMG, 46% of project managers believe that people management is the most critical factor in delivering a successful project.
In addition, 28% thought technology was vital, while 26% of project managers felt that either processes or governance were critical for success.
This implies that by using AI-assisted tools in management, companies could reduce or eliminate repetitive tasks in the PM cycle, such as data collection, tracking, and reporting.
PM teams can then focus on people management, project vision, emotional intelligence, and conflict resolution.
Companies can refocus their efforts on stakeholder engagement, people management, and innovation. This would also leave managers with time for personal or professional development.
AI would thus complement project management processes by acting as a catalyst for advancements rather than replacing employee time.
But do we have AI or ML use cases for traditional project management? We don’t want a situation where we’re forcing a solution.
Do you need it? For example, there might be cases where efficiently built statistical tools using regression methods work effectively. In that case, investing in AI might be unnecessary.
Is implementing AI and ML technology worth the effort?
These are some of the questions you should consider before implementation.
AI continues to cause disruption, so managers must become AI-ready and engage heavily in AI-powered tools.
In short, AI is here to stay. Therefore, it’s in our best interest to leverage its capabilities in all phases of project management.
**About GlobalLogic**
A Hitachi Group Company
About GlobalLogic
GlobalLogic is a leader in digital engineering.
We help brands across the globe design and build innovative products, platforms, and digital experiences for the modern world.
By integrating experience design, complex engineering, and data expertise—we help our clients imagine what’s possible, and accelerate their transition into tomorrow’s digital businesses.
Headquartered in Silicon Valley, GlobalLogic operates design studios and engineering centers around the world, extending our deep expertise to customers in the automotive, communications, financial services, healthcare and life sciences, manufacturing, media and entertainment, semiconductor, and technology industries.
GlobalLogic is a Hitachi Group Company operating under Hitachi, Ltd. (TSE: 6501) which contributes to a sustainable society with a higher quality of life by driving innovation through data and technology as the Social Innovation Business.
Visit our website at globallogic.com.
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