Implications of AI For Project Management + What You Need To Know About Data Products
The rapid advancements in Artificial Intelligence (AI) play a critical role in different business settings. So it comes as no surprise that various tasks related to Project Management are also being transformed with the help of AI.
AI can be used to automate many project management tasks such as scheduling, resource allocation, and risk identification. This is done with the help of AI project management tools that are are now available to help us plan and execute our projects in an efficient and effective manner.
One of the most common uses of AI in project management is scheduling. It helps in predicting how long it will take to complete a task and what resources are required for its completion. AI helps in resource allocation by allocating resources based on their skillsets, availability and location. It also helps in risk identification by predicting possible risks before they occur so that they can be mitigated before they become a problem.
Here are three major implications of AI and how it can transform Project Management at any organization.
1) Role of AI in Administrative Tasks:
Administrative tasks and functions like planning, meeting, and daily updates can be given to AI tools for improved management. A report by KPMG showed a 15% improvement in productivity when organizations used AI tools.
2) Latest AI Systems Can Help Keep Projects Within Budget:
Project Managers required various data and calculations to estimate budget and time durations for projects in the past. But with AI-powered analysis tools, it has become relatively simple to make future projections. Now Project Managers can make decisions regarding future projects with more confidence.
3) Collect Unique Insights From Projects:
A key advantage of using AI technology in project management is that unique insights collected from the data will help address different risks involved in projects. These insights can further help in improving the decision-making capabilities of Project Managers.
One of the fastest ways to increase a company’s valuation is through data products. Unlocking data products can confer multiple benefits such as:
- Additional monetisation streams.
- Increased valuation.
- Building unique competitive advantages.
Who is this for?
This lesson is perfect for an executive or entrepreneur of a startup or a scale-up who wants to understand how data science can positively affect a valuation. This is extremely valuable for those who are fundraising, or are in a very competitive marketplace, and are looking for new monetisation streams for their business.
You can sign up for free here.
I was reading recently a very interesting article on O’Reilly’s blog: Designing great data products. I thought it would be good to summarise it and add some of my own thoughts, since it touches upon some of the themes that I am also covering in my work.
The blog discusses the issue of using data science to create products. One of the main issues in the design of data products, is that data scientists, quite often, do not have good business understanding. At the same time, people responsible for coming up with the products, e.g. product managers, might not be very familiar with the possibilities and limitations of machine learning.
You can read more on this topic on my post here.
The Data Product Framework for Startups
This is a framework for any entrepreneur or startup that is thinking about how to productise their data, and increase their valuation through data products. It presents a simple 3-step process that can help you clarify how to make the most out of your data strategy and your product strategy.
You can find it here.
AI is driving the need for change in project management. AI and data science need to be managed just like any other software and R&D activity, but they also require additional tasks, such as managing the data scientists, expectations and risks.
The simplified project management framework is a great and easy way to think of the project management process. It cuts down on the time needed to manage a project and also helps with tracking tasks and projects more easily. The framework provides an air-tight overview of the entire process, from start to finish. It will be obvious what tasks need to be done when they need to be done by, and who’s responsible for them.
On this event Dr Joseph Mallia is going to talk about this framework, which can be applied in AI, but also related disciplines such as software development
Make sure you grab your free ticket here.
Are you any of the following?
- A product manager or product owner?
- An entrepreneur
- Work in a startup or a scale-up
- A manager in a bigger organisation?
If yes, then it is quite likely that sooner or later you are going to have to deal with data science. As more and more companies adopt AI and data science, it is inevitable that those who don’t are simply left behind. Those who do adopt AI, see massive gains in efficiency.
On this webinar we discuss topics such as:
- What is data strategy?
- Why is it important?
- What can a company do to best deal with data strategy in the era of big data?
- How can data strategy help me build a superior product?
The event is presented by Denton Rawson is an entrepreneur and Founder of IOK Digital Ltd, which is a technology and AI consulting firm. With more than 20 years of experience in the technology industry. He has worked with some of the worlds Top Bluechip organisations in the F100 and F500 at stakeholder level: A proven track record in delivering value for organisations with technology.
You can grab your free ticket here!
Other Interesting Posts From Around The Web:
Data Science, AI and Big Data:
- Statistical Analysis Methods
- AI governance adoption is leveling off – what it means for enterprises
- Five Roles Every Data Science Team Should Hire
- Google is using AI to better detect searches from people in crisis
- Why Organisational Culture Is Important for Tech Start-ups