Guest post by qualified Project Manager, Declan Foster
“AI will create jobs if it succeeds and jobs will be destroyed if it fails”. This quote could have been ensured if not for the fact that it is a tweet created by GPT-3, a massive neural network AI tool capable of generating human -like text and can also generate computer code.
This tool was developed by Elon Musk’s Open AI, a San Francisco -based AI the research laboratory, has created a lot of buzz in recent days and indicates the seismic shift that AI will bring to most industries and professions.
When Declan Foster began his project management career in the late 90s, the profession gained management in virtual teams due to the emerging popularity of offshoring and follow-the-sun support and delivery models. software development. Fast forward 20 years, and the profession is now faced with the challenge of managing non-human resources; chatbots, digital employees, and machine learning tools.
The project management profession is at a point of increasing strength due to the challenges and opportunities presented by the rapid development in AI technologies. The abundance of big data, advances in computer technology, and algorithms have led to giant leaps in the adoption of AI technology in recent years.
What is AI?
AI is defined as machines that act to simulate human cognition to solve problems. The most common components are Machine Learning (ML), Natural Language Processing (NLP), and Robotics. ML uses statistics and algorithms and large sets of data to predict outcomes, whether predicting from a scan whether a particular growth is cancerous or predicting whether a loan application will default.
The most popular examples of NLP can be said to be Alexa or the chatbots you may have encountered when using your utility or bank website. Self -driving vehicles are the most obvious forms of robots we see in public spaces.
Use cases for Machine Learning in project management are placed in two areas; classification and return. For classification, it is essentially a yes or no strategy to predict whether a project is successful or not or whether the project is likely to be finished on time.
Where there are continuous values, regression algorithms, eg are used, based on the x factor, what is the predicted cost of completing a particular task? Or what is the expected completion delay based on risk profile and historical data? In addition, we can use Natural Language (NLP) emotional analysis to understand how our stakeholders might feel about the changes brought about by a project.
Existing Threats to the Profession.
So, is there an existing threat to the project management profession? The short answer is no, but there is no doubt that AI will affect the profession. To understand the threat to any job, we can use the automated vulnerability matrix created by MIT.
Based on the level of risk in the defined core skill and level of threat to the delivery mechanism, we can place jobs in a deconstructed, displaced, disrupt, or rigid category.
Due to the unique core skill-set of a good project manager and the current delivery mechanism that is too expensive or challenging to automate, the profession can be placed in the ‘Durable Jobs’ category. Some might argue that this would be a deconstructed role, such as college professors whose skills remain safe but had to get used to delivering online education, even before Covid-19.
It can be useful for a project manager to have insights into the durability of the jobs they can manage or interact with. US-based National Public Radio has created a practical tool that demonstrates the possibility of any role being automated in the next 20 years, e.g., according to the tool, the bookkeeper’s role has a 97.6% chance of being automate.
Should project managers be advocates for the introduction of AI in our projects and organizations? Professor Paul Boudreau, the author of “Applying Artificial Intelligence to Project Management,” certainly thinks so. He believes that the application of AI in project management can increase “project success rates to 95% or higher continuously.”
As part of his AI research, Professor Boudreau developed an AI project success prediction tool based on a neural network that used 87 factors, or features, from 35 real projects to predict success. of any project. This work provides a fascinating insight into how AI, and machine learning in particular, and how it can be applied to project management as soon as possible. You can visit Stonemeadow Consulting to get more details on the tool.
Other major players in this space include UK -based SharkTower and Scopemaster. Shark tower uses machine learning models to analyze data to spot problems before they occur, showing the project’s health goal, slippage, and team sentiment. ScopeMaster is a requirements analyzer tool that uses AI to find and fix issues as needed, saving significant rework on software projects.
Challenges for Project Management
Implementing AI in project management is not without its challenges. At least which concerns data bias and privacy. However, adequately designed machine learning tools can reduce or eliminate bias. They don’t have to retain data once the model is trained, which helps with data privacy concerns.
Colin Hammond agrees that there are many challenges to overcome, including getting project managers to accept the need for AI. “It was a bit like when I started using spellcheckers in word processing. I felt like I didn’t need them because my spelling was good, but now that I’m used to them, I wouldn’t be without a spellchecker and grammar checker”, he said. Hammond.
Project Management Opportunities
AI will not replace the project management profession, but we must take the opportunities presented by AI to improve our profession. Nikki Horwood, from Shark tower, believes AI can help project managers become project leaders. “Can AI help the project management profession provide strategic advice and measurable business value?”, Horwood said.
Thought leaders, including Professor Thomas Malone of MIT, advocated for a collective intellectual approach when using AI, where “people and computers can be connected so that together they act smarter than any person, group, or computer who has acted previously “.
Top Tips for the Future- prove your career as a Project Manager in the Age of AI
- Develop or improve irreplaceable AI skills. This includes collaboration, imagination, teamwork, coaching, and creativity.
- Educate yourself in Data Science and AI. While you don’t necessarily have to have a degree in AI, you will need to have enough education and knowledge to have knowledgeable and meaningful conversations with data scientists and machine learning experts.
- Learn to understand and value your project data. How and where the data is currently obtained, and what you can do to improve the quality and extent of project data used in machine learning.
- Be proactive in preparing your organization for AI and be seen as a champion for AI. You can start by assessing your maturity in the organization. Use an AI maturity model to measure where your organization is now and wants to be in five years. Microsoft has created a useful model of maturity. It breaks the maturity of AI into an organization into four stages; Foundation, Approaching, Aspirational and Mature.
We are in an exciting time for AI. It has gone from science fiction to buzzword to become a true provider of business innovation. The introduction of AI tools can free up time for those in project management to perform more value-adding activities, including team building and development, stakeholder engagement, and building relationship. In addition, many project managers will be responsible for implementing AI systems in the coming years.
Disclaimer: The opinions expressed within this article are the personal opinions of the author. The facts and opinions appearing in the article do not reflect the views of knews.uk and knews.uk does not assume any responsibility or liability for the same.