The AI project management driven revolution is here
Since our article How AI Will Transform Project Management, was published in Harvard Business Review in February, we have seen exponential growth in publications and discussions on this topic that will bring the most significant disruption in our profession since its inception.
AI will drive efficiency
AI language models, like ChatGPT, are revolutionising how projects are managed as we write this. By analysing large amounts of data, automating tasks, and offering real-time insights, AI will soon help project managers be more efficient, make better decisions and improve project outcomes.
AI offers several advantages with one of the most significant being the amount of time saved. Through automating administrative tasks like scheduling and data entry, project managers can save up to 20% of their time. This will allow project managers to concentrate on more critical tasks such as stakeholder management.
More accurate insights
In addition to saving time, these new technologies will improve project outcomes by providing more accurate data analysis and insights. Project managers can make better decisions and increase success rates by leveraging AI. For instance, PwC’s Sizing the Prize Global AI study found that using AI to analyse project data can lead to a 15% increase in project success rates.
AI language models will also enhance risk management. By analysing large amounts of data from diverse sources, project managers can identify potential risks and take proactive measures to mitigate them. According to Deloitte, using AI to analyse social media and news data can improve risk management by up to 60%.
Reduce costs
Gartner’s 2019 The Future of Project Management’s Global Outlook shows that project managers can reduce project costs by up to 10% by optimising resource allocation. This enables organisations to complete projects more quickly and with fewer resources. In addition, an Accenture study indicates that AI language models can increase team productivity by up to 25% by providing real-time communication and collaboration tools among project team members.
Real world examples
Several companies are already implementing AI models in their project management. Siemens uses AI to analyse project data and identify potential issues before they become major problems, resulting in more efficient project completion with fewer cost overruns. Bechtel, a construction company, uses AI to analyse project data and identify cost savings and efficiency improvement opportunities. Similarly, IBM and Microsoft are developing AI-powered project management tools, which automate specific tasks, provide real-time data analysis and insights, and facilitate collaboration and communication among team members.
As AI continues to transform our profession, project managers will need to develop new skills to take full advantage of the technology. Some of the skills that will be increasingly important include:
Data analysis and interpretation: with AI language models providing more data and insights than ever, project managers must be skilled at identifying trends and analysing and interpreting this data to make better-informed decisions.
Communication and collaboration: project managers will need to be skilled at using real-time communication tools to facilitate collaboration and communication effectively.
Strategic planning and risk management: with AI language models providing more accurate risk analysis and insights, project managers will need to be skilled at strategic planning and risk management.
Technical knowledge: with AI language models becoming increasingly complex, project managers will need to understand the technical aspects of AI, including machine learning algorithms and natural language processing.
Adaptability: with AI language models evolving rapidly, project managers must be adaptable and open to change. This will require a willingness to learn new skills, experiment with new tools and be open to new ideas and approaches.
AI is not science fiction any longer and it is already causing significant changes in project management. It is revolutionizing the way projects are executed by delivering time savings, better project results, improved risk management, increased efficiency, and better communication and collaboration. Project managers must step up and keep themselves updated with the latest technological advancements and adjust their skills to urgently increase the value delivered to their organisations.
You may also be interested in:
- APM research on Artificial Intelligence in project management
- The event on Artificial Intelligence projects
- What is project data analytics?
is Strategy Implementation Institute founder, and author of the HBR Project Management Handbook.
2 comments
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This is an excellent article. Truely, there are numerous things you can use AI to accomplish within a short time. You can also consider using Bard AI by google, it is like ChatGPT by OpenAI. They are awesome tools. I use both to simulate events and it is beyond words the information you can gather. By all means, if you are a Project Manager and want to stay relevant in this profession, please adapt now. More so, if you have a little programming knowledge, this makes a whole lot of difference. The truth remains, computers will give back information according to the level of your intelligence. "Garbage in, garbage out."
Agree, we as project professionals need to know our stuff and use AI as a tool…not the answer; like humans, AI can make mistakes too ;)
Although the article provides an insight on AI applications in Project Management, it is full of many understood phenomena that would surely take place once you go for AI. I began reading it for some new information on the subject, but found statements that did not actually advance knowledge. For instance, "with AI language models providing more data and insights than ever" is a very evident thing to happen! The statement "Through automating administrative tasks like scheduling and data entry, project managers can save up to 20% of their time." has no backing/reference. It seems a rough analysis. Even if it is only a guess, quoting such percentages or expected changes gives a weak foundation of the opinions expressed in this blog. "Real world examples" is really a good, brief section the reader would love to refer to. I suggest if anyone has a sufficiently good knowledge base, a series of articles on "AI Applications on Projects" and "Real-Life Cases of AI Implementation" should be initiated. This is certainly we need to see here rather than articles merely praising AI. With the fact that AI is no more a fiction and is a buzzword today, writings explaining the roadmap to implement AI on projects facilitating their management and control will serve the purpose! This is with due apology.