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By Lars Janowski, Head of Transformation, Innovation and Technology Advisory, HKA Australia
On an average, more than 50 percent of projects fail. Without touching on failure factors this staggering number applies across all sorts of project environments–IT, construction, engineering, or transformation projects.
One would assume we’d figured out by now how to successfully deliver projects on time, on a budget, and to the desired scope and benefits; But apparently, we haven’t.
Enter Artificial Intelligence (AI)
AI is one of the buzzwords du jour, thanks to frequent tech media news about voice-enabled personal assistants and self-driving cars.
However, the concept of AI is older than project management itself—going as far back as 380 BC to Greek philosophers such as Aristotles who described the syllogism, a method of mechanical thought.
Artificial intelligence is a system or device that acts intelligently and is divided into two categories. Artificial Narrow Intelligence systems can perform a single, mostly repetitive task, extremely well - in most cases, better than any human being. Bots are a good example, retrieving answers from a database in response to a simple question.
Artificial General Intelligence systems and machines can, in theory, handle any task. They have the ability to function like the human brain. With the help of machine learning, this category of AI will be able to teach itself and apply cognitive thinking. I say ‘will’ because this kind of AI is still in its infancy. It‘s this kind of AI that seems to worry a lot of people and makes great science fiction movies.
Project Management and AI relation
Project management is about dealing with complexity, making sense of vast amounts of information to drive timely intelligent actions and constantly working with assumptions and constraints. That is if you have an objective and a plan in the first place.
There’s a much less attractive side of project management, though–the part where a huge amount of time and resources is spent on mundane administrative tasks and performance monitoring.
Then there’s the most important part of project management: dealing effectively with people. Low take-up of senior management ownership and ineffective stakeholder engagement, rank in the top 10 of every project failure list.
AI will take over the vast majority of administrative and technical project management activities across the full project life-cycle
The issue will be: how do we use these tools to best effect? What aspects of project management would be enhanced and enabled with these tools, and which would be diminished by their application? On what basis will we make those decisions? We need to think about this now because the application of AI in project management is not the future, it’s already begun. Google, Microsoft, Apple, and Amazon have recently formed a partnership on AI, with the aim to benefit people and the society. Interestingly, they are all heavy users of project management, so rest assured, it won’t be long before their efforts will disrupt traditional project management environments.
With further research in deep learning, AI will develop progressively and exponentially over the next few years in generational stages.
First Generation – Simple Task Automation
Artificial Narrow Intelligence-driven virtual PMO assistants will take care of the dreaded administrative tasks, freeing up time for human resources to focus on higher-value activities. Several systems are already out there that autonomously deal with managing meeting invitation processes, automate parts of the communication process, or provide bots to take care of simple email responses to “obvious” questions from project stakeholders.
Second Generation – Autonomous analysis of existing project information
AI will evolve into more analytical and data-driven tasks. Artificial General Intelligence systems will start learning about specific project management data and begin understanding correlations, linking data and applying analytics to available project information, and providing ‘insights’ back to us humans. This will be mostly autonomous, only involving things with a pulse to provide direction to AI on where to look, and what to analyze and present.
The challenge here will be ‘GIGO’ (Garbage In, Garbage Out). The credibility of the machine may be so compelling that we don’t examine or question the information project stakeholders have provided. Danger, Will Robinson.
Third Generation - Deep Learning, Data Mining, Interpretation, & Recommendations
This is the generation of AI where it gets interesting. AI will be a project manager’s everyday companion. You might even give “it” a name and interact with “Rosie” (that’ll be my choice) as you would with your colleagues, through voice, electronic messages, or even gestures on your smart-watch. The longer you work with the Rosie, the better she’ll anticipate your responses. On international projects, she will be able to issue information in whatever language is required. Rosie will dig deep into all sorts of big data, far beyond what’s available from your organization. She will interact 24/7 with the other Rosies, the web, and PM data sources around the world, constantly sharing and learning how to improve things, providing actionable advice to her human colleagues. She will address the GIGO challenge by providing relevant information that has proven to work and led to successful project delivery.
In short, AI will take over the vast majority of administrative and technical project management activities across the full project life-cycle.
So how is that a good thing?
AI, the Internet of Things, and digital futures have arrived. This will fundamentally alter the way we live, work, and relate to one another. AI will enable the project management community to improve project delivery. Success is only driven partly by technical ability. The part AI won’t be able to do is leadership and motivation. AI can’t provide empathy with our clients or the emotional intelligence to create a connection with their beliefs, goals, and vision.
At the end of the day, AI will enable us to be more human.