Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...Full Bio
Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...
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3 ways AI will change project management for the better
If you've read any tech media recently, then you're probably hearing a lot about artificial intelligence (AI). Some people herald it as the promise of the future, while others are skeptical - even fearful - of its impacts on society, culture, and our workplaces.
As it turns out, the buzz around AI has mostly resulted in a lot of conflicting emotions. A recent Atlassian user survey found that 87 percent of respondents said artificial intelligence (AI) will change their job in the next three years. Almost the same number said that some part of their job could be done by AI. And while 86 percent of those surveyed said they were excited, 87 percent also reported feeling skeptical.
However, AI isn't something to fear. It may even be your best team member, especially for project managers. AI for project management is on the rise, and the way things are going, it's going to help teams make smarter decisions and move faster. Let's take a look.
What is project management AI ?
Project management AI is a system that can perform the day-to-day management and administration of projects without requiring human input. It will not only automate simple tasks, but will also develop an understanding of key project performance. Project management AI can then use this understanding to uncover insights, perform more complex tasks, make recommendations, and make decisions â?? sometimes in ways people just can't do today.
Ultimately, an AI system will save you time while improving outcomes for your projects and team.
Project management AI provides a level of service that rises above many of the bots available today. For example, a HipChat bot that lets you check on the status of a JIRA task quickly, while useful, is not considered project management AI. Similarly, an algorithm that applies machine learning to predict estimates for tasks, while interesting, isn't AI either. It's only when you start bringing bots and algorithms together that you start to realize the potential of project management AI.
Today: narrow project assistants
Early project management AI will be a project assistant focused on a narrow area of managing a project or team. By focusing on supporting a team in one specific area rather than dealing with all the complexities involved in managing a project, project management AI will be useful to teams sooner rather than later.
My company, Stratejos, has started out by assisting with estimates, budget, and sprint management. Other companies, such as Memo, focus on assisting with the management of team knowledge.
Within these narrow areas, these early project management AI tools are giving us a glimpse of the future where AI automates tasks, provides insights, and even communicates with the team.
However, there are some challenges. These early, narrow project management AI tools rely on people to input data correctly, update tools in a timely manner, and make corrections. The limited capabilities also mean that humans are still a step ahead - for now. In order to provide even more value, project management AI needs to evolve.
Second generation: expanding project understanding
The next step for these narrow assistants is to start expanding their understanding of projects and teams.
At Stratejos, we started out dealing with estimates, actuals, sprints, and budgets, but we are now expanding to processing information that can be learned from task descriptions. By tying together sprint history with people's individual efforts, we can show that your key engineer is being pulled away each week to other projects.
As assistants expand their understanding, new metrics will be revealed that weren't previously possible, such as quality, performance, learning, change, and effort.
For example, AI will know the changes made to source code and link those changes to people and tasks performed. This will allow AI to link bugs reported to a line of code, the person that wrote it, and the tasks that relate to it. This will allow for real, actionable indicators of team and project performance.
With more data points about projects, predictions will become more reliable, more appropriate, and easier for people to understand. But even this enhanced understanding will still require one more thing: usable data.