Artificial intelligence (A.I.) has taken the media by storm, with new groundbreaking accomplishments by global companies. Google’s DeepMind recently beat a world champion of Go, which is said to be the most advanced board game on this planet. Moreover, DeepMind is now able to assist doctors during surgery, detect risk of blindness in an early state to improve the chances of recovery, and other important breakthroughs such as natural language recognition, object detection in images, and face recognition.
Most recently the DeepMind team has been able to generate natural-sounding music and speech based on data from its neural network, WaveNet. A survey showed that the A.I.-generated voice sounded more natural to the sample group of both English and Mandarin Chinese speakers than Google’s other text-to-speech technologies developed by other means, though WaveNet was still not able to outperform the recorded voice of real human beings.
IBM’s Watson is able to, among other things, gather, analyze, and provide you with detailed insights into your personality based solely on data from your Twitter account. There are already many companies in this space, and the consumer will, in the coming months and years and with or without their knowledge, begin to benefit from some of these technological advances.
One feature that many consumers have already played around with are the personal mobile assistants, including Google Assistant, Apple Siri, Microsoft Cortana, Facebook M, and many others. These bots are already helping people perform daily tasks, saving time and energy by making photos searchable with objects and people present in them, uncluttering your inbox, and automatically generating subtitles for your videos. But this is still just the beginning.
One specific space ripe for A.I help is the project management field — and thereby technically all industries. Major projects, whether on a private or governmental level, are prone to go overdue or over budget, sometimes both. This all comes down to inaccurate planning in the initial phase of the project. It’s an ideal target for machine learning.
Project managers face on a daily basis a large number of unknown factors that need to be taken into consideration before, during, and after the project: estimates, employee allocation and utilization, task management, and more. There are many unknown values to play around with, which often turns into too much information. A few examples from Denmark suggest that even very experienced entities encounter these problems, e.g. the Eurovision Song Contest in Copenhagen, Rejsekort (the Travel Card system for public transportation), and the national digital health journaling systems. There are many other examples from Denmark alone.
To help this problem, artificial intelligence and machine-learning technology are now beginning to penetrate the market for project management tools. Right now project managers are only able to base their decisions, estimates, and so forth on their own previous experience and cannot automatically benefit from the knowledge that the rest of the world’s project managers are dealing with. That is where artificial intelligence comes in. Intelligent software is able to grasp data from across organizations and various types of projects (whether private or public) and tasks, anonymize this data, and create an algorithm to more accurately estimate some of the unknown variables including the schedule, budget, and resource utilization.
For every piece of data added to the intelligent project management system, the A.I.-generated algorithm will be updated and improved. This results in better and more justified decisions from project managers, as well as the individual team members. In the end, providing and supporting more stable projects that stay on track makes your team able to deliver better projects in time and on budget.
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