What is AI?
Artificial intelligence (AI) is a technology that has the power to transform how we work, and it’s already being used in many different industries.
AI in project management has a big impact, with companies like Slack, Amazon Web Services, Microsoft, and aqua offering tools that use AI to automate tasks for managers and team members.
Project management has been a long-time staple of business and is still strong. While the tools we use for testing software and managing projects have changed over the years, some things still need to change.
Project managers must keep an eye on deadlines, budgets, and resource allocation — all while keeping their team motivated and organised. No wonder project managers are some of the highest-paid professionals in the world!
But what if you could automate some of these processes or even the entire workflow? What if you could get your team to work together more effectively and increase ROI? What if you could ensure your team is always on track for success? Well… now you can! With AI in project management tools, you’ll be able to use automation to take care of all those pesky little details that would otherwise distract you from your actual work: leading your team!
Let’s look at the role of artificial intelligence in project management and how it works in project management tools now and in the future.
Benefits of AI based project management tools
Whether a small startup or an established corporation, AI-based project management tools will help you get things done more efficiently and effectively than ever before.
Let’s take a look at a few examples.
The role of bots and AI in project management is significant for time tracking. This allows managers to set up schedules using an algorithm that determines how to get as much work done as possible with a specific number of employees — and then implement those schedules automatically. The result? More efficient use of resources and more effective management of employee time.
Finally, there’s AI-powered reporting. This can set up reports based on specific metrics (like sales or employee satisfaction), which you wouldn’t be able to structure by yourself — too much data to analyse or requires a ridiculously long period of time in perspective.
These benefits are far from theoretical. Our overview of top AI testing trends has a number of real-life QA examples, including latest use cases offered by GPT-powered solutions.
Learn the 5 AI testing trends to save 12.8 hrs/week per specialist
Save time on repetitive tasks
Let’s say you have a project that requires certain tasks to be completed by specific dates. So far, so good. But if your team members are like most teams, they will also need regular updates on the status of their tasks and other projects around them. That means you’re going to spend too much time answering questions like “How’s it going?” or “When will this be done?” or “Why isn’t this done yet?”
But what if an AI system could be programmed with all those answers — and then answer them for you?
A good example here is test cases again. If you let AI write test cases for your testers and you don’t need to control them, in the end, you will get a big picture — all possible bottlenecks, where you need to put a person in charge instead of automation or AI, and if the defined time period was enough for these cases. So, then you don’t spend time finding these insights but only plan how to regroup your resources for better project management.
That would mean fewer interruptions and more time for strategic thinking about managing your resources and moving things forward in the long term.
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Create highly accurate estimates for projects
Using AI in software testing, you can create highly accurate estimates for projects that would have been impossible to do manually.
AI can help you predict the workload for your projects, how long each task will take and how many people it will require. The technology can also determine which tasks are most likely to be completed on time and which are most likely to fall behind schedule so that you can make adjustments if necessary.
Using AI in your project management processes means you’ll spend less time planning out projects and more time working on them which gives you more time to focus on other areas of your business.
Automate many of the processes
One of the most interesting applications of artificial intelligence in project management is its ability to automate processes that would otherwise be incredibly time-consuming.
As AI can proceed with a great amount of data in a minimal time, it gives a huge advantage to project managers. For example, AI bots analyse the big scope of the data, make certain discoveries that are important for clients and can take over the tedious task of writing and sending emails to them.
Or what if these bots could also create period-wise reports based on their team’s work results using specific metrics — like a number of bugs in code during holidays?
These are just two examples of how AI can make life easier for PMs by taking care of tedious tasks so they can focus on what matters.
It’s not just a buzzword; it’s a fact. Artificial intelligence (AI), machine learning, and bots are already used in project management. And they’re doing a lot more than just automating mundane tasks. And it is a huge advantage in favor of them.
Artificial intelligence is very useful in QA as well. Vendors can adapt the GPT language model to make tests better and with more context than the free ChatGPT would. aqua’s AI Copilot does just that, and it is free for all aqua users. You can use it for project management to prioritise items and remove duplicates among other things.
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