If you have a team of software engineers and want to move them to Mac, you will need to consider a number of things before you do so.
AI-Powered Project Management for Software Development
Major changes are coming to the way software development projects are managed courtesy of Artificial Intelligence. Of course, some will be skeptical, but a lot of tasks are about to become a lot easier and faster to pave the way for all stakeholders to make better data-driven decisions.
As the impact of AI varies by role, we’ll focus here on benefits and questions likely of interest to Engineering and Business Intelligence Managers. And while AI may not replace your job anytime soon, it might lead you to want a new job title. So, let’s take a look!
What is an AI Project Manager?
It’s not an AI that manages projects, that’d be a Project Manager AI. It’s going to be one of those centuries where we’ll be continually asking, “Is it Real or Digital?” Flashback…
An AI Project Manager is a real person who specializes in managing AI projects. Like project managers, they have a long list of responsibilities such as:
- Provide oversight to facilitate projects from initiation to release
- Acquire and share technical specifications from stakeholders
- Identify risks and provide guidance to mitigate them
- Define, plan and track project progress toward milestones and goals
- Determine and adhere to project budget and timelines
- Everyone’s favorite – Duties as Assigned!
As you would expect, an AI project manager has additional expertise and experience in areas of Machine Learning, Deep Learning, Automation, Natural Language Processing, Big Data, and in different cases text, speech, and visual recognition systems. AI project managers can be involved in developing AI systems and/or integrating them into normalized business operations (digital transformation initiatives).
Gitential’s in the process of rolling out an Early Access Program that will introduce all of our users to an AI-Powered Digital Assistant for Software Development Teams and Projects.
What is an AI-Powered System?
How is AI Used in Project Management?
Ways AI Can Help Project Managers
Boost Team Performance
See by org/project/team/developer level where the greatest improvements can be made - and how to make them.
Optimize Resource Allocation
Identify the best combination of developers for a project - like best Python or C++ developers with additional metrics like Pull Request Commenting rates or lowest defect density.
Enable More Accurate Planning and Budgeting
Use historical data to compare with project requirements and the relative skill of developers in specific languages. Help to assess whether to outsource for a Swift specialist or provide training for your best Objective-C developer.
Automate Time-Consuming Tasks
Complexity of these calculations increase by team size. Hours of research are streamlined into minutes.
Improve Delivery Processes
Where are your bottlenecks - and actionable insights on how to fix them.
Better Align Teams with Company Objectives
Know where your team is at compared to strategic interests - Delivery speed? Quality? Budget?
Receive alerts 24-7-365 whenever key indicators exceed the standards you set.
But, let’s take a closer look into how we see AI working with something of interest to just about all software development stakeholders.
How Can Managers Use AI to Drive Team Performance?
Improving cycle time is of interest to just about everyone. It’s a sort of a top-level metric that C-levels especially like to see steadily improving because it has the best correlation to ROI. It is also an aggregate of nearly all other software development metrics. With conventional analytics, no matter how good, managers still have to dig through their team’s data to discover and prioritize contributing factors.
“What’s slowing down my Cycle Time?” With an AI-Powered Digital Assistant, you merely need to ask the question and you’ll see what’s causing your cycle time to slow down the most – and best “most likely” solutions. Moreover, you can view it organization-wide, by project, team, or individual developer.
- Avg. development time: the total time since creating the first commit until creating a pull request
- Avg. pickup time: time between PR creation and moment when the review started
- Avg. review time: time that was taken to review the commit until it was closed or merged
In this chart, we can see that Pickup and Review times took altogether almost as much as the Development time itself. This kind of practice can regularly delay the delivery processes. If the Pickup time was faster, deployment of this pull request could be faster by 2-3 days, which could translate to two merged or closed Pull Requests a week.
You should take a closer look at your team’s composition. There probably are not enough senior developers that can pick up and review pull requests regularly to merge them in a timely manner. Try to reallocate the responsibilities within the team differently, so there’s always someone available to work on pull requests at least every 1-2 days.
No Improvement? Next Steps:
Adding one more senior developer to the project should fix the problem.
What are the Cons of AI-Driven Project Management?
Everything to this point has focused on talking up the benefits and pros of AI for project management. So, what are the negatives?
Until recently, AI required a huge investment to implement. But companies that have made that investment, like Gitential and Revenue.AI, offer access to AI capabilities with Software as a Service. This offers businesses an opportunity to leapfrog technologies and rapidly implement AI capabilities at a reasonable cost to achieve an even greater ROI.
Some will argue that AI increases your dependency on machines. Where software development is concerned, machine-dependency is a given. Coding on a napkin?
There is merit in this argument in that some may lose touch with the processes for conducting manual calculations and analysis. Some might let the AI override their own knowledge, experience, discretion, and judgment. The AI’s role is as an advisor – it is not the decision-maker. We always need to keep that in mind.
Others argue that AI will change the way we work. Yes. It can take over a lot of laborious, monotonous, time-consuming, and costly tasks. How many companies are committed to making their products and services slower, more costly, with more defects? Okay, soooo…. governments are not companies… um, well, officially – not yet… None. At least, most try to avoid these things.
Can AI Replace Project Managers?
This could be a big negative, but… it’s not. At least, not yet. The faster technology evolves, the faster it will continue to evolve. “Is Current Progress in Artificial Intelligence Exponential?” and its supporting links by DiggingDeepAmidstChaos digs deep and hard into AI’s potential whether we frame AI’s evolution in linear or exponential terms.
Honestly though, barring an Extinction Level Event, eventually, AI will be able to replace all jobs.
Ray Kurzweil estimates AI will achieve human-level intelligence in 2029, and that “singularity” will be achieved by 2045.
As IT Workers Increase, So Will the Demand for More IT Workers
“...according to Israel’s Innovation Authority (IIA), there is still a shortage of between 12.5k and 18.5k IT specialists. So, despite every effort over 20 years, the median shortage is exactly the same: ~15k tech workers. The long-term (5-10 year) goal now is to increase Israel’s percentage of high-tech workers from 9.6% to 15% of the workforce.”
Israel’s like a Microcosm of global IT demand in consideration that China alone is in need of 55 million more skilled workers. By the time China generates 55 million more skilled workers, they’ll need another 55 million. Probably more.
There’s a lot to cover about AI and how it’s going to impact all of us, but for now – it definitely won’t be replacing project managers or software developers.
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