AI-Powered Project Management for Software Development

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Run-through

The value of AI-powered Business Intelligence

What benefits can AI-powered Business Intelligence can bring? While this may be of interest to true blue BI Managers and Analysts, business intelligence is making its way into a lot of other roles. Between skill shortages, job title overlap, and a growing interest in cultivating cross-functional teams, BI is pretty much for everyone who has a mind to be more efficient, productive, and profitable.

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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?

To borrow from DataRobot’s CEO, Jeremy Achin, “AI is a computer system able to perform tasks that ordinarily require human intelligence.” He goes on to associate AI with Machine Learning and Deep Learning, but sometimes, “very boring things like rules.” It uses algorithms to repeatedly cycle through massive amounts of data to find patterns, relationships, and even insights that would take regular people far, far longer. Human intelligence is typically measured as Intelligence Quotient (IQ). The average human IQ is roughly 100, very few people have scored under 70 or over 130. Ainan Cawley has the highest recorded IQ score of 263. AIs are measured against the Turing Test, perhaps less a measure of intelligence than its ability to mimic intelligence. But, it’s fun to make absurd comparisons. It’d take the average person about 10,000 years to read 1 TB of text data, say nothing of validating or analyzing it. Cawley could probably read 1 TB in just 2,500 years. While not exactly the same thing as reading, Tencent Sort set the 2019 record for sorting 100 TB in just over two minutes in 2019. That’s like an exercise in alphabetizing file names.

How is AI Used in Project Management?

Project management is inherent to and overlaps with many job titles – in companies of all shapes and sizes. AI’s useful for all stakeholders in software development projects. As we envision it, AI can provide project managers with Cognitive Analytics capabilities using “Google-like” queries for data-driven, actionable insights in real-time. The following are good examples of how AI can work to help you address a wide range of software development issues.

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?

Real-Time Awareness

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.

 

The Data:

  • 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

Summary:

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.

Action:

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.

Chart from Ray Kurzweil’s book from 2005, “The Singularity is Near.”

As IT Workers Increase, So Will the Demand for More IT Workers

Unemployment is fairly low, almost globally, while demand for skilled IT professionals continues to grow. Israel is an interesting case, with a population of just 9 million or so. Twenty years ago, Israeli Innovation Authority projected that it needed to double the country’s population of tech workers, from about 4.5% to 9%. They needed 15k more tech 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.

About Gitential

Gitential is an Analytics and Engineering Intelligence service provider bringing visibility and optimization highlights on teams’ productivity. Our mission is to augment decision-making with smart-recommendations to improve DevOps and DataOps teams’ performance and to proactively mitigate risk areas within development projects while bringing visibility and turning the development sector more fact-based. Please take a moment to arrange a free demo – or sign up for a free trial, no credit card is needed.

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