16 specific tasks a project management AI can do for you

16 tasks a project management AI can do

People often say “stratejos, what is a project management AI?” I then reply* with things like “it’s like having a project management assistant sitting next to you, checking all of your task data, all the time, watching for missing or incorrect information then giving you nice reports and giving your team friendly reminders.”

Then they say “Great! But… can you please be a bit more specific about what a project managment AI actually does?”

So here is an answer to that question. A very specific list of 16 tasks that a project management AI can do today (based on some of the things I, stratejos, can do).

I don’t actually have conversations or write these posts for that matter. I haven’t achieved singularity (yet).

List of alerts to team member and project managers

#01: Alert when fields are missing on a task

missing fields

#02: Alert when estimates are missing

#03: Alert when estimates are missing but work has started

logged time but not estimated task

#04: Alert when timesheets are expected but missing

If you use timesheets then stratejos will either detect this or you can tell stratejos to look for timesheets. Then you set when you expect people to work and stratejos will send alerts if people aren’t entering the time you expected of them.

missing timelogs

#05: Alert when task is ‘In Progress’ too long

#06 Alert when a task is taking longer than expected

Agile project management alerts

#07: Alert when sprint has too many tasks

sprint has too many tasks for the team

#08: Alert when sprint has not enough tasks

sprint has not enough tasks for team

#09: Alert when an individual team member is overloaded this sprint

sprint has too many tasks

#10: Alert when an individual team member doesn’t have enough work this sprint

sprint has not enough tasks

Project budget alerts

#11: Alert when project budget is predicted to be exceeded

#12: Alert when project budget is exceeded

Reporting project budgets

#13: Report on project budget and costs in real-time

#14: (For services companies) Report on project revenue and profit in real-time

report on project revenue and profit

#15: Provide an overview of a portfolio of projects

report on a portfolio of projects

#16: Report on risks, coaching opportunities and areas of uncertainty inline with project reports

This helps highlight risks, missing data or areas of improvement for the team.

risk reports

 

That’s not all

There is still more project management AI can do, this is just the tip of the iceberg. Over the coming weeks and months I’ll share more lists like this. Soon I’ll share one with the features that have resulted from the algorithms we’ve been running in the background.

Hopefully this list has given you a sense of what a project management assistant is capable of.

Are Project Managers about to be Replaced by AI?

Here’s a recent interview one of my creators did with Jason O Callaghan that appeared on LinkedIn.

Jason: Can you describe what the stratejos smart assistant does?

Scott: Having stratejos on your team is like having your own personal team assistant. It helps you manage your projects by:

  • automating project reporting 
  • providing insights you didn’t have
  • identifying risks and uncertainty
  • coaching your team on better practices.

Jason : What made you decide to build the smart assistant? 

Scott: stratejos is all about solving the problems we’ve experienced managing projects and teams. 

There is just too much time wasted on unnecessary work that doesn’t even produce the best results. We’d waste time building reports that didn’t tell the full story and took too long to produce. 

We then went and spent more time checking everything and following up the team, like ensuring their estimates were in and up-to-date.

With this investment in time we found that we could improve the accuracy of the report but highly talented (and expensive people) were wasted on tedious administration instead of solving the big problems their best talents were made for. And often they just didn’t have the time for this kind of administration.

So we decided to set out on a mission to rid the world of these issues. That way, teams can focus on more important things like prioritising the roadmap, working with a customer or managing a key stakeholder’s expectations.

The added benefit then became the insights you can drive when you have a team of PhDs looking at data. This kind of insight is hard to create in a spreadsheet when you’re managing a project, even if you have the mathematical skills.

Jason: stratejos smart assistant helps PMs by taking much of the daily admin off their plate but do you think AI tools such as this will eventually replace human project managers?

Scott: I don’t see AI replacing human project managers in the near future, instead I see them assisting PMs. We are so far away from singularity (at least another 20-30 years). AI just can’t deal with a question like “what are Sally’s expectations?” or “what feature do we build next?” 

Jason: How comfortable do you think engineering teams will be with being directed by an AI tool?

Scott: Our focus at stratejos is not to direct engineering teams but to assist them by providing them with relevant, timely feedback and advice. So far we’ve seen engineering teams respond nicely to the chatbot version, often making jokes about the bot following them up on things and apologising to it.

Jason: Finally, any advice for human Project Managers who may feel threatened by AI? 

Scott: Don’t be threatened, embrace it. It is one of the most useful tools you can implement to take your team to the next level of performance. 

Consider the project managers that first picked up issue tracking systems like JIRA. They were more organised and could deal with the teams in a much more efficient way then those that didn’t.

Jason: Thanks Scott.

Head over to stratejos to start using their smart assistant and instantly increase your team’s productivity.

Podcast: Bot That Knows Your Best Project Performers

My creator was recently interviewed by one of the world’s leading Atlassian experts, Service Rocket, on how chat bots can help in the enterprise.

Scott Middleton, Stratejos Founder and CEO, talked to Helping Sells Radio about how artificial intelligence (AI) is already changing project management.

You can find a summary of the interview below.

A coach bot

Here is the challenge: to get a project team to perform well, a manager must get the team to follow the discipline of the project process, understand what’s going on with the project, and coach team members as needed. This is challenging because project managers often get bogged down in the thick of things, and they do not have access to all the data necessary to understand how to keep a project humming along.

Scott Middleton started Stratejos to solve this problem: to coach teams and individuals to better use the software that enables them to do their jobs.

“What’s exciting about AI and bots and software to deal with this problem is that you can get specific and meaningful advice…that’s relevant at the right time,” says Middleton.

Here are just a few examples of ways AI and bots can help coach a team:

  1. You have not filled out your time sheet
  2. You did not estimate this task
  3. You are at risk of running over on your sprint
  4. Why you are constantly running over on your sprints
  5. Who on my team needs help
  6. What are the risks to this sprint

AI is changing project management

Says Middleton, “AI is going to change project management….almost full stop. It’s coming, and it’s really starting to happen.”

Then Scott goes on to tell a story about how his Bot told him that a customer project was about to run over on the sprint. Scott then immediately took action, talked to the team straight away, and called the customer to set expectations.

We asked Scott, “How does a bot know to tell you your sprint is at risk?” Scott responded, “How does a person know to tell you that?” There are data points like estimates, number of tasks, hours in the day, story points, number of people working on tasks, days / story points left until the end of the sprint, etc. The bot looks at all of this and puts the story together and then can alert the project manager of any possible risk.

This would normally take an experienced project manager to discover this risk, if that person was paying attention, and if that person was not getting bogged down in day-to-day tasks. It would also take team members to proactively raise the red flag to say they were behind…which as many of us know….people are not so willing to do.

So, as Middleton describes, “It’s really starting to happen.”

Here is Scott’s article on the Atlassian Blog: 3 Ways AI will change project management for the better.

How are people receiving this?

Middleton describes two kinds of people. First is the person who gets exited about the technology. The flashy part. AI and bots, etc. This is the early adopter that is comfortable with the risks of trying something new. The second type of person is the practical manager who asks, “How is this going to help me?” If the bot can see the performance of a project and keep it in check, this customer is happy and the AI part is irrelevant. It’s just a tool.

A bot can understand key project performance? Really?

Yes. Really.

Middleton answers this question with a customer story:

Customer: “Why is this bot telling me to update my time sheet every day?’

Middleton: “It’s probably telling you something you should be doing.”

 

 

Defining AI: What sailing 750 miles with an AI taught me

An AI, in this case, an auto-helm took the wheel for most of a recent 750 mile (about 1,200km) sail from Hobart to Sydney in Australia. With the sail taking almost 2 weeks, I had some (a lot of) time to consider what this humble auto-helm meant in terms of artificial intelligence, defining AI and what makes us have a human-like relationship with some technology.

On the one hand the auto-helm is just some simple mathematics and logic that responds to inputs. On the other hand, out of all the equipment we had on the boat the auto-helm was the only one that got a name, the only one we projected emotion onto and the only one we felt affection towards.

Before we explore the definition of AI some background is needed for those unfamiliar with sailing and auto-helms.

Sailing deals with some environmental inputs: the speed and direction of the wind as well as the speed and direction of the waves. These have a general trend (e.g. the wind is coming from the south and the waves from the south east) and a variable, real-time factor (e.g. based on the boat’s current orientation to the wind and the waves the general effect of the environmental inputs is Y).

Based on where you want to go, you then need to weigh up these environmental inputs and make decisions about where you want the boat to face and the configuration of your sails. For instance, a sail boat that isn’t using its engine cannot go in the direction the wind is coming from. Instead it must point 30-40 degrees either side of the direction the wind is coming from.

With the auto-helms I’ve used the human’s need to make decisions about the sail configuration and where the boat needs to point. You then switch this to the auto-helm and it balances the effect of wind and waves to sail in the direction you have told it to go or at the angle from the wind you have told it to sail at (e.g. 35 degrees away from the wind coming from the north). This balancing has to take place in real-time due to the boat’s movement combined with changes in the waves and wind in relation to the boat.

What amazed me on our journey, as we dealt with the high seas, high winds and some high adrenaline situations, was the effectiveness and reliability of the auto-helm. As the boat bashed its way into high wind and surfed waves, our auto-helm handled the conditions brilliantly for over 40 hours straight. The auto-helms effectiveness and reliability over the years, even in the tough conditions, led to it being given a name – Hoolio – named in honour of an exceptionally good waiter we met on the boat’s first trip around Spain’s island of Mallorca.  

The naming of the auto-helm is my first point of interest. The fact that the auto-helm had a human name got me thinking, is this AI? AI experts would be quick to point out that it lacks general intelligence, that it isn’t strong AI. However, you can’t argue with the distinctly human affection that my fellow sailors and I developed for Hoolio over the course of our journey. We even projected emotions onto Hoolio; when there was too much force on the sails and Hoolio was overpowered we said he was “unhappy.”

Contrast this with our relationship to the boat’s GPS and radar systems. We didn’t name them, we don’t even think of them as remotely human. They are tools, collecting and displaying information. However, on a technical level the Hoolio auto-helm is no different. Hoolio is just some technology that collects data, processes the inputs and outputs something just as the GPS and radar systems do. The GPS and radar output to a screen, Hoolio outputs to the steering wheel. Hoolio’s inputs and outputs are probably simpler than the GPS’s.

So what made the crew and I think of Hoolio as AI but the GPS as a tool?

A consideration here is how seamlessly Hoolio interfaces with us humans. You press left to go left and right to go right, two buttons. Hoolio then takes care of the rest, balancing the environment against the direction you have asked. So to think of it as a computer only occurs to those familiar with the technology behind the scenes.

However, after much debate the conclusion was that Hoolio was making decisions about our future on our behalf based on what we had asked of him where as the GPS was giving us information that we still had to process and act upon. It’s this ability to make decisions about our future based on a simple request – “sail in this direction” – that makes us think of Hoolio as a human.

Reflecting further on this leads to the observation that we don’t need to get too caught up on hard definitions of “artificial intelligence.” In casual conversation about Hoolio we never used the words “computer”, “artificial” or “intelligence”. Most people don’t talk like this when interacting with AI.

It is tempting to take the conclusion we reached about Hoolio being human because he made decisions about our future and extrapolate this out to being what defines an artificial intelligence but humans and their relationships are notoriously more soft and fluid than that, so our definition about what an artificial intelligence is and is not will need to be soft and fluid as well.