OLD-BUT-GOLD | BOLD Predictions: The Rise of AI-Driven Projects…in the 2020s

OLD BUT GOLD... this article is written by Oliver Yarbrough for pmmagazine.net in December 2019

Picture this…

Always on, sophisticated AI bots working in the background processing data and delivering curated insights to you when AND how you want them.  Think Amazon Alexa or Google Assistant, but for project management.

This will better enable you to spot trends and make informed decisions.  Your AI bot can then check relevant stakeholders’ availability for a meeting and reserve a time that works best for everyone.  As you refine the system over time, so you can get even better results.

Sound bold, audacious, or maybe even a bit farfetched?  

Well, trust me, it isn’t.  

PwC says 85% of global CEOs predict AI will significantly change the way they do business in the next five years.  And according to a recent PMI Pulse of the Profession® In-Depth Report –

• 81% of respondents report their organization is being impacted by AI technologies
• Over the next 3 years, project professionals expect the portion of projects they manage using AI to jump from 23 to 37%
• 37% of respondents say adopting these AI technologies is a high priority for their organization

Let that sink in for a moment.

If you didn't think AI would continue to tighten its grip on the project management profession…well, now you do.

Get ready for major disruptive trends that will lead us towards AI-driven projects in the 2020s.  As you prepare, here are 2 BOLD predictions you should keep in mind.

BOLD Prediction #1: AI Becomes Ubiquitous in Project Management Software  

Is it just me or does it seem like AI is starting to pop up almost everywhere?  

I bet you asked your voice assistant (e.g. Siri or Alexa) a question today or got investing advice from a robo-advisor this week.  And you probably didn’t give it much thought.  

You know why?  

AI is built into the devices and apps you’re already comfortable using.

Well, organizations want this same ease of functionality for their workforce.  In fact, according to a Gartner study, almost 60% of organizations have already deployed AI in some capacity.

They are integrating AI assistants into software and apps project teams are familiar with such as Slack and Salesforce.  Some of the ways they’re using them to improve projects include –

• Collecting, tracking, and reporting data
• Enabling voice queries and commands
• Reducing human errors that lead to issues

Today, the most widespread use of AI in project management software is via chatbots.  They can save you time and provide quick support on everything from menial tasks to higher-level predictive analytics.

According to another Gartner study, 70% of white-collar workers will interact with conversational platforms on a daily basis by 2022.  This trend is expected to grow because younger generations crave immediacy and access to the most up-to-date information.  

AI in Action:

Imagine for a minute being able to spend less time on administrative tasks (e.g. writing reports) and more time on mission-critical work. Well, you don’t have to imagine anymore.  Narrative Science, a leader in natural language generation (NLG) for the enterprise, does just that.

Their AI-powered software integrates with popular platforms such as Salesforce and Tableau to uncover the story that’s locked inside of the data.  They do this by translating structured data into stories and numbers that the average person can understand.

It can be used to draft long form content.  Examples include management reports, as well as web and mobile content. This content can then be communicated interactively via chatbots or through text-to-speech programs.    

How to Prepare:

Keeping projects on track involves a lot of moving parts.  Luckily, there are AI-powered solutions that can help.  

You should be regularly exploring ways to integrate these solutions into your projects and daily work routine.  This will make your life easier and increase you and your team’s productivity.

Look for solutions that enable you to visually monitor your project’s progress and notify you if your project starts to slip.  Also, make sure the solutions allow you to collaborate easier, optimize resource productivity, and streamline workflows by automating repetitive tasks.

Lastly, you’ll want to be able to generate real-time status reports.  This way, you’ll be able to better gauge your project’s performance and make strategic decisions based on the latest, most accurate insights.

BOLD Prediction #2: Data-Driven Recommendations Lead to AI-Driven Decisions

Projects produce data.  Terabytes of it.  

And this data leaves behind clues.  Clues that can be stitched together to uncover repeatable patterns.  

Until recently, organizations couldn’t easily parse this data and turn it into actionable insights.  Today, primarily due to AI and machine learning, they can better identify these repeatable patterns at scale and leverage them to make faster, more accurate decisions.  

Did you catch the part where I said it can be done at scale?  Meaning, it can be automated at high volumes.

This creates a virtuous cycle of sorts.   

As more data gets captured, insights are gleaned, decisions are made, and lessons learned are documented.  Once archived, these lessons learned can be used as inputs into future projects.  This creates a continuous feedback loop that improves project results over time.

Today, there are AI-powered software/apps that can easily capture data, glean insights, and even document lessons learned.  The one thing this technology hasn’t been allowed to do yet is make autonomous decisions (at least not at scale).  

But ask yourself –

“What would happen if AI-powered bots were allowed to make decisions on their own?”

It’s not unreasonable to think that with continuous feedback loops running, an AI bot could identify repeatable patterns better than humans.  Say for example, a bot noticed that a resource is performing tasks at 60% of its target and showing traits similar to a previously failed project.  It could automatically flag that resource, and the tasks assigned to it, for review.  Next, the bot could notify key stakeholders and request alternative (or additional) resources, so the tasks are brought back in line with the original plan.

Harvard Business Review found that the majority of management decisions could eventually be made by artificial intelligence, especially those based on data analyses.  We’re already seeing evidence of this in our personal lives in everyday things such as self-driving cars and smart thermostats.

But don’t worry.  For the time being, human managers will still need to set the decision-making criteria and present the final findings to upper management.  

AI in Action:

A few years ago, Cisco Spark partnered with Redbooth, an all-in-one project management and collaboration platform, to extend Cisco Spark’s messaging experience, along with enhancing team collaboration and productivity.  They accomplished this through bot integration.

These bots can continuously monitor an entire team’s performance or drill down to an individual team member’s performance.  If the performance is less than expected, the appropriate parties can be notified.  Also, the bots can answer team members’ questions using natural language.  This promotes transparency and improves project communication.

How to Prepare:

For the foreseeable future, there are some areas where humans will maintain an advantage over AI. They include skills such as leadership, creativity, emotional intelligence, influencing, and public speaking.  

And even with all of AI’s strengths, there are still gaps in the data.  By marrying human intuition with AI’s predictive analysis, managers can add value by helping to close those gaps.  

Conclusion:

Change is inevitable.  It’s safe to say that project management as we know it will look quite a bit different by the end of this decade than it does today.    

But here’s the good news – there will be jobs for professionals who are able to combine their strengths with AI to deliver project results.  It’s just that we don’t know what these jobs will look like.  What we do know is that the trend towards AI-driven projects will continue, so we have to plan accordingly.

Original Author:  Oliver Yarbrough