Here on my third draft of sequencing these paragraphs, I became frustrated as I searched for the proper opening. However, what I was searching for was already here. Via my primary source, a paper published by the Brightline Initiative (BI) and quoting the Project Management Institute;
“Organizations that fail to develop a competency that allows quick response to significant change will not survive.”
Here, in a simple sentence, the future of business, consulting, and perhaps, Project Management writ large is on notice. It will no longer suffice to simply keep moving forward; staying ahead of your competitors is vital to continue working in the industry.
A non-technical and straightforward test of quick response to change has been COVID. Not to belabor the subject, but the world has seen significant changes in the consumer services and business industries. Those who were willing or capable of change have come out ahead. Ventures that were already primed to deal with home shoppers (Instacart, Amazon, etc.) need only make minor edits to their models to fit the issue. 💰
Looking into the future of project management is no easy task. First, my time machine is broken, so I’m relying on current studies and my wits. To that end, the future of the world in which we operate is expected to change. And depending on your view, it’ll be for better or worse.
I’ve not hidden my concerns about artificial intelligence, “taking over the world.” Yes, it’s an exaggeration stemming from my lack of understanding of the algorithms and perhaps too many books and movies. That noted, it is the enablement of AI at the project management level that will forever change our industry. Much like the blockchain future, which will undoubtedly be part of an AI system, the next-generation project manager will have to be much savvier with the technology and have an in-depth understanding of its capability.
Today, AI is already in play within some niche markets. While we’re not to the point that we need to worry about HAL 9000 or Rehoboam, current, very real, systems are executing “increasingly non-routine and complex processes that have traditionally required the unique pattern recognition capabilities associated with human cognition.” (BI)
HAL 9000 (right); Rehoboam (right)
Case in point, Quill. Quill’s a platform that collects and analyzes natural language, mixes the company’s tone with its data, and is then capable of writing a corporate financial report or a project status update, “without any human editing. It can do the same with workflow reporting or business intelligence, just about anything that involves data, analysis, and reporting.” It’s less impressive if you’re not thinking of the long game. As the CFO or CEO of Company X, I no longer need to attend meetings with the project team of today. I need only to log in to my Quill supported system, click an option or two, and the report I need for my meeting is there. [You can play with a version of Quill here.]
I emphasized the word “today” above, as a reminder that today’s project team isn’t prepared for such a system. Without advancements in our team’s training and understanding of the systems coming online right now, the talent pool for next-generation project managers is going to be limited.
Another well-detailed example is what Deloitte’s Center for Government Insights is actively working on. Deloitte estimates that assigning administrative and data management tasks to today’s AI systems could free up 96.7 million hours and over $3 billion annually in the U.S. Given a more significant investment, it’s thought that companies could save as many as 1.2 billion working hours, and $41 billion. Money like that makes things move.
The complications of implementing such a system shouldn’t be underestimated. If you haven’t watched Netflix’s The Social Dilemma yet, I highly recommend it. Within, a former Google engineer provides a dire reminder of what we’re (you) are up against when it comes to corporate machine learning (AI). I’m paraphrasing here, but there are literally only a handful of people within Google who understand how the AI algorithms work across a vast expanse of Google’s digital footprint. However, the system is always learning; thus, once the system is turned on, it outpaces its creators.
This isn’t a scare tactic from yours truly; it’s a reminder that moving forward will require a new mindset, tactics, and drive unseen at the tactical level of being a project manager.
I don’t see the Project Manager or members of the team going away anytime soon. But to mitigate the example of the CEO getting their project status reports without your assistance- it’s time to embrace the future.
Where to now
The next hurdle we need to jump with be educational timing. That is, how soon and at what level do we need to educate ourselves (yes, me too)? I wish I had that answer. The reality is that it will be industry-specific and follow the pace of the new system’s financial feeding. While it may nearly guarantee a time (and money) savings, a transition to new PM technology will not be cheap to implement.
So, for now, I’ll be keeping tabs on the future of our craft, much like I already do. Tomorrow was here yesterday, now’s the time to catch up.
Or this could all be for naught; if Christian Mendieta is right, “agile killed the machine,” and it won’t be back for a while.
To end this, and if you’re interested, you might want to check out Michael Quinn’s Ethics for the Information Age. Within, you’ll find an exciting discussion on the bias of machine learning.