The Artificial Intelligence Revolution in Project Management
When AI became the shiny new thing, the buzz word and theme of nearly every piece of communication through every channel imaginable, I’ll admit to being a little annoyed— after all, this is not a new topic, and what we have isn’t a generalized intelligence. Marketers love a theme, though- and this one has it all: new, scary, transformative. Except, it’s so ‘not new’ that when I moved to Cambridge, MA in 2000 to begin a career in scholarly publishing I had considered pursuing research in the field as an alternative path.
I was living in the Blue Mountains of Washington State and wanted something new; adventure, career, travel… I was restless. As I tend to apply process to questions I cannot immediately answer, I went to the white board and began a formal decision-making process to identify how I wanted to focus my ‘next steps’. Before long, I had a narrow list of pursuits which included dimensions from business, technology, epistemology, and creative disciplines (writing and art). It was my personal SWOT analysis that tipped the scales towards scholarly communications as ‘where I wanted to go’. While AI was super interesting, and there was some real progress coming out of the MIT labs, I concluded that there was “no there, there”, so to speak, in the immediate future…and that proved correct for two decades.
The turn of the century was a time full of possibility and innovation. It was the height of the “dot com” era, and the beginning of the migration from print to digital. Until recent break throughs, artificial intelligence had been mostly limited to algorithms that approximated a ‘Choose Your Own Adventure’ book capable of delivering canned responses to sophisticated If/Then statements (I am oversimplifying)- most nerds, including myself, were more interested in how to make better bots and NPCs in video games… at that time, having a competent digital assistant, much less a decent artificial copy writer, wasn’t on the radar in terms of realistic expectations. Spell-check was still fairly new. Extending such a capability to superhuman levels was little more than an interesting topic among friends and pub philosophers. Ray Kurzweil was making noises, but was more entertaining than taken seriously.
The topic of ‘what’s possible’ was never far from the horizon, however – NLP (natural language processing), the ‘semantic web’, search and extract/transform/load (ETL) concepts were emerging buzz words of their own circa 2005ish. These had practical impacts on how content was created, described, and used. Systems could be built, taxonomies developed, and content tamed by interweaving elements we, as humans, could identify, measure, and repurpose. We were all about well-structured metadata to enable access, distribution, and improve the ability of researchers to conduct, link, and share their work. Meanwhile, data and network architecture continued to improve, and Moore’s Law marched on.
Many academics and companies used such concepts to transform the world of information. Positive feedback loops were created, research benefited, and real progress was made in enabling humans to discover, create, and share our collective efforts to better understand and navigate a complex world. It has been wonderful to watch and be a part of – and now, everything is going to change again.
Breakthroughs in machine learning are the new ARPANET, data lakes are TCP/IP, and Large Language Models (LLMs) are HTTP. A new era is upon us, and it will have a bigger impact than the last technical revolution by virtue of accessibility and results. Anyone can use it, and it works. We’ve seen nothing yet. To continue my analogy, these are the AOL days of AI; and just like then, everyone with half an idea is trying to get a seat on the boat they believe will rise with the tide. They aren’t wrong, but it isn’t going to be easy; and like the Dot Com era, bubbles will form, and burst. Just as during that time, the most important progress is being made behind the closed doors of proprietary R&D institutions, and, it’s used to sell things. Not just physical items, but ideas and concepts too. People interact with and are influenced by so-called AI in so many ways, and that will continue to a point that frightens many. However, you are not doomed to be a leaf in the wind.
I recently heard an expression, “AI won’t take your job, those who use it will.” This same statement could be made about every new technology paradigm that has occurred. In this case, think nail guns and hammers; we still use the latter, but if you want to be efficient and produce a superior product, go with the nail gun. I’m going to gloss over the “use AI” bit, because there’s too much to cover there for this post; just know, there’s a lot more out there than just ChatGPT. The mathematical magic that makes AI special isn’t important for the user; I’m certain many readers have driven hundreds of thousands of miles and yet have nothing more than a rough idea how the engine in their car works, much less an airliner’s turbine. Focus on what you can do with it.
While experimenting with various platforms and tools, including ChatGTP (this is a human produced piece, by the way) I have recently been inspired to go a little deeper. Project Management is a discipline close to my heart, and there is rapid adoption of Generative AI tools within trusted frameworks to produce better projects with less work. This has been on my mind as I have encountered clients who, while organized, do not employ formal PM systems. That’s okay in some circumstances, but not for anything with real complexity. I define ‘complex’ as any single project that relies on more than two contributors, has contractually required deliverable, more than a handful of stakeholders, any outside contracted resources, or interdependent milestones. So, yes… I’m biased, one could argue that an oil change requires project management; Jiffy Lube actually has a fantastic system designed to increase efficiency and mitigate risk, but I digress.
Some of the things I would encourage business leaders to familiarize themselves with include how Gen AI is being implemented within the existing tools and trusted frameworks we use to manage complex project and mitigate risk to our stakeholders. It doesn’t really matter if you’re building software, houses, or a production process; these are universal project management concepts.
PMI is currently offering a free course creatively entitled: Generative AI Overview for Project Managers. Yes, they will try to sell you services; I have no affiliation. It’s worth taking a disciplined approach to staying current with trends and you’ll likely not only learn something but find a little inspiration along the way. If you are already a PM, or working towards a PMP certification, it offers 5 PDUs and won’t cost you a dime.
Topics covered include AI’s impact on:
· Efficiencies and time management
· Collaboration
· Using predictive insights to support decision-making
· Task automation,
· Project management concepts like scope, risk, and stakeholder management
Check it out, here’s a link: Generative AI Overview for Project Management
“AI is not a future, nice-to-have technology. It is used in organizations today as an essential tool to improve project performance.”
Paul Boudreau, Professor, Speaker, Author of The Self-Driving Project: Using Artificial Intelligence to Deliver Project Success
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