The Three Essential Pillars for AI to Be Practical, Applicable and Strategic
“The limits of my language mean the limits of my world.” - Ludwig Wittgenstein
This is a fascinating quote that I first heard that quote 25 years ago on a random train ride talking with a stranger.
I honestly didn’t understand it. But I never forgot it.
As I’ve since researched the philosopher and his views I see it’s application in all sorts of ways.
This quote gets to the heart of how language shapes our understanding and experience of reality.
...that language isn't just a tool we use to describe our world - it actually defines and limits what we can comprehend and experience.
But here's the thing - this idea is highly relevant for AI.
Right now we're entering into a new reality but without the language to fully understand and navigate it. But with understanding language of artificial intelligence, we can begin communicate, influence and work with this emerging reality.
Before we get into the strategic pillars of AI, I want to quickly address the technical.
For AI to be functional and powerful, it needs three things:
Compute ✓
Data ✓
Algorithm ✓
The compute relates to the computer hardware, processors, and energy requirements. These physical components are the fuel that enables the training and building of AI.
The data is the base of knowledge necessary for training today’s Large language models. The strategy seems to be the data the better. So every piece of data that can be scraped from the internet is how AI is built.
Finally there’s the algorithm. The intelligence or brain or way of sifting and referencing all the data. Its the “GPT” as aspect of ChatGPT. The invented strategy from the 2017 Google paper, Attention is all you need.
Now for most of us, we don’t have any influence on how AI is created. We’re not engineers or data scientists. For us, the practical pillars of AI is more strategic.
Three Pillars of AI for Practical and Strategic Benefit
Now we need to return to the Ludwig quote.
The foundational pillar we need to for success is literacy. Language. We need to understand the basic terms of AI.
Pillar 1: AI Literacy
Without a healthy literacy, we’ll get confused following media pundits and even the disjointed descriptions from Open AI, Anthropic, Google, and Meta.
They ^ do NOT always use the same language.
I believe we need to know the basics of what AI is.
What it does (today).
Where it’s going (soon).
Our vocab needs to expand. Our perspective needs the peripheral vision of the accelerating and fast approaching horizon.
But Literacy is just mental. To embody our understanding we must go from head to hands.
Pillar 2: Competency from Experience
Ethan Mollick often says to understand AI today, we need to spend at least 10 hours using a large language model.
Only from the hands on use… applied to whatever is important to you will true potential and understanding happen.
When I teach AI competency principles in my speeches, courses, and workshops, I encourage a layered approach to gaining competency.
Learn the basics of prompt engineering
Find personal projects with models and niche apps
Organize team pilot initiatives with responsible AI policies and guardrails.
These elements of experience build upon the foundation without judgement, right or wrong. When you get to organizing team projects and pilots it also forces your company to develop policies and frameworks to make sure data is protected and human checkpoints are in place.
Before you invest larger amount of money and time, you want to have a health structure from leadership, legal, and every employee.
Pillar 3: Focus on Constraints
The final pillar of practical AI benefit is the focus on constraints, not strengths. This pillar and decision comes from the work of Eli Goldratt and the Theory of Constraints.
In short, if you apply AI to a strength or strong area in your business/life you will still by a limiting factor. Thus, the AI’s will only create a larger inventory of XXX … whatever the AI creates, but if you don’t fix the bottleneck the entire business will not be any better.
Imagine if you used AI to create masses of content or video, but you didn’t have enough money to fund Facebook/Tiktok/YouTube, all those videos would never get the view necessary to increase your sales.
Or what if you had the money and you created the content, leads came in, but your sales staff as the limiting factor and you ended up burning out your sales team or frustrating your leads by not responding to them in a timely fashion… and this even began to spread via word of mouth that your company was non-responsive.
Instead of focusing on strengths, I recommend you find the weakness. The limitation. The constraint of your business.
Once you elevate the constraint with AI, then you can next find the next weakest piece of the puzzle.
Conclusion
Each of these pillar build upon one another.
As you gain literacy, language, and understanding of AI… what it is, does, and going, you’ll be able to see opportunities personally and professionally.
For a list of marketing use cases, use my book as a reference to get started.
For a workshop for your company, please reach out for scheduling and prices.
Create a Great Day!