Despite being years deep into the new Age of AI, there is still surprisingly little clarity around how to systematically approach and model the space in order to find opportunities for investing and building new businesses.
My intention here is to create a simple top-down process for identifying opportunities by analyzing the core components that are critical in any viable AI-driven product or business.
As an entrepreneur, these are the questions I ask myself when deciding which areas look most fertile to pursue. As a VC, you might use this to find green fields for investment or as a tool to evaluate businesses that cross your radar. As a researcher, this may provide new areas to explore and as an industry expert this should help you think about triangulating in on a good opportunity within your domain space.
The conversation about Artificial Intelligence has become so muddy lately that it is important to be very clear about what we mean when we say an organization is "using AI" or is "AI driven". This post will clear up those definitions and some of the implications of each classification.
There are three levels at which an organization can adopt artificial intelligence:
- AI-Assisted: AI is a technical bolt-on to existing processes, usually through the use of AI-created tools, for example AI assisted sales or team management tools.
- AI-Enabled / AI-Augmented: AI is applied to existing processes or product data to make the product or service better or more useful, for example the recommendation engines behind Netflix, Spotify, Amazon, etc. This is often in the form of one or more AI-driven features or products.
- AI-Driven: AI is literally the lifesblood of the company or initiative, for example self-driving technologies and the companies providing tools to AI-Assisted companies. This is truly an AI-Driven company.
Each of these cases has different implications from the perspective of the implementing organization.
Much of the hype around Artificial Intelligence centers on some vague sense that it continuously learns from the world around it so it gets ever-better at performing tasks. In reality, it's important to understand that the core truth underlying this is much simpler and more powerful: AI technologies allow us to make better predictions than we could before.
Despite the simplicity of that fact, it is an enormously powerful building block which enables automation on a scale we've never seen before by disrupting task loops across the information and physical worlds. Understanding it will allow you to better appreciate the kinds of change it can and will drive.
The semiconductor represents a useful analogy for this reduction. Semiconductor technology obviously changed the world but these empires were built on top of a single simple truth: it reduced the cost of arithmetic. That most fundamental use case forms the basis of computing and, at sufficient scale, allows us to do everything we can today.
The Virtuous Cycle of AI Products, also called the "AI Flywheel Effect," is one of the most exciting ideas in Artificial Intelligence and it's also incredibly simple. Essentially, when AI technologies are integrated with a product properly, they create a feedback loop where the product continuously improves with use, generating more usage and a better competitive position relative to other products.
It looks like this:
- Product gets used, generating data
- Data from usage is fed into machine learning (or similar) models
- Models improve the product, generating more usage
Any product tends to improve with usage regardless of its underlying technology because a good team will use qualitative feedback and analytics data to bring it closer in line with user needs. This improvement, though, tends to reach an asymptote where additional usage and data no longer provide much marginal insight to the product.
Burnout sucks. I'm not talking about that "I can't wait for the weekend" feeling or even the glazed-eye look you gave your parents when returning home from finals week during college. When I refer to burnout, I mean the structural depletion of energy which makes it nearly impossible to raise your head and get real work done. It's a poison that seeps into and sucks the life out of every working minute.
In startup culture, we glorify working ourselves to death in a way which is completely absurd and totally self-imposed. Along my own 5 year rollercoaster building Viking Education, I became intimately familiar with the feeling of burnout. I distinctly remember the numb progression through checklists of tasks that had become divorced of any meaning and putting on a smiling facade which overlaid an inner me who had long since stopped bothering to panic at his lack of excitement for work.
I'm always amazed that people seem shocked when something they've trusted is usurped for commercial gain. Somehow, in a world that's incredibly dynamic and built on Darwinian evolutions at all levels from single cell organisms up to commercial entities, we still hold onto this naive view that our trust in systems is somehow static.
This is probably because we build our relationship with trust based on our relationships with close friends and family. In most (healthy) cases, this one-to-one trust grows slowly or remains constant over time. A fairly static model for trust is reasonable in this microscopic system.
Unfortunately, we tend to implicitly model the trust we place in third parties and macroscopic communities along similar lines and that simply doesn't reflect reality.
"Inch towards daylight" is one of my favorite mantras from a book I read recently. It also accurately describes how to develop the oft-discussed but seldom mastered skill of Grit.
Grit is generally defined as perseverance in the face of obstacles and/or lack of positive reinforcement. It's the ability to do hard things regardless of whether the environment is supportive, and it's the ability to maintain determination and motivation for long term goals through all the shit work between now and then.
Grit is often and inaccurately presented as an innate characteristic. That gives those who lack it far too convenient an excuse to stop trying or to justify their deficits. In reality, Grit is a muscle that needs to be trained.
In 2017, I ran an Ironman triathlon and sold a challenging service business that I'd bootstrapped through 4 arduous years. I live with a group of highly motivated high achievers who span the world of entrepreneurial and life success -- the collection of their acquisitions, press articles, TED talks and general awesomeness gives me constant awe -- yet they constantly express amazement at the kind of will I'm able to deploy to the fulfillment of a particular goal. Why?
I'm a huge fan of any models that find applicability beyond their intended domains and there are few quite as versatile and useful as The Hedgehog Model.
In his seminal book "Good to Great", Jim Collins examines 1,435 businesses over a period of 40 years in order to answer the question "what separates the good companies from those which make the leap and become great companies?" Over the course of his analysis, he uncovers a variety of factors that drive this distinction but one of the most fundamental concepts he explains is "the Hedgehog".
This idea is based on a fragment attributed to the ancient Greek poet Archilochus which says "a fox knows many things, but a hedgehog one important thing." Both these animals have survived successfully by deploying greatly different strategies. The fox is clever -- she knows a great many things and tends to rely on her intelligence to hunt and survive. The hedgehog is a far simpler creature -- when she is threatened, the hedgehog simply curls up into a ball and points her spines outwards.
At 7:41:10pm On July 29th, 2017 I slowed to a halt, put up my hands and wept. I could barely breathe after the deceleration but didn't care because I'd stepped into the moment I'd visualized 10,000 times and it was every bit as sweet as I'd hoped.
This was a moment to culminate the most difficult challenge I've ever undertaken in the course of my life -- and ever hope to. The Ironman triathlon, commonly known as the most challenging single day sporting event in the world, is something so stupidly crazy that it prompts concerned looks and a whole lot of "why?". No one questions any more if you decide to train for a marathon but this mother of all triathlons is that and more -- a 2.4 mile swim followed by a 112 mile bicycle ride followed by a full 26.2 mile marathon.
This 140.6 mile course is the most challenging thing I could possibly imagine a human being voluntarily doing and that's frankly much of its appeal.