What’s our AI Strategy?

This question is being asked in every boardroom of every enterprise right now. Strategy is about uncovering previously unrecognized insights amidst a sea of qualitative experiences and quantitative data.

It’s about looking at challenges holistically and asking ‘Why?’ a lot. It’s about leveraging an organization’s strengths while mitigating its weaknesses.

However, AI is a powerful tool that is available to everyone. Its existence does not automatically dictate a strategy. AI is not a solution searching for a problem; it’s a tool. Before using this tool, we should understand how to employ it effectively. This approach seems to be the most strategic choice.

To conceive new and novel applications, we must understand the intrinsic qualities of AI. The crucial question is: Where does AI deliver value in our specific context, so that its application is in fact, strategic? In order to answer this we need to better understand what it is that we’re talking about when reference AI.

Note: I will use “AI” as the shorthand, encompassing term that includes all forms of AI, generative as well as predictive algorithms, and LLMs to computer vision and all the modalities in between.

More than a better horse.

I’ve been referencing Henry Ford a lot lately. Prior to the invention of the automobile, 100 miles was a vast distance, that took a lot of time to traverse. The car accelerated the collapse of time and space that the steam engine started. This has had profound effects not just on where and how we live, but the process by which the automobile was made transformed how we worked, ushering in an entire paradigm shift in manufacturing. Prior to this invention, we couldn’t conceive of a future where we lived more than a mile or two from where we worked. I submit that the invention of the automobile represented an event horizon beyond which we could not see… until we started using them.

Currently, many are mentally grafting AI onto our legacy paradigms and systems, viewing it as a new appliance to plug into the stack, promising greater productivity. This vision is flawed. AI is not merely additive; it is transformative.

Yes, AI will allow us to do more. However, using this technology for the same old tasks is as much an underutilization as claiming a car is merely a faster horse is an understatement. The car and the internet collapsed time and space, creating paradigm shifts that we are still reconciling (hello remote work!), and I expect this technology’s full impacts won’t be understood comprehensively or fully leveraged and exploited for years to come.

But to bring these transformative changes to life, we, human beings, not the technology itself, need to fundamentally shift our understanding and broaden our horizons regarding what is possible. We must evolve our mindset, break away from traditional limitations, and acknowledge the vast potential that these technological advancements can offer, even though we don’t fully understand them yet.

The future lies in our ability to envision it, not merely in the capabilities of the technology we wield.

Think like an artist.

I grew up wanting to be an artist. I drew, I painted, I sculpted. I made videos, films, interactive installations. I worked with all kinds of media—from acrylics & oils to woodcuts and resins and more sculptural media than I can remember.

I believe that AI represents a new medium for us to explore and use creatively. But like the artists that came before, we need to explore this medium to understand its intrinsic qualities—what is it good at, what is it not.

When you study art (the practice, not the theory), one of the things you come to understand is the intrinsic qualities of the different media you work with. The way you can’t always control the pigment when painting silk, or the reality of how long it takes yellow oil paint to dry (weeks!), to the inherent challenges of powering large reactive LED installations. You come to understand the different qualities of graphite in your pencils, the right-sized marker tip to use for your desired goal. Every medium has its own qualities and attributes.

The value of this effort is that you internalize an intrinsic understanding of each medium. You build mental models that allow you to develop a type of foresight that helps you move from the idea in your head to something real and tangible in the world. Only after understanding your various media, you can move faster, masterfully, to realize the vision in your mind and bring it into reality.

So, how does one “explore” AI?

Play like a child.

Approach AI, this new and foreign medium, with the mindset of a child encountering a new object for the first time. One of the most outstanding characteristics of children is their creativity. This is fundamentally rooted in curiosity – a relentless desire to understand, to ask questions, and to explore with all their senses until comprehension is achieved.

Curiosity manifests as play. We understand that play is crucial for a child’s cognitive development because it fosters the foundations of intelligence—the ability to explore one’s environment, understand limits, and navigate social dynamics. Children learn through play, constantly evolving their mental models around what is possible. They are not deterred by failure, often not even perceiving it as negative— their primary motivation is curiosity.

Not sure if making AI a co-pilot is a worthwhile endeavour? Do it anyway. You can’t learn something by ignoring it. And the potential of this new medium is still very much in its infancy. Have a tedious pile of data you need to find some insights within? Leverage one of the MANY (and growing) services of AI-powered tools. Need ideas on what to buy your spouse? Ask AI. Not sure where to start in planning for retirement? Ask AI. Not sure what to make for dinner with the 5 ingredients you have in the fridge? Ask AI! And give the AI context for what you are trying to accomplish. In the case of the recipe ideas… tell it what foods you like. Ask it to operate interactively and have the AI ask YOU questions in order to get to more interesting outputs.

The point in all of this is to play. There are thousands of scenarios where AI may or may not have an application that produces value. But knowing where and when to leverage it will be the agency of every human on the planet with a smartphone and an internet connection. Over time, your own intelligence will start to develop mental models around what leads to good and valuable applications.

Evaluate like a Scientist.

The Scientific Method says you start with a hypothesis, experiment, measure, evaluate and adapt. I think the process itself is likely a bit rigid to follow in the spirit of playing like a child, but do take the time to interrogate the outcomes that you achieve from your playful experiments.

GenAI is known to hallucinate (one might argue that it’s a feature, not a bug), earlier versions of ChatGPT (i.e the version from 6 months ago) was awful at math (it’s not a reasoning or logical engine but a predictive word engine), and the cocktail recipe I had it come up with on New Year’s Eve was terrible. But in the spirit of both the Scientific Method and child playfulness…how many times and ways did you try to get a better outcome? Did you enter a simple command or request with no context? How many roles did you ask AI to assume? Did you use a single call-and-response mode or use it in an interactive and conversational experience? Only through this iterative process of experimentation can we truly uncover the potential of AI and harness its power effectively.

Just Start.

As we witness the relatively mundane applications of AI in the enterprise context, it is time for businesses to embrace a spirit of creative experimentation as a strategic imperative.

If the point of strategy is to uncover new opportunities and ways of working, and we face tools with untapped potential, it makes sense to leverage our unique human abilities to understand and envision the future. Don’t try to answer the question “What’s our AI strategy?” but rather answer with a better question; “What problem do we want AI to solve for us?”

And if you’re struggling to answer that, maybe you consider reaching out to a firm that understands technology at the intersection of business and experiences. Cause at the end of the day, that’s all we want technology to do for us—provide a better experience.

Spencer Saunders

President & CEO