In 1960, the founder and eventual CEO of Intel, Gordon Moore, made a hypothesis about the pace with
which computing would accelerate in the coming decades. ‘Moore’s Law’ as it came to be known, stated
that on their current trajectory, the number of transistors on a circuit would double every two years
while the cost to attain those improvements remained relatively stable.
The concept soon became a rallying cry for futurists, tech nerds, and engineers alike – many of whom
believed that the combination of growing capability and shrinking cost would add up to a Utopian
society replete with flying cars and sentient robot housekeepers. What they didn’t account for was how
long it often takes for new technologies to make their way to the market and the rarity with which they
do so in the fantastical ways we first imagine.
That’s because our ability to synthesize new technology into working tools evolves over decades, not
years. When met with real-world challenges, new technology often succumbs to the simple realities of
the free market: Cost, feasibility, demand, user experience, et al. (We’re looking at you, metaverse) The
upshot is that there’s almost always a gaping chasm between what we can and do build.
It’s a relevant allegory for marketers at a time when the media is filled with bold, yet hyperbolic
predictions about the inevitability of AI. To believe the headlines, one would think that these
technologies will replace marketers in a matter of years. When combined with a changing of the
generational guard, that angst has created a breeding ground for our worst fears to thrive.
For those of us who’ve spent a lot of time around new technology, it’s also a somewhat amusing
proposition and seems to ignore the almost universal struggles marketers often still have just trying to
get varying aspects of their technology stack to co-exist.
“Yesterday people said chat was going to take everyone’s jobs. Today, they’re complaining
about how slow it is.”
Sam Alman, CEO of OpenAI
These doubts may seem like the ramblings of a technology cynic scorned. On the contrary, I am a chronic
early adopter – often to a fault. Not only do I love the possibilities that new technologies bring, as the
senior marketing strategist at a national communications agency, I also consider it my job to have a
strong grasp on how these tools can hurt or help us and our clients.
One thing we can agree on, no matter what, is that the marketing ecosystem has gotten orders of
magnitude more complex over the last decade. Virtually every organization has been forced into
becoming a media company unto themselves and even the smallest brands now require an integrated
team of strategists, creatives, and technicians working in lockstep to deliver messaging at scale.
While executives are, somewhat understandably, looking to AI as a potential solution to this challenge,
the use case strikes me as inefficient at best – akin to using the heel of your shoe as a hammer. Not only
would leaders be jumping out of the labor frying pan into the fire with multiple new layers of engineers,
et al, they would likely double their costs overnight for much lower quality and less reliable results.
AI technology will almost certainly improve and expand in the coming years. These challenges beg an
honest appraisal of the current conversation, though. While we have built what, by all accounts, appears
to be an impressive new technology, are we moving forward with intent or just throwing digital
spaghetti at the wall to see what sticks?
Like the flying cars and sentient robots of yesteryear, the most common use cases I’ve seen for
generative AI are fun, bold, and thought-provoking. They’re also unproven and very costly and just plain
inefficient.
There is, of course, a chance that I’m wrong; that these new tools will tear across our economy like
wildfire ravaging the creative and communications system in the process. If we base our estimates on
the progression of other similarly positioned bleeding-edge technologies, however, the true benefits of
AI will creep in at the edges, changing the way we work in an act of evolution rather than revolution.
In fact, when we step back from the edge, we end up with a far more pragmatic set of questions. Will AI
survive a series of impending intellectual property lawsuits? If it does, what capabilities should
marketers prepare for and/or expect in the near term? What are the positive use cases for the
technology? And, will we ever be able to trust the results it delivers?
When we boil tools like ChatGPT Gemini, Claude, and others down to their most basic capabilities, they
represent a new and far more dynamic way for us to explore, find patterns in, and ask questions of our
data. In its best incarnation, the technology would serve as a strategic, creative, and technological
exoskeleton that allows marketers to iterate more quickly, reducing waste and empowering us to spend
less time buried in data and more getting to know and talking to our audience.
This guest blog post was provided by Rion Haber, who is the co-founder and Chief Strategy Officer at Catalyst Marketing Agency – an award-winning communication team based in Seattle, Washington and serving clients nationally. Over the past two decades Rion has become a recognized advocate for integrated marketing strategies as well as the originator of an embedded solution meant to help downscale them for growing organizations. If you are interested in learning more how Rion and his team can help your company, contact them here – Contact Us | Catalyst Marketing Agency
