4 Reasons You Need to Right-Size
Your AI
Sometimes
it’s smart to be careful—and slow—when you’re dealing with new technologies.
EXPERT OPINION BY HOWARD TULLMAN, GENERAL MANAGING PARTNER, G2T3V
AND CHICAGO HIGH TECH INVESTORS @HOWARDTULLMAN1
Aug 26,
2025
This is a very complex
and challenging time for startups and small businesses in terms of how they
should be addressing all of the issues and concerns around artificial
intelligence and, more specifically, how they can incorporate the new AI tools
and technologies into their own businesses. I realize that every startup in the
world already professes to have built AI into their current offerings as well
as into their future plans but, at best, many of these claims are nothing more
than adaptations of machine learning or pattern recognition with a new shiny
coat of paint and some text prediction capability. Sometimes it’s smart to be
careful and slow when you’re dealing with new technologies. The last thing
you want to do is be the latest victim of the fake-it-‘til-you-make-it disease.
It’s not remotely clear
that a surface-level solution built on top of a generic large language model
system will be of much value or benefit to many midsize businesses with very
specific needs and nuanced market dynamics. One size almost never fits all these
days. The implementation and operating costs alone of many of these systems
would likely exceed any concrete internal improvements that addressed the
user’s real needs. On the other hand, a smaller, more targeted, and clearly
focused system whose objectives and functions the company’s management
understands could be a valuable aid and time-saver if properly
deployed.
A side note that should
be obvious but is often overlooked in top-down implementations of new tech is
that you must secure buy-in from your key management and other pivotal team
members and address in advance their concerns and the typical misunderstandings
they may have about the plans, the short- and long-term job consequences, and
other implications of the new systems and their roles in the process.
We’re all rushing to
employ these things before we fully understand them and, worse yet, it’s easy
to come to depend on these seductive tools even when we know in our hearts that
we’re not fully in control of them. You don’t need to cross the chasm in a
single bound. Hallucinations and biases are only two of the most obvious risks
and concerns when you start looking under the hood of some of these programs
and discover that even their makers have only a passing idea of how they really
work.
The big guys in the
corporate world can now rush to join the line of lemmings willing to pay OpenAI
a consulting fee starting at $10 million to send a team of its eager engineers
into their shops to build them custom solutions based on its GPT-4o technology.
You would think that—given the havoc that the DOGE monkeys and minions brought
about across our entire government—these corporate honchos would take a breath
or two and ask themselves whether turning over the keys to their futures to
Sammie’s smarties is the wisest course or whether it’s roughly akin to giving
expensive whiskey and your car keys to the neighbor’s teenage son and wishing
him well on his journey.
If there’s a single
statement that says it all for me right now, it’s the various versions of the
observation that no one’s going to lose their business to AI, but most will
lose their businesses to competitors who are more effectively using AI to
streamline and accelerate their operations, to reduce their headcount without
sacrificing customer connections and satisfaction, and to give them a far
broader and more accurate overview of their marketplace, their competition, and
timely intelligence and data to react to emerging positive and negative
trends.
The best and quickest of
the players will rapidly realize that the hours and days they previously spent
pouring over voluminous market data, analyzing their often incomplete and
delayed compilations, and attempting to extract actionable information from the
mess will now be replaced and made available in real-time detailed summaries
crafted by young and clever prompt engineers.
The truth is that—with
regard to the introduction of any new and disruptive technology—it will take
every business a significant amount of time to learn how best to deploy it and
how to deal with the displacements, interruptions, and new responsibilities and
job descriptions that will accompany it and inevitably cause
problems.
Walking before you
run—especially if you’re trying to do this development and implementation
basically on your own—is the only rational and cost-effective course. It’s
critical to keep in mind that you can always circle back and build better and
more robust versions of what you’re initially experimenting with. It’s not
likely to be an overnight project or an overnight success, but each iterative
step will teach you a great deal, further empower you, and also help you to
better understand the capabilities of the tools you are using—even as those
abilities continue to grow and expand every day.
What’s most important is
for you to take the time to gather your team and review your operations and
outline the areas where some intelligent automation could speed and simplify
your own processes and actually produce a better result. In the first instance,
none of this needs to be rocket science. Guesty is a legitimately AI-assisted property
management system that was designed specifically for short-term rentals handled
by Airbnb owners and operators.
While this sounds about
as mom-and-pop as can be, these folks face many of the same issues you do in
your businesses—albeit at perhaps a smaller scale. The point is that, if this
kind of simple use-case can show dramatic improvements in their metrics and
their bottom lines, then shame on you if you haven’t figured out how to
replicate these tools and techniques in your own shop.
Here are four simple
examples that a satisfied Airbnb operator told me has increased his yield and
profit, dramatically decreased the time he was spending each week on his side
business, improved his ratings and rankings with Airbnb, and led to repeat business
and referrals from satisfied customers. And to be clear, I think he spends
about $30 a month for the app. Eat your heart out.
1. Hundreds of stored
FAQ responses are delivered automatically in context-sensitive and narrative
serial fashion
You would be surprised
and possibly shocked to learn how many times a day your team members waste
their time repeatedly responding to and answering the same questions over and
over again. Often, they do it slowly or inaccurately and eventually they do it
impatiently—human nature being what it is—and none of this is good for your
business. Automated responses can satisfy a significant number of callers who
have simple, redundant inquiries and, more importantly, can deflect the wrong
callers by simply and quickly making it clear to them that they are looking in
the wrong place.
Pricing is dynamic 24/7
and throughout each week based on a variety of factors and competitive
offerings in the market as well as available capacity
While in theory you
could spend your entire day checking out competitive offerings and prices and
adjusting your offers accordingly (and clearly Amazon does its pricing in this
fashion every minute) and you could also constantly check your bookings through
the week and determine whether price reductions might absorb available and
empty units, rooms, or beds (just as American Airlines does all day long), the
fact is that neither you nor anyone on your team has the time or interest to do
anything like this, but the Guesty system
does it automatically for you according to your guidelines and parameters
instantly every day.
Publish and sync your
listings in real time across more than 50 major listing services including all
the major sites
You may use programmatic
tools (with very little actual accountability) to get your messages out to the
masses, but, in truth, you have little idea of who is seeing them and
absolutely no real time ability to change or update the content or distribution
plan. Intelligent systems using open APIs across multiple platforms give you a
one-stop solution to precisely target and deliver your messages to qualified,
interested viewers in the proper context with the ability to vary and alter any
portion of the listings that you wish at any time.
Responses to every
inquiry are immediately replied to even if the reply is merely a placeholder
and conversation starter
Not surprisingly,
response time is a measurable metric that firms like Airbnb use to evaluate the
owners and operators on their site who use their services. Automated
intelligent systems can respond instantly to every inquiry even if the response
isn’t a substantive answer, but only a request for further info, details, or
specificity to continue the conversation. In addition to managing the Airbnb
metric, this immediate reply improves customer satisfaction and engagement
without consuming any incremental resources until the lead is further
qualified.
Bottom line: While these
examples may not directly apply to your company’s needs and current operations,
each of them is an invitation and a suggestion to explore similar kinds of
concerns and friction within your own organization and to see how AI and intelligent
automation can help to address and improve things.
