Why Every CEO Needs a Drone Maker Strategy for AI

In modern warfare, large, complex systems
costing millions of dollars are defeated

by drones costing hundreds of dollars.

For example, there are routinely reports
of $30 million missile defense systems

overwhelmed by swarms of $500 drones.

In business, the same math apply.

Welcome to the Enduring Advantage podcast.

I'm your host.

Zachary Alexander.

Right now, CEOs are watching cash cows
they spent decades building in the

form of proprietary systems, carefully
cultivated expertise, painstakingly

constructed competitive moats, turned
into table stakes by swarms of newly

launched startups and category adjacent
competitors using AI capabilities that

may not have existed seven months ago.

This is called threat saturation
and it's a strategic concept.

CEOs are missing, while most of
them are entirely focused on the

moves and machinations of open AI
and the other major AI providers.

Here's a pattern you've probably
witnessed a thousand times

over the last couple of years.

Major AI company launches a capability.

Executives scramble to understand
the implications and what

it means for their business.

Consultants debate whether this is
a threat or an opportunity Your team

is tasked to implement the additional
capability at breakneck speed.

You gain temporary relief.

Then seven months later,
the cycle repeats.

Only this time the screams are much
louder because the threats have doubled

in both volume and sophistication.

Stop me if you've seen
this play out in real time.

The real problem isn't the latest
AI release or just the speed

in which capabilities double.

The problem is that threat saturation
is fundamentally different from

traditional competition, and most
CEOs are applying the wrong strategic

frameworks to meet the new challenges.

Let me be, precise about what
threat saturation actually means.

Threat saturation occurs when you face
more competitive threats than your

business strategy can reasonably handle.

Why this matters.

These threats aren't coming from
your traditional competitors.

Everyone knows the
Blockbuster video story.

Video

Zachary Alexander: retail Giant killed
by Netflix streaming, but that was 2000.

And it was one disruptor
with a clear business model

entering an adjacent market.

Let me now show you what threat
saturation looks like today.

Trust me, it's not about late fees.

As a case study, let's talk
about Southeast Asian retail

and merchant services.

You are a merchant leader and
retail management consultant.

Life's good.

Four completely different companies
with four completely different

starting points all suddenly
converge on your competitive space.

All deploying AI capabilities
simultaneously and some

cases cooperatively, meaning
sharing capabilities.

Here are the new vectors (participants)
you need to be concerned about.

Grab.

Started as a ride hailing app.

Now, their merchant AI assistant gives
small and large retails access to expert

guidance, traditionally reserved for
enterprises at a fraction of the cost.

When I say fraction of the cost, I'm
talking exponentially less expensive.

Indonesia's answer to grab,
nearly even in market share.

Also added merchant services, AI
support and financial services.

And then there's Sea Group and it's
e-commerce platform, Shopee plus Sea

Group's FinTech Shopee Pay combined
for a broad retail and market

ecosystem with AI powered tools.

Lazada, Alibaba's, Southeast Asian
platform, deploying super app

features, retail eWallet Logistics
and AI powered merchant services.

Four companies, four different
origin stories all converging

on the same target market.

All deploying similar AI capabilities
all arriving simultaneously.

that's what threat saturation
looks like in the market today.

The management consultants never
saw it coming because they were

watching the wrong horizon.

They were tracking traditional retail
consulting competitors while ride hailing

apps and e-commerce platforms were
building AI powered merchant services.

Here's a question for you.

what's coming for your industry from
companies you've never even heard of?

No.

here's a better question.

How do you build competitive
advantages that accelerate

faster than AI capabilities do?

Traditional strategies can't answer that.

They assume you know your competitors.

They assume industry
boundaries are stable.

They assume.

You'll have all the time in the world
to identify your competitor's weaknesses

before they get large enough to make
any real impact on your bottom line.

All three of these
assumptions are obsolete.

Drone warfare strategies can
provide answers to these questions

on the battlefield and enduring
advantage can do the same in

business or a new opportunity space.

Before we go any further.

Let's define what we mean
by enduring advantage in a

threat saturated environment.

Enduring advantage is a competitive
positioning that compounds over time

through value density strategies and
intelligent feedback loops, creating

barriers to imitation that become
mathematically insurmountable as the

increase of AI capability accelerates.

This is not about temporary wins, not
this quarter's edge, not the advantage

you get from simply implementing
AI before your competitors do.

We're talking about positioning
that strengthens automatically while

competitors chase the next capability
release and panic about what it

means for their business model.

Now let's redefine speed for an AI
abundant era because most executives are

measuring it using outdated concepts.

Speed in traditional business, how
quickly your business system responds

to customer queries, how fast you ship
products, how rapidly you close deals.

Speed in an AI abundant era.

Is a multidimensional calculation,
First dimension: traditional

response time still matters.

But it's table stakes now.

AI can respond instantly
to simple requests.

But something that's a little more
than initial acknowledgement won't

protect you from a startup swarm.

Second dimension: Complexity.

How fast can your AI enabled system
complete complex projects that

used to take weeks or months to do?

Now we're entering the AI abundant
opportunity space and we're dealing

with a level playing field where we
have to compete on intellect and drive.

This is where it helps to
have a drone maker mentality.

Just an aside drone makers are the kind of
people who use consumer grade 3D printed

airframes to defeat military spec hardware
costing tens of millions of dollars.

It's not about the cost of the
application, it's about the novelty of

the strategy, the intellect required
to complete it or even comprehend it.

Third dimension: Unsupervised work.

Practically speaking, this has to
do with how long your AI systems

can work on complex problems
without human intervention.

This is where the real AI
capabilities power happens.

For the record.

We're still talking
about people in the loop.

Even though AI can handle all of the
necessary tasks required to accomplish

the mission autonomously, drone makers
still use operators to respond to

situational changes in the battle space.

And you should do the same in business.

You could argue that complexity
represents two horns of a dilemma.

On the one side, you have
large multinational companies

with unlimited resources.

On the other side, you have middle
market companies with consumer grade AI

capabilities and intellect, and a little
secret sauce learned along the way.

. Back in the day, it was common
to talk about the threat posed to

your wallet by consulting wear.

This was enterprise software that
required a team of high price

consultants to deliver any functionality.

A remnants of which you see an open
AI's announcement of $10 million

minimum for its consulting services.

For those using enduring advantage,
this should set off blaring alarm bells.

There have to be drone makers
licking their lips, waiting for

any indication that a company is
using open AI's consulting services

because they're seeing a easy mark.

Okay.

Obviously I'm not talking
about real drone makers.

I'm talking about people with
the drone maker mentality.

You can think of them as the people who
use off the shelf components and task

built AI functionality to defeat systems
that cost orders of magnitude more.

Plus they understand that AI
capabilities are doubling every seven

months, and in the opportunity spaces
created by Open AI's consultancy.

Speed is about how quickly your
organization learns and adapts, not just

the response time of your consultants.

Not to beat a dead horse, but
let's get real clear about

what threat saturation actually
represents and why common defensive

reactions miss the point entirely.

Traditional competitive threats
follow predictable patterns.

One or two major competitors
per market segment.

The rest are too small to matter.

It's your 80 20 rule.

Known capabilities and business models,
most entrepreneurs are like that.

So that's the traditional
threat environment.

Industry boundaries
remain stable for years.

You know, there's no
smudging of the lines.

Things happen and people get upset when
you start to talk about possibly using

their solution in a new environment.

The time to analyze threats and
develop strategic responses.

This is to say there is a certain
rhythm or flow about things

generally we're talking about.

A yearly cycle threat saturation creates
a different opportunity space entirely.

Multiple simultaneous threats.

Not one or two competitors,
but 5, 10, 20 organizations all

developing similar capabilities
simultaneously using the same AI tools.

Stealth threats are the ones where a
company decides that they're not gonna

broadcast that they're working in a space.

You know, you see these
with startups all the time.

These startups, you
know, they're stealthy.

They don't want to tell you what
they're actually working on.

They keep everything, you
know, close to their vest.

Phantom threats are the ones that seem
to pop on and off your radar screen

as they ride along, just above the
noise floor, meaning that, you know,

there's something there, but it's
too small to devote any resources

to investigate until it's too late.

Compressed response times, no time
for strategic planning cycles.

By the time you completed your initial
analysis, more threats have emerged and

your competitive advantage is collapsing.

Mainly because AI capabilities
double every seven months.

I can't say that enough.

And then there's cost as symmetry.

Your new competitors are deploying
capabilities for thousands of

dollars that it took you millions
of dollars and custom integrations

to build and months to deploy.

I understand the panic AI just blew
a competitive advantage hole in your

business model that you spent years
building and millions developing.

But here's what everyone's missing.

The individual threats aren't the problem.

Threat saturation is simply a
symptom of a deeper reality.

The systematic commoditization
of every business capability

that can be enhanced by AI.

And this commoditization is accelerating.

So let's do a back of
the envelope calculation.

Everything in the AI ecosystem is
doubling in capability every seven months.

Not just the large language
models, everything, the tools, the

databases, the specialty tools like
vector database storage, the UI

components, you get the picture.

And they're not all on the same timeline.

They don't happen in the same window.

So basically everybody doesn't say: okay,
we're gonna hold our new advancement

until everybody else is ready and
we're gonna launch at the same time.

Not how it works.

Basically, it's happening all the time.

In past episodes, we talked about how
the doubling of AI capabilities led

to the competitive advantage built
with them to have an 18 to 24 month

window before they become table stakes.

However, because of the
capabilities of everything else

in the AI ecosystem are doubling

Your 18 month competitive advantage
could shrink to approximately three

to four months before competitors can
replicate it, using better tools, doing

it cheaper, and deploying it faster.

Depending on where your most
important technology are in their

capabilities, doubling cycle.

This is not a business model.

This is a treadmill that's accelerating.

And here's the mathematical reality that
makes threat saturation so dangerous.

Traditional defense strategies
assume you can outspend attackers.

In military terms.

You can build a better missile system
In business terms, you can invest more

in r and d, build bigger industrial
campuses, the people working with

this new drone maker mentality,
they're spending a hundred hour weeks.

So it doesn't matter how much you
invest in your r and d that you expect

to see a payback in 18 to 24 months.

You know, if you're working a hundred
hours a week, you're gonna get something

out of it, and it's gonna be a moving,
basically, you're gonna be moving the

goalpost every chance you get, But
Threat saturation in an AI abundant

environment inverts the cost equation
when attackers can deploy capabilities

in a fraction of what defense costs.

Volume overwhelms
sophistication every time.

It's why swarms of $500 drones defeat
$30 million Defense systems routinely.

And it's how AI powered middle market
companies can outperform better funded

multinational enterprises despite
having a fraction of their resources.

Next, let's talk about the
strategic error that's crippling

most organizations right now.

treating each new AI capability release
as a strategic inflection point rather

than as an expected variable that's
already priced into your planning.

It's like a logistics company treating
traffic patterns as an unexpected

disruption instead of as a predictable
variable you can optimize around.

Every time open AI or anthropic
releases new capabilities.

I watch the same cycle, play out new
capability launch executives, paniced,

what does this mean for our business?

Will we survive?

Then there's market confusion.

Clients ask, should they switch
strategies or find a new vendor?

Then there's a rush to implementation.

That's the AI version of
keeping up with the Joneses.

Then there's temporary relief.

Oh my God, we really dodged a bullet.

Next launch, repeat entire cycle,
seven months later, only louder.

This cycle exists because organizations
have allowed AI capability advancement

to creep onto their critical path.

Just to be clear, when I say critical
path, we're talking about the steps that

are essential to organizational viability.

Even a brief delay can
leave lasting scars.

When you allow AI capability
advancement onto your critical

path, you guarantee inconvenient
disruptions and constant chaos.

But you also can't ignore these advances.

Ignoring these advances makes
it difficult to keep up.

It leads to what I like
to call the capabilities.

Avalanche capabilities
double every several month.

The fear of falling behind and
the very real consequence caused

a cascading chain of failure.

Once the capabilities avalanche
is underway, minor changes

cost exorbitant amounts because
you haven't made incremental

adaptations to keep systems current.

So what's the answer?

Concentrate on enduring advantage.

It's more important to strengthen
your positioning and find ways to

ensure new capabilities compound your
advantage rather than decrease 'em.

We call this adaptive intelligence.

Key characteristics, self-improving
systems capabilities that strengthens

through feedback loops rather
than requiring manual adaptation.

Enhanced learning advantages that
accelerate as AI capabilities improve

rather than being made obsolete by them.

Automatic strengthening competitive
positioning that improves without

requiring constant investment
or management intervention.

predictive intelligence systems that
anticipate competitive advantage market

changes before they actually materialize

Adaptive intelligence operates through
intelligence multiplication measuring

how much organization's performance
improves after AI enhancements across key

decision categories, strategy, operations,
customer success, competitive decisions.

The power comes from compound effects.

If improvements reinforce each other in
virtuous cycles For example, better AI

enhanced proposals lead to better clients.

Better clients provide
better case studies.

Better case studies enable
even better proposals creating

automatic capability development.

Why it matters.

In environments where AI capabilities
double every seven months.

Traditional competitive advantages
become rapidly replicable commodities.

Adaptable intelligence solves this by
creating advantages that accelerate

through the same AI advancement
that threatens traditional moats.

This is contrasting with static
capabilities that require continuous

defense and reinvestment just
to maintain their effectiveness,

implementing just a few of the
changes outlined on this podcast.

And you will help create a drone
strategy that will allow you to

survive the threat saturation
that tank Many of your traditional

competitors always remember good things
come in small proms and we're out.