Their Question: How Do We Finance AI? Ours: How Much Cash Do We Have?

In Europe, companies are discussing how to finance their investments in artificial intelligence.

Equity? Bank loans? Capital markets?

Reading this, it is hard not to think of Türkiye.

How many companies here have actually reached the point of asking, ‘Which financing model should we use for our AI investment?’

Because many companies here have a much older, much more familiar file open on their desks:

Collections.

Credit.

Inventory.

Exchange rates.

Costs.

Month-end.

On one side, companies are discussing productivity investments for three years from now. On the other, many companies in Türkiye are recalculating their cash flow for the next three months.

The gap is not a technology gap.

It is a balance-sheet gap.

The European Central Bank’s latest study shows that most companies planning to invest in AI intend to finance it with their own funds.

Good.

But financing something ‘with your own funds’ comes with a prerequisite:

Having funds of your own.

This is precisely where things get complicated in Türkiye.

The economy has not come to a complete standstill. Production continues, exports continue, and there are companies still investing.

But the mood inside companies and the story told by macroeconomic indicators are not always the same.

When orders fall, customers extend payment terms, banks make credit lines more expensive, and suppliers demand cash upfront, a company’s growth calculations change overnight.

You may still look investment-ready in Excel.

Your cash balance may tell a different story.

That is, to some extent, what the industrial slowdown, high financing costs, and rising number of court-supervised debt restructuring cases have been telling us.

In Türkiye, capital is not merely expensive.

It is nervous.

And nervous capital has little appetite for long-term stories.

An AI project may deliver a 15% productivity gain two years from now.

But if you are struggling to fund working capital over the next six months, that 15% loses much of its meaning.

This is the unforgiving side of finance:

Even the right investment can become the wrong investment if made at the wrong time.

That is why I think the AI debate in Türkiye is starting from the wrong place.

Instead of asking, ‘Are companies using artificial intelligence?’

perhaps we should ask:

Which AI investment pays for itself fastest?

Because here, rather than ambitious transformation projects,

applications that accelerate collections,

reduce inventory needs,

shorten proposal preparation,

turn three days of work for the finance team into three hours,

and flag cash shortfalls earlier

may make more sense.

In other words, AI’s first major success in Türkiye may not be transforming the entire factory.

It may be keeping cash inside the business a little longer.

That may not sound as exciting as Europe’s ‘AI transformation’ presentations.

But companies survive on cash, not presentations.

Perhaps this is exactly where the difference between the two economies lies:

Europe is discussing how much to invest in AI.

In Türkiye, a well-managed company first asks:

When will this investment start making money for me?

And if you ask me today, the smartest AI project in Türkiye may not be the one using the most advanced technology.

It may be the one that pays for itself without leaving the company gasping for breath.