Revealed: The Smart Way Into Commercial Real Estate

Falling interest rates are sparking a rebound in interest in commercial property. However, for many first-time investors, commercial property can feel very intimidating. With commercial property, there are typically numerous different numbers, complex leases, and unfamiliar terminology.

But once you understand what to look for, the pathway into commercial becomes much clearer and far more achievable than most people realise. So, what does a smart entry point into commercial property actually look like?

If there’s one standout option, it’s typically an industrial property with value-add potential.

Why industrial is the right place to start

Among all the commercial sectors, industrial is currently the most stable and accessible. Demand is being driven by the trades, small manufacturers, logistics operators and e-commerce businesses, many of which are growing rapidly and need practical space to operate from.

Unlike retail and office properties, industrial assets are typically simpler to understand. They’re often lower maintenance, easier to lease and more resilient to changes in the economy. This makes them well-suited to first-time investors who want to enter the market with confidence.

The importance of value-add potential

When looking at entry-level opportunities, many investors make the mistake of prioritising presentation. But it’s generally not the flashiest property that delivers the best returns. It’s the one where you can create the most upside.

That might mean buying a property where the current rent is well below market value. When the lease ends, you have the opportunity to negotiate a new lease at a higher rate, instantly increasing the property’s value.

In other cases, it may be a warehouse with a short-term lease in a high-demand area, providing you the opportunity to renegotiate the terms and secure a better return. Even basic improvements like repainting, improving access, or updating signage can make a big difference to tenant demand.

Don’t chase yield for the sake of it

A common trap for first-time commercial buyers is chasing the highest yield on offer. While yield is an important consideration, it shouldn’t be the only one. A high yield can sometimes signal a risky investment, one with a poor location, limited tenant demand, or low capital growth prospects.

Instead, smart investors focus on balance. A net yield of six to seven per cent in a strong, established area with reliable tenants and good fundamentals is often a far better outcome than a nine per cent yield in a declining market.

Yield is only part of the story. A good commercial investment is one where the income is sustainable, the asset has growth potential, and the risk is well-managed.

The risks of starting with retail or office

Retail and office properties can be suitable for experienced investors, but they’re often more complex and carry higher risk, especially for those just starting out. Retail in particular has faced significant changes in recent years, with e-commerce altering the way consumers shop.

Unless the property is in a high-traffic, local strip with essential services like medical, food or personal care, vacancy risk can be high. Office space is still adapting to the post-COVID shift towards remote work, and in many cases, demand has softened. If you’re entering the commercial market for the first time, it’s better to stick to simple, functional industrial assets in proven locations.

Where to look, and why

For first-time investors, some of the best opportunities can be found in outer-metro industrial precincts or larger regional centres.

Suburbs in places like Geelong, Logan, Toowoomba or Altona North offer a compelling combination of affordability, strong tenant demand and relatively low vacancy risk.

These areas often have diverse local economies that don’t rely on a single industry and offer entry points between $600,000 and $1 million, a sweet spot where competition from institutional investors is limited and owner-occupiers are still active.

What a good entry deal looks like

Imagine purchasing an industrial shed for $750,000 with a tenant in place and a current net yield of 6.5 per cent. The lease has about 18 months left, and you know the current rent is around $10,000 below market.

Once the lease expires, you can renegotiate or re-lease at the correct rate, increasing the income and, by extension, the value of the asset.

That’s a textbook example of a good commercial entry point. The property is tenanted, it generates income from day one, and it has a clear path to growing your equity within 12 to 24 months.

Abdullah Nouh is the founder of Mecca Property Group, a boutique buyer’s agency in Melbourne helping Australians build wealth through strategic property investment.

There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.

What gives?

U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.

The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.

All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.

But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .

Landing a job is tough for most everyone else.

Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.

Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.

Playing a different game

It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.

Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.

You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.

“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.

He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.

The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.

As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.

A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.

In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .

Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.

He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.

If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”

Overlooked

James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.

He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.

He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.

Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.

“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”

The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.

“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”

He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.

It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.