Country clubs are an American tradition among those wealthy enough to afford them. But as unique experiences become increasingly coveted, many members are looking for more exciting alternatives to a golf course and some fancy hors d’oeuvres. Enter Apex Motor Club.

APEX Motor Club is a private motorsports club in Maricopa, Arizona, built around cars, community and competition.

As COO, Bill Barba puts it, “We’re similar to a country club, but instead of golf courses, we have race tracks.” 

Costs and culture 

The Club is a 280-acre facility featuring 2 race tracks, a six-acre skid pad, 96 trackside garage condos, a drivers’ lounge and a clubhouse. 

The goal is to give motorsports enthusiasts a place to share that passion with others, including their family members. At the same time, the exclusive luxury landscape offers an escape from the pressure of running a billion-dollar company, as some of its members do. 

“We’ve got members whose names are known,” Barba says. “They run global companies, plus some local entrepreneurs that built great businesses. Motorsports are interesting because they all share the joy, rather than expecting to be Mr. or Mrs. So and So when they’re out here. That’s part of the culture we’ve created.”

There are two primary membership types: Gold, a $70,000 initiation fee plus an annual $8,000 fee and Platinum, a $90,000 initiation fee plus an annual $15,000 fee. The two are similar, offering 240+ annual track days, transferable membership and family access, with Platinum offering event host days. They also recently introduced a one-year membership for $35,000 and an under-35 membership with a $25,000 initiation fee plus $4,500 annually. 

“Motorsports is not a cheap endeavor,” Barba explains. “To run a car for a weekend out here, you go through tires, brakes and maintenance. Depending on the type of car, that cost can go up quite a bit.” 

While APEX provides the location and platform, members must maintain their own cars. Some have small teams doing only the necessary maintenance, while others come to the track with five people analyzing the data behind each lap. Some look to shave milliseconds off their cornering, while others just want a place to let the fancy ride they just bought rip. 

Driven to drive 

APEX’s business model includes partnerships with luxury car companies. They have a deal with Lexus, which brought out cars to join the APEX fleet. They also have a relationship with Aston Martin, which has an on-site presence in their garage condos. The local McLaren Scottsdale, one of the country’s highest-volume McLaren dealers, is a corporate member of the club. 

Companies will also rent the tracks for events, including Ferrari, Mercedes and Porsche.

“It gives them a chance to put people who aren’t necessarily enthusiastic enough to join a club on a track to understand what the car can do,” Barba explains. According to him, 85% of the engineering in performance cars never shows up on the street. At APEX, someone might own their fourth Porsche 911 but never experience its full power until they get on the course with an instructor. 

“The guy who buys or leases a Lamborghini to park at the valet is not a member of a motorsports club,” Barba says. “Our members tend to have more enthusiasm for the vehicles. Then there’s a whole different area of what level of racing they may want.” 

While most members are interested in track time, Barba estimates about 20% take wheel-to-wheel racing seriously. For them, APEX runs an 11-race series with 10 to 25 people per race, depending on the car. “Some people love it and thrive on the competition and pushing the car. Others want to enjoy the tracking and their times, but not race,” Babra says. 

A family affair 

What sets APEX apart from the competition is its family policy.

“If you join APEX, your spouse and kids are a part of it, and we don’t age them out,” Barba shares. “What we saw historically was that a lot of clubs would age kids out, and then they’d have to buy a membership. We want kids to stay as long as possible because it keeps parents, grandparents and everyone else engaged. So it’s a family membership because we want it to be a family experience.” 

This plays into a larger theme among the wealthy: finding the “new inheritance.” Rather than passing down expensive paintings and big houses, rich parents want to give their kids something more meaningful and personal.

One option is their passions. “Members will talk about the first race car they had, the first time they reached a certain speed, or the first time they watched their child drive a car,” Barba says. “It’s a passion that passes down, and it connects back to what I believe is most potent about motorsports: the emotions.” 

One example is the Bacon family. Seth Bacon had built a successful logistics business focused on organ donations and sold it. Looking for a way to spend more time with his teenage son Jace as he approached adulthood, he found an unexpected solution: racing.

“He was about to turn 16 and get his driver’s license. He’s getting a job. He was busy in school. He’s about to go off to college, and I thought this is that period where he’s beginning to separate himself from the nest,” Seth says. “I wanted an opportunity for us to still do something tight together.”

The two visited APEX to watch a few races. Before long, they bought a pair of Radical race cars and hit the track themselves.

“Instead of the son ignoring him at 16, they’re working together on racing,” Barba says with a laugh.

At Jace’s first race at another club in Nevada, father and son competed together, with Jace winning. 

“It made a real impact on the dad that out there, his son is an equal with guys who are running billion-dollar companies,” Barba says.

The Bacons could take their cars to any track, but few offer the built-in community they’ve found at APEX. 

“There’s a lot of senior drivers, a lot of retired professional drivers who are members there, and everywhere we go, they’re always checking in on him, asking about his career,” Seth says of Jace. “It really is more of a community of people who are willing to support one another, not only on track, but also, how did that business of yours go? Did you get that acquisition you were looking for? What do you need next?”

Business connections are great, but at the end of the day, APEX is about cars, community and competition. A hole-in-one is unforgettable, but the average day on the golf course doesn’t necessarily make the lifetime highlight reel. Driving a luxury race car at breakneck speeds on an open track? That’s an experience that’s not only incredible, but repeatable.

Country clubs are an American tradition among those wealthy enough to afford them. But as unique experiences become increasingly coveted, many members are looking for more exciting alternatives to a golf course and some fancy hors d’oeuvres. Enter Apex Motor Club.

APEX Motor Club is a private motorsports club in Maricopa, Arizona, built around cars, community and competition.

As COO, Bill Barba puts it, “We’re similar to a country club, but instead of golf courses, we have race tracks.” 

For most entrepreneurs, growth is the ultimate measure of success. Expanding into new markets, acquiring customers, increasing revenue and building stronger teams are often the priorities that dominate strategic discussions.

However, one critical factor frequently receives less attention: the technology infrastructure supporting everyday business operations.

A company might have an excellent product, a growing customer base and an ambitious expansion strategy, yet still struggle to scale because its internal systems cannot keep up with increasing demand.

Technology challenges rarely appear overnight. They develop gradually through outdated software, disconnected applications, inefficient databases, inadequate security measures and technology investments made without a long-term strategy.

These issues may seem manageable during the early stages of business development. But as organizations grow, even minor inefficiencies can become expensive obstacles.

Understanding these hidden challenges is essential for entrepreneurs who want to build businesses capable of sustaining long-term growth.

1. Outdated technology can create unexpected operational costs

One of the biggest challenges growing businesses face is their dependence on outdated technology.

Many organizations continue using software and infrastructure implemented years earlier. These systems may still perform their original functions, making replacement or modernization appear unnecessary.

However, maintaining older technology can become increasingly expensive. Outdated systems may require specialized technical support, frequent maintenance, manual workarounds and additional resources to remain compatible with newer applications.

The financial impact extends beyond direct maintenance expenses. Employees may spend additional hours completing routine tasks, departments may struggle to exchange information, and customers may experience slower service.

These inefficiencies reduce productivity and make it harder for companies to respond quickly to changing market conditions.

For business leaders, the important question is not simply whether existing technology still works. It is whether that technology continues to support the organization’s future requirements.

Regular infrastructure assessments can help identify systems that are becoming expensive to maintain or increasingly difficult to integrate with modern business applications.

2. Disconnected business systems reduce productivity

As businesses expand, they frequently introduce new software to address specific operational requirements.

A sales department might adopt a customer relationship management platform, while the finance team uses separate accounting software. Marketing teams may rely on analytics platforms, and operations departments might introduce project management applications.

Each tool can provide individual benefits. However, problems arise when these systems cannot communicate effectively. Employees may need to enter identical information into multiple applications. Managers might receive conflicting reports, while customer-facing teams struggle to access accurate information.

Consider a growing service company where sales, billing and customer support operate through separate systems. When a customer purchases a service, employees may need to manually transfer details between departments. This increases the possibility of errors and delays.

As transaction volumes increase, these problems become more difficult to manage.

The solution is not necessarily purchasing additional software. Instead, companies should evaluate how existing applications exchange information and whether integration or workflow improvements can eliminate unnecessary manual tasks.

Entrepreneur’s discussion of why businesses can have access to powerful tools and still struggle to make progress highlights the importance of turning technology availability into practical business capabilities.

Entrepreneurs should prioritize connected systems that provide reliable information across departments and simplify daily operations.

3. Poor database decisions can limit business scalability

Behind most business applications is a database responsible for storing, organizing and retrieving critical information. Customer records, financial transactions, inventory details, employee information and operational reports often depend on database infrastructure.

When businesses are relatively small, database performance may receive little attention. However, as customer activity increases and applications become more complex, limitations in database architecture can begin affecting operations.

Slow queries, inefficient data processing, limited integration capabilities and inadequate capacity planning can create performance bottlenecks. These issues may result in delayed reports, slower applications and additional infrastructure expenses.

Database selection also involves important architectural considerations.

For example, organizations maintaining applications built around SAP SQL Anywhere or SAP Adaptive Server Enterprise may need to evaluate differences in their deployment requirements, workload characteristics, administrative complexity and scalability.

Understanding how different database systems compare can help technical teams assess the suitability of existing platforms before making decisions about application upgrades or infrastructure modernization.

Importantly, replacing a database is not always the best solution. In some cases, performance improvements can be achieved through query optimization, indexing, infrastructure upgrades or improved database administration.

In other situations, changing business requirements may justify a more substantial modernization initiative.

Entrepreneurs do not need to become database specialists. However, they should understand how database reliability, performance and maintenance requirements affect customer experience and business continuity.

Treating data infrastructure as a strategic business asset rather than an isolated technical concern can help organizations avoid costly decisions as they expand.

4. Technology investments without clear business goals can waste resources

Businesses are constantly introduced to new technologies promising greater efficiency, improved customer experiences and increased profitability. Artificial intelligence, automation, cloud platforms and advanced analytics all offer meaningful opportunities.

However, adopting technology without clearly defined objectives can create additional complexity instead of delivering measurable improvements.

A company might invest in an expensive automation platform without first examining whether its underlying processes are efficient. Another business might purchase sophisticated analytics software without having employees who can interpret and act on the information.

In both situations, the problem is not necessarily the technology itself. It is the absence of a clear implementation strategy.

Before introducing a new system, business leaders should identify the operational challenge they want to solve. They should also establish measurable success indicators, such as reduced processing time, improved customer response rates, lower operational expenses or increased employee productivity.

A practical approach involves testing new technology within a limited business function before expanding its use across the organization. This allows teams to evaluate effectiveness, identify implementation challenges and determine whether the investment provides sufficient value.

Technology should support business strategy rather than become a substitute for it.

5. Weak cybersecurity can threaten business continuity

Cybersecurity is frequently viewed as a technical responsibility assigned to an IT department or external service provider. However, its implications extend directly to business growth, financial stability and customer trust.

As organizations expand, they typically collect more customer information, process larger transaction volumes and provide system access to additional employees and partners. Each expansion can introduce new security considerations.

Weak access controls, outdated applications, inadequate backup procedures and insufficient employee training may increase exposure to cyber threats.

A serious security incident can interrupt operations, damage customer relationships and create substantial recovery expenses. For smaller businesses, the financial and operational consequences can be particularly difficult to absorb.

Effective cybersecurity requires more than installing security software. Organizations should implement appropriate access controls, maintain reliable backups, regularly update systems and establish procedures for responding to incidents.

Employee awareness is equally important because human mistakes can undermine otherwise effective technical safeguards.

Business leaders should consider cybersecurity investments part of their overall risk-management strategy. Protecting systems and information helps maintain the operational stability necessary for sustainable expansion.

6. Lack of reliable data can lead to poor business decisions

Modern businesses generate significant amounts of information through sales transactions, marketing campaigns, customer interactions and internal operations. Yet collecting data does not automatically translate into better decisions.

Many organizations struggle with inconsistent reporting, duplicated records, outdated information and fragmented data sources.

For example, a company might report strong revenue growth while overlooking increasing customer acquisition costs or declining profitability. Similarly, managers may make inventory decisions using incomplete information because different departments maintain separate records.

These challenges can become more serious as organizations expand into additional markets or introduce new products.

A reliable data strategy begins with establishing consistent definitions for important business metrics. Teams should agree on how revenue, customer retention, operational efficiency and other key indicators are measured. Organizations should also identify the systems responsible for maintaining authoritative records.

Automated reporting can reduce manual errors, while regular data-quality reviews help identify inconsistencies before they affect important decisions.

Ultimately, entrepreneurs need information that is accurate, accessible and relevant to their strategic priorities. The goal is not to collect as much data as possible but to turn reliable information into timely business decisions.

7. Scaling too quickly can expose technology weaknesses

Rapid growth creates exciting opportunities, but it also places additional pressure on existing business systems.

A technology setup designed for a company with 10 employees may not adequately support an organization with hundreds of employees operating across multiple locations.

Increased transaction volumes, additional users, more complex reporting requirements and greater customer expectations can expose previously unnoticed limitations.

Businesses may experience application slowdowns, service interruptions, inconsistent processes or rising infrastructure expenses. These problems often emerge when organizations expand faster than their technology planning. Scalability should therefore be considered before major expansion initiatives.

Business leaders can begin by evaluating whether existing systems can accommodate increased workloads and additional users. They should also examine whether infrastructure can be upgraded without requiring expensive or disruptive changes.

Cloud services, modular software architecture and well-documented operational processes may provide greater flexibility, depending on the organization’s requirements. However, scalability involves people and processes as much as technology.

Planning ahead can help companies avoid reactive technology investments made under pressure.

8. Overlooking employee training reduces the value of technology

Even the most advanced technology cannot deliver its full potential if employees do not understand how to use it effectively.

Businesses sometimes invest substantial resources in software implementation while allocating limited time or budget to training.

This can lead to inconsistent adoption, employee frustration and continued dependence on inefficient manual processes. In some cases, employees may avoid using new systems altogether because they find familiar workflows easier.

Successful technology adoption requires clear communication about why changes are being introduced and how they will benefit daily operations. Employees should receive practical training relevant to their responsibilities.

Organizations can also identify internal technology champions who help colleagues understand new processes and provide feedback during implementation. Regular evaluations can reveal whether systems are being used as intended and whether additional training is required.

By treating employee development as part of technology investment, businesses can improve adoption rates and achieve more consistent operational benefits.

9. The absence of a long-term technology roadmap creates unnecessary risk

One of the most common strategic mistakes is approaching technology decisions individually rather than as part of a coordinated plan.

A business might replace an application when it fails, upgrade infrastructure when performance deteriorates or introduce new software when a department requests additional capabilities. While these decisions may solve immediate problems, they can create a fragmented technology environment over time.

A long-term technology roadmap provides a more structured approach.

It should identify current infrastructure limitations, anticipated business requirements, implementation priorities and realistic investment timelines. Business leaders should collaborate with technical specialists to evaluate which systems require immediate attention and which can be improved gradually.

The roadmap should also account for potential changes in customer demand, staffing, regulatory requirements and market conditions. Regular reviews are important because business priorities and technology capabilities continue to evolve.

A useful roadmap does not need to predict every future requirement. Instead, it should provide a flexible framework for making informed decisions while minimizing unnecessary disruption.

Turning technology challenges into growth opportunities

Technology problems often remain hidden until they begin affecting revenue, productivity or customer satisfaction. By that stage, addressing them may require urgent investments and operational changes that could have been avoided through earlier planning.

Entrepreneurs can take a more proactive approach by reviewing their technology environment regularly and identifying potential weaknesses before they become significant obstacles. This includes evaluating outdated systems, improving application integration, monitoring database performance, strengthening cybersecurity and investing in employee training.

Equally important is connecting every major technology decision to a measurable business objective. Not every company needs the newest software, the most sophisticated infrastructure or an immediate migration to emerging technologies. In many cases, improving existing systems and simplifying workflows can produce meaningful results without unnecessary spending.

The businesses best positioned for sustainable growth are not necessarily those investing the most in technology. They are those making thoughtful decisions about where technology can deliver lasting operational and strategic value.

Ultimately, business growth depends on more than ambitious goals and market opportunities. It also requires a reliable foundation capable of supporting those ambitions.

By recognizing and addressing hidden technology challenges early, entrepreneurs can reduce operational friction, make better decisions and create organizations that are better prepared for the next stage of growth.

The first time I watched a machine draft something that looked finished, I almost signed off. The language was clean. The structure made sense. Then I tried to check three claims against the source material and burned more time reconstructing the case than the draft had saved. Speed had moved. The cost had not gone away. It had just changed rooms.

I remember the annoyance more than the draft. The tool had done its job. The review path had not.

Here’s my situation, so you know where I’m coming from. I founded Main & Machine, an AI implementation firm for small and mid-size businesses, and I also sit in the buyer seat when technology lands in a real operating company. (Disclosure for the editor: I have a financial relationship with Main & Machine.) I teach management and entrepreneurship at Arizona State University’s W.P. Carey School of Business. Across those chairs I keep seeing the same pattern: owners celebrate generation and underbuild verification.

Most shops treat “human in the loop” as a checkbox on a vendor slide. That move fails in practice. The economic value of generated output depends on how cheaply and reliably a competent person can verify it in the real decision. U.S. Census Bureau data from late 2025 through early 2026 put overall business AI use in the 17% to 20% range, with more firms still planning to join them. The next wave will not stall because models got worse. It will stall where checking stays slow, opaque or socially expensive.

I used to treat a second click as proof of judgment. Wrong. A second click can still leave you with one judgment if the reviewer never saw the underlying case on independent terms.

Price the review path before the draft

Before you automate a deliverable, write down who will check it, how long that check should take and what happens when the check fails. Generation reduces first-draft cost. Uncertain output creates a checking obligation. When verification is fast and error is reversible, the gain survives. When checking requires scarce expertise, reconstructing evidence or absorbing liability, the apparent speed just moves cost downstream.

The principle fits in one line: Cheap output with expensive verification is still expensive work.

Try the same pricing this week. Pick one workflow you want the machine to touch. Estimate minutes to generate and minutes to verify on a hard case. Skip the polished demo. A restaurant owner might let a tool draft the weekly schedule and still need a manager who can read labor rules and walk the floor. A clinic owner might let a tool summarize intake notes and still need a clinician who can open the raw chart. If the hard-case check cannot fit the day, the automation is not ready.

Give reviewers a route the machine did not frame

A reviewer cannot meaningfully check an automated recommendation when the system is also the only account of the underlying case. When evidence, framing and conclusion arrive through one interface, disagreement requires reconstructing information the reviewer never independently saw. Time pressure then makes rubber-stamping rational.

The principle: Review needs an independent path to the facts.

Build that path on purpose. For high-stakes work, keep a sampled set of raw inputs available beside the machine’s summary. Ask the reviewer to name the decisive evidence and the uncertainty before the recommendation appears, then compare reasons. A franchisee can do this on customer-complaint drafts. A contractor can do it on estimate language. A professional-services owner can do it on client memos. Agreement alone proves little. Shared framing can produce shared error. What matters is whether disagreement can change the action and survive in the record.

Rehearse the override under pressure

An override that exists only as a policy or a button is not a reliable safeguard. Automation reduces exposure to normal system dynamics, while the ugly cases compress time and raise uncertainty. People need practice recognizing, deciding and acting without the automated system when the answer feels wrong.

The principle: Practice the no until it is usable.

Run a short drill this month. Take three recent outputs the team almost shipped. Hide the machine’s confidence language. Ask a named owner to reject one of them with a written reason and an alternate next step. Then watch whether the rejection sticks or gets smoothed over because the draft sounded finished. Automation leaves a harder residue: The exceptions that remain are ambiguous, rare and consequential. If your team only ever sees clean demos, they will not keep the skill they need when the residue shows up on a Tuesday afternoon.

Here’s where I’d start this week: Pick one AI-assisted workflow, write the review minutes and the independent evidence route on a single page, and run one override drill with the person who actually owns the outcome. Say it to the team before you expand the tool’s reach.

The draft that looked finished still sits in my mind. The checking cost was the real product. Build that first, and the machine earns its keep.

The first time I watched a machine draft something that looked finished, I almost signed off. The language was clean. The structure made sense. Then I tried to check three claims against the source material and burned more time reconstructing the case than the draft had saved. Speed had moved. The cost had not gone away. It had just changed rooms.

I remember the annoyance more than the draft. The tool had done its job. The review path had not.

Here’s my situation, so you know where I’m coming from. I founded Main & Machine, an AI implementation firm for small and mid-size businesses, and I also sit in the buyer seat when technology lands in a real operating company. (Disclosure for the editor: I have a financial relationship with Main & Machine.) I teach management and entrepreneurship at Arizona State University’s W.P. Carey School of Business. Across those chairs I keep seeing the same pattern: owners celebrate generation and underbuild verification.

When I wrote about the difference between using AI and being AI-native, the most frequent response from executives was a polite objection: the distinction is real, but redesigning how work happens is a luxury reserved for companies with transformation budgets.

I spend my working life inside those budgets, and most of what they buy is the expensive undoing of habits that formed when the company was small. A founder has nothing to undo yet, which is why the quarter ahead is worth more than the three-year program a large enterprise will fund.

Here is the plan I would run if I were building a company today with no budget beyond my own calendar. In 90 days, with no new software and no outside help, you can do the three things that separate an AI-native business from one that merely uses AI: Write down how the work actually happens, take ownership of your data, and redesign who decides and what gets measured.

Why the big companies are paying for your quarter

In June, Genpact and HFS Research published a survey of more than 2,000 senior executives, and 85% of them said that accumulated enterprise debt — meaning undocumented processes, unusable data, aging systems and unprepared people — is limiting the value they get from AI. The researchers put the trapped value across the Global 2000 at roughly $18 trillion, found that only 33% of enterprise data is AI-ready and estimated that inefficient or manual processes consume about 40% of a typical employee’s week. More than half of those enterprises have no funded initiative to fix any of it.

Every item on that list is a habit before it is a legacy. Nobody decides to have undocumented processes; they go unwritten while the company grows, and the McKinsey Global Survey published this year found that nearly three-quarters of AI high performers have fundamentally redesigned their workflows, against roughly one-quarter of the rest, while the share of smaller organizations scaling AI agents sat flat at 22%. The gap between the two groups is not spend, and it is not model access. It is redesign, and redesign is cheapest before the habits set.

The first 30 days: Write down how the work actually happens

Choose one process that touches revenue directly, such as quote to cash, customer onboarding or returns, and resist the urge to choose three at once. Sit with the people who run it and have them narrate the real path, including the spreadsheet nobody admits to, the approval stuck in one inbox and the exception handled from memory, because the documented process and the one that actually runs are rarely the same document.

Then mark every step as either production or judgment. Production is the drafting, gathering, comparing and summarizing that a model can increasingly perform; judgment is the deciding, prioritizing and taking of responsibility that a human must own. By day 30, you should hold a one-page map a new hire could follow on their first morning, and if a new hire can follow it, so can a model. A process nobody can describe is a process no model can run and no auditor can defend.

Days 31 to 60: Take ownership of your data before it owns you

With the map in hand, trace where the information for each step lives, and expect to find it scattered across three tools, several inboxes and one personal drive. For every field that matters — meaning customer, product, price, status and date — name a single owner and agree on a single definition, because enterprises I work with across the Americas, Europe, Australasia and Japan are spending fortunes to rediscover what counts as an active customer, a question you can settle in a single afternoon.

Then check the exits. Open every tool you pay for and confirm that your data can leave it, in full, in a usable format, on your schedule — and if it cannot, that is the first renewal to renegotiate. Data you cannot export is data you are renting, and a company that rents its own context is not AI-native, however many models it subscribes to.

Days 61 to 90: Redesign who decides and what gets measured

Return to the judgment steps on your map and give each one a name, a definition of what a good outcome looks like and a clear rule for when a human reviews before anything reaches a customer. Then look hard at the approvals that remain, because most approval chains are information poverty in disguise, and once last month’s data is visible to everyone, many of them survive only out of habit.

Finally, retire the metrics that measure the tool and install the ones that measure the business. Baseline the cycle time, cost to serve and customer turnaround of your chosen process on day 61, measure again on day 90, and let the difference, rather than the number of licenses, tell you whether anything changed. In my experience, the first fully redesigned process returns more than the first 10 pilots combined, because a pilot proves that a model works, and a redesign proves that the company does.

What to do on day 91

Three moves follow. First, run the same quarter on the next process, because the method compounds and the second map takes half the time. Second, only now buy tools, since you can finally specify what a tool must do and measure what it did. Third, make the habit a condition of growth, so every new hire inherits a map, and every new vendor passes the export test before a contract is signed.

In August, I offered a test: If every model disappeared on Monday morning, would your business notice? Here is the companion test once you have run this quarter: If you hired 10 people on Monday morning, would they know by Tuesday how the work happens? The companies spending billions are buying back the quarter you still have, and the only transformation budget it requires is the discipline to spend it.

When I wrote about the difference between using AI and being AI-native, the most frequent response from executives was a polite objection: the distinction is real, but redesigning how work happens is a luxury reserved for companies with transformation budgets.

I spend my working life inside those budgets, and most of what they buy is the expensive undoing of habits that formed when the company was small. A founder has nothing to undo yet, which is why the quarter ahead is worth more than the three-year program a large enterprise will fund.

Here is the plan I would run if I were building a company today with no budget beyond my own calendar. In 90 days, with no new software and no outside help, you can do the three things that separate an AI-native business from one that merely uses AI: Write down how the work actually happens, take ownership of your data, and redesign who decides and what gets measured.

After more than two decades of working with independent contractors, I still believe they’re one of the best ways to run a flexible small business. But I’ve also learned that they’re not nearly as cheap, simple or risk-free as many business owners assume.

There are plenty of advantages. I can hire contractors for specific projects without making a long-term employment commitment. I don’t have to provide employee benefits, paid vacation or other traditional employment perks. I can negotiate project rates, define deliverables and avoid worrying about keeping someone busy when the work dries up. Contractors generally manage their own schedules, tools and methods.

It can be a flexible and cost-effective model. But it’s not all rosy.

Here are seven things I’ve learned about working with independent contractors — and what every business owner should consider before building a business around them.

1. Weigh the savings against the costs

When you hire a contractor instead of an employee, you may save money on payroll taxes, benefits and other employment-related expenses. But contractors have their own business expenses, and those costs have to be covered somehow. That’s why their hourly rates are often higher than what you’d pay an employee doing comparable work.

Their rates can also change as market conditions shift, making long-term costs less predictable.

This may still be a financially sound decision for your company, but I recommend projecting the total cost of hiring a contractor versus an employee for every position you consider. Don’t assume you’re saving money just because you’re not running payroll.

2. Invest in compliance

Independent contractors are independent business owners, freelancers and professionals who provide services to other businesses. When you work with them, you need to understand and comply with federal, state and local tax and labor laws.

The distinction between an employee and an independent contractor generally comes down to the nature of the working relationship, including how much control the company exercises over the worker. Factors can include how the work is performed, who provides the tools and equipment, how the worker is paid and whether they operate an independent business.

I generally don’t have the same payroll tax, benefit and wage-and-hour obligations associated with employees — assuming the worker is properly classified as an independent contractor.

I have written agreements with all my contractors. These agreements document the scope of work, payment terms, deliverables and expectations. But a contract alone doesn’t determine someone’s legal classification. Government agencies look at the actual working relationship, not just what the agreement says.

Tax reporting requirements also apply. Depending on the circumstances, you may need to issue Form 1099-NEC to report payments to contractors.

Run these relationships by your accountant and attorney to make sure you’re compliant. Misclassifying an employee as an independent contractor can result in penalties, back taxes and liability for unpaid benefits and wages.

3. Prepare for a changing regulatory landscape

The rules governing independent contractors aren’t necessarily permanent. Federal and state governments have different approaches to worker classification, and regulations can change with new administrations, court decisions and legislative priorities.

Some regulatory changes make it harder for businesses to classify workers as independent contractors, while others give employers more flexibility. These debates often center on worker protections, benefits and the degree of independence a worker actually has.

The takeaway for business owners is simple: Don’t assume today’s rules will remain unchanged. Pay attention to developments in the jurisdictions where you operate, and periodically review your contractor relationships with your legal and accounting advisers.

4. Always have backups

Because independent contractors are independent, they’re free to follow the money wherever it takes them. They can take on other clients, accept new projects or move on when a better opportunity comes along.

Many of my contractors serve multiple clients, which I actually encourage. It reinforces the independent nature of the relationship and allows them to maintain their own businesses.

But contractors come and go. Some are more entrepreneurial, restless or focused on short-term opportunities than others. That’s why I’ve built relationships with multiple contractors, including some who compete with one another.

This gives me options when someone becomes unavailable, misses a deadline or doesn’t deliver. It also means I’m not dependent on one person to keep an important part of my business running.

Just remember: Finding good people isn’t easy. Building a reliable network of contractors takes time, and you need to invest in those relationships before you need them.

5. Don’t confuse ‘independent’ with ‘expert’

I’ve also learned that hiring an independent contractor who presents themselves as an expert doesn’t guarantee that they actually have the experience or skills you need.

Anyone can hang out a shingle and call themselves an expert. I’ve worked with so-called professionals who were hired to perform specific jobs but misrepresented their experience and capabilities.

When you hire an employee, there’s often a formal vetting process. You review resumes, conduct interviews, check references and involve other people in the decision.

Hiring a capable contractor requires the same level of due diligence. Ask for work samples, speak with previous clients, check references and clearly define expectations before signing an agreement.

Don’t assume someone knows what they’re doing just because they have a website, a business name or an impressive title. You still need to do your homework.

6. Your customers may not be thrilled

There’s a difference between the relationship a manager has with an employee and the relationship with an outside contractor. Employees generally work within your organization, while contractors maintain their own businesses and client relationships.

My customers understand this, but sometimes I have to explain that the people I’m sending to their projects aren’t my employees. That can raise an eyebrow.

There’s a perception that employees are more dedicated, accountable and easier to manage than outside contractors. Customers may reasonably believe I have less influence over a contractor servicing them than someone on my payroll. They’re not necessarily wrong.

You can’t hide the relationship, and you shouldn’t try to. Customers aren’t necessarily bothered by contractors. They’re bothered by uncertainty over who’s accountable when something goes wrong.

You need to be prepared to explain how you manage quality, communicate expectations and remain responsible for the work being delivered. The customer is hiring your business, and you need to stand behind the results.

7. Your employees may not be thrilled

Using too many independent contractors can also affect internal relationships and company culture.

Employees may resent the flexibility contractors enjoy or question why certain responsibilities are outsourced instead of handled internally. They may also wonder whether their own contributions are valued if the company regularly turns to outside professionals.

Contractors can become part of a team, but they aren’t employees. How you manage those relationships matters. There are also practical considerations involving confidential information, company data and access to internal systems. Make sure contractors have appropriate agreements and access controls in place to protect your business.

Hiring a contractor for a short-term project is one thing. Relying on contractors for essential, ongoing responsibilities is another. Think carefully about how those decisions affect morale, accountability and the culture you’re trying to build.

Independent contractors can be a great business model — with the right expectations

I don’t want to discourage business owners from using independent contractors. After more than two decades, I still rely on them, which should tell you something.

But it’s important to understand the trade-offs. Contractors can offer specialized expertise, flexibility and defined deliverables without the long-term commitment of traditional employment. They can also introduce uncertainty around availability, costs, compliance and continuity.

My advice is to use contractors when you need specialized skills, project-based support and flexibility. Hire employees when you need consistency, direct oversight, institutional knowledge and long-term commitment. The right mix can help you build a more flexible and efficient business. Just don’t assume that outsourcing the work means outsourcing the responsibility.

After more than two decades of working with independent contractors, I still believe they’re one of the best ways to run a flexible small business. But I’ve also learned that they’re not nearly as cheap, simple or risk-free as many business owners assume.

There are plenty of advantages. I can hire contractors for specific projects without making a long-term employment commitment. I don’t have to provide employee benefits, paid vacation or other traditional employment perks. I can negotiate project rates, define deliverables and avoid worrying about keeping someone busy when the work dries up. Contractors generally manage their own schedules, tools and methods.

It can be a flexible and cost-effective model. But it’s not all rosy.

The safest-looking marketing plan in the room is usually the one most likely to keep you invisible. When you copy the channels, the messaging and the metrics that already work for the category leader, you compete on terms that favor whoever has the bigger budget and the longer head start. That feels like prudence. It is actually the slowest and most expensive way to stay a follower.

Safe feels responsible because failure is easy to defend when you followed the same plan as everyone else. Nobody gets second-guessed for matching the industry norm. That comfort is exactly the problem, because a plan built to avoid blame is not built to win, and the market rewards the brands willing to be wrong in public before they are proven right.

I learned this early. In 2013, I argued that mobile apps needed a strategy of their own rather than a shrunken version of web marketing, back when that sounded like a distraction. The people who moved before the consensus did not have better tools than everyone else. They simply refused to wait for permission and had already taken ownership of the space by the time the cautious crowd arrived.

The safe playbook keeps you invisible

Best practices earn their name because everyone already uses them. By the time a tactic is safe enough to carry that label, it is crowded and drained of any edge it once held. You can run it flawlessly and still finish exactly where you started, one more voice repeating the same message in the same place as your competitors.

The same trap shows up in how you measure success. Chasing the impressions, followers and engagement numbers every rival reports is the most crowded play in marketing, because those figures are easy to hit and easy to ignore. They make a quarter look healthy while the business underneath them sits still.

That ground is moving faster than the safe playbook admits. A Pew Research Center study of nearly 69,000 searches found that when an AI summary sits atop Google results, users click a traditional link in only 8% of visits, down from 15% when no summary appears. Ranking a page and waiting for the click is losing its footing, and most brands are still optimizing for rules that have already changed.

The calculated move rewards discipline

Bold does not mean reckless. What builds leaders is an asymmetric wager, where the downside is small and survivable, and the upside is owning territory no rival has claimed. You are not gambling the company. You are spending a measured slice of budget and attention on a shift you can already see forming, and planting yourself where it lands before the crowd arrives.

The highest-return version refuses to fight inside a crowded category at all. Instead of scrapping for a sliver of space the leader already defined, you reframe the problem so you become the obvious answer to a question nobody else is asking. Think of the companies that stopped selling a slightly better version of an existing product and instead named a new category they could own outright. They looked risky right up until they looked inevitable.

You can pressure-test the move in a single meeting. Ask what happens if it fails and whether the honest answer is a bruise or a catastrophe. Then ask what happens if it works and whether the payoff is a marginal gain or a foothold nobody can take from you. When failure is survivable and success is defining, hesitation becomes the expensive choice.

AI answers reward the brands that move first

The clearest version of this decision sits in front of every marketer right now. AI systems are becoming the layer between your customer and the answer, and the brands that appear inside those answers are the ones deciding today to be there. Waiting until the behavior is undeniable means arriving after the winners are already chosen.

Winning that visibility depends less on budget than on being the clearest and most credible source on the questions you want to own. When an AI system builds an answer, it pulls from information it can trust and quote, so the work is making your expertise easy to find and hard to leave out. That legwork is fundamentals executed better than the competition, aimed at a channel most of your rivals are still ignoring.

In practice, that means publishing direct answers to the questions your customers actually ask, in language a machine can lift without guessing at your meaning. It means keeping your pages clean enough that the facts are easy to extract and quote. It means earning mentions on the outside sources these systems already trust, so when they build an answer, yours is the evidence within reach. That is unglamorous work, and it is exactly why most of your competitors will skip it until the advantage is gone.

Playing it safe shields you from the danger you can see and hands you the one you cannot, the slow erosion of being easy to overlook. The move that feels too bold today is often the only thing that keeps you relevant tomorrow. The real threat was never the leap. It was standing still while the ground moved.

The safest-looking marketing plan in the room is usually the one most likely to keep you invisible. When you copy the channels, the messaging and the metrics that already work for the category leader, you compete on terms that favor whoever has the bigger budget and the longer head start. That feels like prudence. It is actually the slowest and most expensive way to stay a follower.

Safe feels responsible because failure is easy to defend when you followed the same plan as everyone else. Nobody gets second-guessed for matching the industry norm. That comfort is exactly the problem, because a plan built to avoid blame is not built to win, and the market rewards the brands willing to be wrong in public before they are proven right.

I learned this early. In 2013, I argued that mobile apps needed a strategy of their own rather than a shrunken version of web marketing, back when that sounded like a distraction. The people who moved before the consensus did not have better tools than everyone else. They simply refused to wait for permission and had already taken ownership of the space by the time the cautious crowd arrived.

Real estate might produce more marketing per transaction than almost any other professional services industry on earth. Professional photography, drone footage, property films, social reels, brochures, digital advertising, portal listings, email campaigns. A single home sale can generate more content than some companies produce in a quarter. And somehow, most of it sounds exactly the same.

That contradiction is worth sitting with. Because the instinct when marketing isn’t working is almost always to produce more of it. Better cameras. Bigger budgets. More platforms. Higher production value. Real estate has been running that experiment for years, and the result is a market where everything looks increasingly polished and increasingly identical.

Production became a commodity

Not long ago, professional photography was a genuine differentiator in real estate marketing. Most agents were shooting listings on a phone or hiring whoever was cheapest. The agent who showed up with a real photographer was doing something visibly different. That gap closed fast.

Now AI is closing the remaining gaps even faster. Listing descriptions that once took time to write get generated in seconds. Virtual staging that required a designer now takes minutes. Video editing tools that demanded technical skill are increasingly automated. The production floor for every agent, every brokerage, every proptech startup keeps rising.

Here’s the problem with a rising floor. When everyone’s production quality improves simultaneously, production quality stops differentiating anything. Better cameras didn’t solve real estate marketing. They created better-looking sameness. And AI is about to make mediocre content infinitely easier to produce at scale, which means the volume of indistinguishable marketing is going to increase dramatically before anyone figures out that more isn’t the answer.

This isn’t just a real estate problem. It’s happening across every industry that produces content. Design tools democratized. Video became accessible. Writing assistance arrived. The production barrier dropped everywhere. What used to be scarce, the ability to make something that looked and sounded professional, became abundant. The scarcity moved somewhere else entirely.

Better-looking sameness is still sameness

Walk through luxury real estate marketing for an hour and a specific vocabulary emerges. Stunning. Exclusive. One-of-a-kind. White-glove. Market leader. Exceptional. Timeless. These words appear so consistently across so many properties, agents and brokerages that they’ve stopped communicating anything. They’re filler. Placeholder language that signals luxury without describing it, claims distinction without demonstrating it and tells the audience essentially nothing about why this particular property or this particular professional is worth paying attention to.

Agent marketing has its own version. Top producer. Local expert. Client first. Results driven. These phrases are so universal that a consumer could copy and paste them between dozens of competing agent websites without anyone noticing. They describe an aspiration, not a reality. They make no claim that a competitor couldn’t make with identical credibility the same afternoon.

Proptech marketing runs the same pattern. Seamless. Transparent. Frictionless. Innovative. Reimagining. Disrupting. The vocabulary of disruption has become so widespread that it now signals nothing about actual disruption. Every company claims to be solving the same friction. Almost none of them tell you what specifically they understand about human behavior that nobody else has figured out yet.

If your story only gets interesting after someone learns the price, you probably don’t have much of a story.

Finding what’s actually worth saying

The question most marketers ask is: What should we post? The question that actually matters is: What do we have that’s genuinely worth saying? Those questions produce different answers, and the gap between them is where most marketing fails.

At the property level, stories rarely live in the obvious places. Price is not a story. Square footage is not a story. Photographs of a great kitchen are not a story. Stories live in the things that made a property what it is. An architect who designed a home around how morning light moves through a specific valley at a specific time of year. A restoration that brought back materials the original builder sourced from a place that no longer exists. A working ranch that has passed through the same family for three generations and carries a particular relationship to the land that no newly built property can replicate. These things are specific. Specific is the opposite of forgettable.

At the professional level, the story underneath the obvious claims is almost always more interesting than the claims themselves. Not a top producer, but the agent who noticed a decade ago that a specific type of buyer was quietly moving into a region nobody was paying attention to and spent years learning that market before it became obvious. Not a local expert, but the broker who walked away from a larger firm to focus exclusively on a property type most of her competitors couldn’t competently sell. That kind of specificity is earned. Competitors can claim to be local experts tomorrow. They can’t claim ten years of transactions in a niche they didn’t bother to understand.

At the company level, the story worth telling is almost never about features. It’s about the assumption that turned out to be wrong, the behavior that changed, the customer experience that should have worked differently and didn’t. Why does this company need to exist right now rather than five years ago? What did the founders see that others were explaining away? Those are interesting questions. Feature lists are not.

The scarcity shifted

For most of business history, the ability to produce something polished was itself a competitive advantage. Small companies couldn’t afford it. Individual professionals couldn’t access it. The production barrier kept a lot of people out.

That barrier is gone. Anyone can produce something that looks and sounds professional. The tools exist, the cost has collapsed and AI is accelerating the trend in ways that will make the current volume of mediocre content look modest by comparison.

What hasn’t been automated is having something genuinely worth saying. A perspective that comes from actual experience rather than market research. A story that could only be told by this company, this agent, this property. A claim specific enough that a competitor couldn’t make it without lying.

Real estate doesn’t have a content shortage. It has a story shortage. And the response most of the industry is reaching for, more content, better production, more platforms, more posting, is solving a problem that stopped being the real problem a while ago.

The companies that figure that out will stop asking how to make more marketing and start asking whether they have anything worth marketing in the first place. That’s an uncomfortable question. It’s also the right one.

Real estate might produce more marketing per transaction than almost any other professional services industry on earth. Professional photography, drone footage, property films, social reels, brochures, digital advertising, portal listings, email campaigns. A single home sale can generate more content than some companies produce in a quarter. And somehow, most of it sounds exactly the same.

That contradiction is worth sitting with. Because the instinct when marketing isn’t working is almost always to produce more of it. Better cameras. Bigger budgets. More platforms. Higher production value. Real estate has been running that experiment for years, and the result is a market where everything looks increasingly polished and increasingly identical.

Production became a commodity

Not long ago, professional photography was a genuine differentiator in real estate marketing. Most agents were shooting listings on a phone or hiring whoever was cheapest. The agent who showed up with a real photographer was doing something visibly different. That gap closed fast.