Billionaire Mark Cuban Says This Software Will Be 'The Next Great AI Application'

The employment market continues to be a flashpoint for markets as the Federal Reserve weighs a potential policy change, with July payrolls data due out this Friday, Aug. 7. 

Ahead of this key economic report, billionaire businessman and widely followed entrepreneur Mark Cuban argued on social media that “the next great AI application” for enterprises won’t be agents, drones, robots, or anything else that’s dominating the conversation this week.

Instead, it’s going to be a job simulator.

What Mark Cuban Said About Job Simulators

In a July 24 X post, Cuban wrote:

“The next great AI application, driven by open source, or open weights, will be a job simulator.”

He continued, “Much like race car drivers and pilots have software that is continually updated to enable them to experience as many scenarios as possible, trying to replicate what could happen IRL, smart companies will have their employees and stakeholders with the most domain knowledge create the simulator that takes them through every possible situation they could face and helps prepare them.”

His prediction arrives at a moment when the labor market is experiencing measurable, if still modest, disruption from artificial intelligence (AI). 

Morgan Stanley economists have found that AI is adding approximately 15 basis points to the overall unemployment rate, up from 10 basis points in late 2025, with the heaviest displacement concentrated among workers aged 22 to 27. 

Workers in highly exposed occupations are experiencing longer unemployment spells between jobs and reporting significant changes in the nature of their work activities.

Bridging the AI Gap for Employees

Cuban's thesis aligns with growing evidence that both employers and workers are struggling to bridge the gap between AI's theoretical promise and its practical workplace impact. 

A survey from Adaptavist found that nearly two-thirds of employees frequently reminisce about the pre-AI work environment, while 42% say they spend more time reviewing and verifying AI-generated content than they save using it. 

The GoTo and Workplace Intelligence study similarly found that although employees save over two hours daily with AI tools, 60% feel pressured to demonstrate AI-driven productivity, and 65% say their employers are failing to equip them with needed skills. A job simulator could address this preparation deficit by allowing workers to practice navigating AI-augmented roles before entering them.

Or, as Cuban explained: “How employees gain experience in a future AI world is going to be far different from today. Employees won’t have as many touch points in the company to gain knowledge and experience from. That’s where judgement has historically come from.”

Where Applied AI Intersects With Physical AI

The concept resonates with broader industry trends showing that physical AI and simulation are emerging as the next frontier of value creation. 

Venture funding for robotics reached nearly $14 billion in 2025, a 70% increase year over year, and the humanoid robot market is projected to grow from $5.41 billion in 2026 to over $50 billion by 2035. 

Companies like Tesla (TSLA) are scaling Optimus production targets tenfold to 10 million units annually, while Chinese robotics firms are moving from prototype delivery to tens of thousands of units in mass production. 

A job simulator would sit at the intersection of these trends, using AI to model real-world work scenarios before expensive physical deployment.

What This Means for AI Investors

From an investment perspective, the idea fits within the applied AI layer that analysts consider the next major growth opportunity, distinct from infrastructure and foundation models. 

The current earnings season has demonstrated that AI spending is producing real returns, with S&P 500 ($SPX) earnings growth running at approximately 47% year over year, though significant portions of headline profits at companies like Alphabet (GOOG) (GOOGL) and Amazon (AMZN) stem from unrealized equity gains rather than operating cash flow. 

Cuban's prediction implicitly acknowledges that the market needs practical, revenue-generating AI applications to justify the hundreds of billions being invested in infrastructure – and a tool that helps workers adapt to AI-transformed roles would address one of the most pressing pain points in the economy today.

This article was created with the support of automated content tools from our partners at Sigma.AI. Together, our financial data and AI solutions help us to deliver more informed market headline analysis to readers faster than ever.