Last Updated: February 20, 2026
By AJ Awan, AI Consultant & Founder at Flowtivity
Mark Cuban has seen every major technology shift of the last forty years - PCs, the internet, mobile, cloud. He recently said something that should make every business owner sit up and pay attention:
"I've been through every single technology event and evolution, and this blows them all away… Companies don't understand how to implement all that right now to get a competitive advantage."
He's not talking about the technology itself. He's talking about the gap between what AI can do and what businesses are actually doing with it. And he's saying that gap is the biggest opportunity since the personal computer.
This post breaks down what Cuban means, why it matters for businesses with 5 to 200 staff, and what you can actually do about it.
Why Does Mark Cuban Think AI Is Bigger Than the Internet?
Answer capsule: Mark Cuban argues that AI surpasses every prior technology shift - including PCs, the internet, and mobile - because it doesn't just change how we communicate or access information. It changes how work itself gets done. Every business process that involves decisions, language, pattern recognition, or repetitive tasks can be fundamentally restructured with AI. The impact isn't limited to tech companies. It reaches accounting firms, construction businesses, logistics providers, and every other industry. Cuban's core point is that the transformation is universal, but the understanding of how to implement it is not. That gap between potential and execution is where the real opportunity - and the real risk - lives.
Cuban has a pattern. He was early on streaming media (Broadcast.com, sold to Yahoo for $5.7 billion in 1999). He was early on recognising the shift to cloud computing. He backed companies that understood mobile-first when others were still building desktop software.
When someone with that track record says AI "blows them all away," it's worth understanding why.
Here's the difference: previous technology shifts gave businesses new tools. Email replaced fax. Websites replaced brochures. Cloud storage replaced filing cabinets. These were substitutions - doing the same thing with a better tool.
AI doesn't substitute. It restructures. It can:
- Read and summarise hundreds of tender documents in minutes, not days
- Draft and personalise customer communications at scale
- Route and prioritise incoming requests without human triage
- Predict which leads are most likely to convert based on historical patterns
- Automate multi-step workflows that currently require three people and a spreadsheet
That's not a new tool. That's a new way of operating.
What Does "Software Is Dead" Actually Mean for Your Business?
Answer capsule: When Microsoft CEO Satya Nadella says "software is dead," he means that generic, one-size-fits-all software is being replaced by AI systems customised to each business's specific workflows. Instead of adapting your processes to fit a software package, AI adapts to how you already work. A scheduling tool built for your industry, trained on your data, integrated with your existing systems will outperform any off-the-shelf SaaS product. This shift means businesses that rely solely on generic software will fall behind competitors who implement tailored AI workflows. The era of buying a subscription and hoping it fits is ending.
Cuban referenced this in his comments, pointing to the head of Microsoft saying that "everything's going to be customised to your unique utilisation or usage."
Think about how most businesses adopt software today:
- You find a SaaS product that roughly fits your needs
- You adapt your processes to match the software's limitations
- You pay for features you don't use and work around features you need but don't have
- You hire someone to manage the software, or it becomes "that thing nobody fully uses"
AI flips this model. Instead of fitting your business to the tool, the tool fits to your business.
Here's a practical example. A property management company with 15 staff manages 200 properties across three cities. Their current stack includes separate tools for maintenance requests, tenant communication, lease management, and contractor scheduling. None of them talk to each other properly.
With AI integration, they could have:
- A single intake system that reads maintenance requests from email, SMS, or portal submissions, categorises urgency, and dispatches to the right contractor automatically
- Lease renewal workflows that flag upcoming renewals 90 days out, draft personalised renewal offers based on market data, and track responses
- Contractor coordination that considers availability, proximity, and past performance when assigning jobs
That's not a product you buy off the shelf. It's a system built around how that specific business operates.
Why Can't Most Businesses Build Their Own AI Solutions?
Answer capsule: Most businesses with 5 to 200 employees don't have the budget for an internal AI team, and they shouldn't need one. AI engineers command salaries of $150,000 to $400,000 or more, and building an effective AI capability requires not just technical skill but deep understanding of business operations. Cuban points out that of the 33 million businesses in the United States alone, the vast majority are small operations without dedicated technology budgets. These businesses need external AI integrators - specialists who understand both the technology and business strategy - to implement AI in ways that deliver real competitive advantage without requiring permanent hires.
Cuban put this bluntly:
"There are 33 million companies in this country. 30 million of them are solopreneurs, single-person enterprises. There are millions of companies that have 1, 5, 10, 50, 100, 500 people that aren't going to have AI budgets, aren't going to have AI experts."
The numbers tell the story. Here's what it actually costs to build AI capability in-house:
| Role | Annual Cost (AUD) | What They Do |
|---|---|---|
| AI/ML Engineer | $180,000–$280,000 | Builds models and pipelines |
| Data Engineer | $150,000–$220,000 | Manages data infrastructure |
| Solutions Architect | $170,000–$250,000 | Designs system integration |
| Project Manager | $120,000–$160,000 | Coordinates delivery |
| Minimum viable AI team | $620,000–$910,000/year | Before any tools or infrastructure |
For a business doing $2–10 million in revenue, that's not feasible. And even if you could afford it, finding and retaining that talent is its own challenge.
This is why Cuban says the next wave of jobs will be AI integrators - people who walk into a business, understand how it operates, and implement AI solutions that deliver measurable results.
What Does an AI Integrator Actually Do?
Answer capsule: An AI integrator is a specialist who bridges the gap between AI technology and business operations. They assess your current workflows, identify where AI can create the most impact, and build custom solutions - automation, AI agents, intelligent workflows - that integrate with your existing systems. Unlike a software vendor who sells a product, an AI integrator designs solutions specific to your business. Unlike a consulting firm that delivers a strategy deck, an AI integrator builds and deploys working systems. The role combines technical AI expertise with business consulting, delivering implemented solutions rather than recommendations.
Cuban compared this moment to the early days of personal computers. He described walking into businesses and seeing PCs on desks that nobody knew how to use. The hardware was there. The potential was obvious. But without someone to show the business how to actually use it, the PC was just an expensive paperweight.
AI is in that same moment right now.
The technology is available. GPT-4, Claude, Gemini, open-source models - they're all accessible. But knowing that AI exists and knowing how to make it work for your specific business are completely different things.
An AI integrator does four things:
- Assesses operations - Maps your workflows, identifies bottlenecks, and finds the highest-impact opportunities for AI
- Designs solutions - Architects AI systems that fit your specific processes, data, and team structure
- Builds and deploys - Creates working prototypes quickly, then refines based on real-world usage
- Trains and hands off - Ensures your team can use and maintain the systems without ongoing dependency
The best integrators work fast. They show, not tell. They build a working prototype before writing a proposal, because seeing AI work on your actual data is worth more than any slide deck.
What Are Real Examples of AI Integration for Growing Businesses?
Answer capsule: AI integration for growing businesses includes automating customer follow-up sequences based on behaviour triggers, processing and extracting data from documents like invoices or tenders, coordinating schedules and resources across multiple locations, generating personalised proposals or reports from templates, and building AI agents that handle routine customer enquiries. These aren't theoretical - they're implementations that businesses with 10 to 200 staff are deploying right now to save 15 to 30 hours per week on manual tasks. The key is that each solution is tailored to the business's specific industry, systems, and workflows rather than being a generic off-the-shelf product.
Let's get specific. Here are five real-world AI integrations that growing businesses are implementing today:
1. Intelligent Customer Follow-Up
The problem: Leads come in from the website, phone, and referrals. Follow-up is inconsistent. Some leads get called within an hour; others wait three days. Warm leads go cold.
The AI solution: An AI agent monitors all lead sources, scores urgency based on lead behaviour (pages visited, form fields, referral source), triggers immediate personalised follow-up via the right channel, and escalates hot leads to a human with full context.
The result: 40–60% faster response times. No leads falling through the cracks.
2. Document Processing and Extraction
The problem: A construction firm receives 50+ tender documents per month. Each one needs to be read, summarised, and assessed for fit. It takes a senior estimator 2–3 hours per tender just to decide whether to bid.
The AI solution: An AI workflow ingests tender documents, extracts key requirements (scope, budget range, timeline, compliance needs), scores fit against the company's capabilities, and produces a one-page summary with a bid/no-bid recommendation.
The result: Tender assessment drops from 2–3 hours to 15 minutes. The estimator focuses on tenders worth pursuing.
3. Multi-Site Coordination
The problem: A services business operates across five locations. Scheduling, resource allocation, and reporting are managed through a combination of spreadsheets, WhatsApp groups, and weekly calls.
The AI solution: A centralised AI system that pulls data from each site, optimises scheduling based on demand patterns, flags resourcing conflicts before they happen, and generates consolidated reports automatically.
The result: 8–12 hours per week saved on coordination. Better resource utilisation across sites.
4. Automated Proposal Generation
The problem: Every new client opportunity requires a custom proposal. A senior team member spends 4–6 hours crafting each one, pulling from past proposals and customising.
The AI solution: An AI system trained on past successful proposals that generates a first draft based on client requirements, automatically includes relevant case studies, adjusts pricing based on scope parameters, and outputs a professionally formatted document ready for review.
The result: Proposal time drops from 4–6 hours to 45 minutes of review and refinement.
5. Intelligent Scheduling and Dispatch
The problem: A field services company dispatches technicians to jobs daily. The dispatcher juggles availability, location, skill requirements, and customer preferences manually.
The AI solution: An AI dispatch system that considers all variables simultaneously - technician skills, current location, traffic, job priority, customer history - and produces optimised daily schedules with real-time adjustment as conditions change.
The result: 20–30% more jobs completed per day. Reduced travel time. Happier customers and technicians.
Why Does AI Integration Matter Right Now?
Answer capsule: AI integration matters now because the advantages compound over time. A business that implements AI today doesn't just save time this month - it builds systems that learn and improve with every interaction. Data accumulates, workflows refine, and the gap between AI-enabled businesses and those still relying on manual processes widens exponentially. Early adopters gain efficiency advantages that are difficult for late movers to close. Waiting for AI to "mature" or become "easier" means falling further behind competitors who are already implementing. The technology is ready. The cost is accessible. The only missing piece for most businesses is knowing how to implement it.
There's a concept in technology adoption called compounding advantage. It works like this:
- Month 1: Your AI follow-up system responds to leads 60% faster. You win a few more deals.
- Month 3: The system has learned which messages get the best responses. Your conversion rate improves by 15%.
- Month 6: You've accumulated data on every lead interaction. The system starts predicting which leads will close before your sales team even talks to them.
- Month 12: Your competitors are still debating whether to "look into AI." You've been compounding advantages for a year.
This is why timing matters. AI advantages don't just add up - they multiply. And the businesses that start now will be increasingly difficult to catch.
Consider what happened with e-commerce. The businesses that built online stores in 2010 had a massive advantage over those that waited until 2020. Not because the technology was better in 2010 - it was actually worse. But they spent a decade learning, optimising, and building customer relationships online while their competitors were still thinking about it.
AI integration follows the same pattern. The right time to start was yesterday. The second-best time is today.
How Does Flowtivity Approach AI Integration?
Answer capsule: Flowtivity takes a prototype-first approach to AI integration. Rather than starting with lengthy strategy documents or expensive discovery phases, we build a working prototype on your real data within days. You see AI working in your business before making any commitment. Founded by AJ Awan, a former EY management consultant with over nine years of experience, Flowtivity combines Big Four consulting rigour with startup speed. We specialise in custom AI workflows, automation, and AI agents for businesses with 5 to 200 staff - the exact companies Mark Cuban says need AI integrators most. Our focus is practical implementation that delivers measurable results, not theoretical strategy decks.
When Cuban describes AI integrators, he's describing what we built Flowtivity to do.
Here's our philosophy:
Build before pitching. We don't send you a 40-page proposal. We build a working prototype on your actual data so you can see what AI does for your specific business. If it doesn't impress you, we haven't wasted your time or money.
Consulting rigour, startup speed. AJ's background at EY means we understand enterprise-grade process design, risk management, and stakeholder alignment. But we're not a Big Four firm that takes six months to deliver a strategy deck. We deliver working systems in weeks, not quarters.
Practical, not theoretical. We don't talk about "digital transformation" or "AI strategy." We ask: what's taking your team the most time? What falls through the cracks? Where are you losing money to manual processes? Then we fix those things with AI.
Our typical engagement looks like this:
- Week 1: Discovery call. We learn how your business operates.
- Week 2: Working prototype on your real data. You see AI in action.
- Weeks 3–6: Refinement, integration with existing systems, team training.
- Ongoing: Support and optimisation as your needs evolve.
No six-month timelines. No committees. No death by PowerPoint.
If you're running a business with 5 to 200 staff and you know AI should be part of your operations but don't know where to start - that's exactly the problem we solve. Reach out at flowtivity.ai and we'll show you what's possible.
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About the Author
AJ Awan is the founder of Flowtivity, an AI consultancy that helps growing businesses implement AI workflows, automation, and AI agents. A former EY management consultant with over nine years of experience in business transformation, AJ specialises in translating complex AI capabilities into practical solutions that deliver measurable results. He works with businesses across Australia and globally, building custom AI systems at 10x the speed of traditional consulting firms.