You’ve probably sat through an AI demo that made everything look easy. A few prompts, a polished response and suddenly your business appears to have an entirely new way to work. Then you return to your inbox, your team’s questions and the same operational headaches you had before.

A logistics employee updating an order, a business managing external collaborators and a founder deciding which tasks to automate all need software that makes their work easier. Building that value takes more than adding an AI feature. It takes understanding the problem, fitting the solution into daily operations and proving the improvement is worth the investment.

That’s where the real work begins. Buying access to AI is straightforward. Figuring out where it belongs in your business takes more thought. For software entrepreneurs, connecting those two moments is where the growth opportunity begins.

Leaders from Queue Associates, Envision IT and Think AI have all explored how technology partners build, adapt and grow their businesses. They are navigating the same question many founders face: How do you turn interest in AI into something customers will use, value and keep buying?

AI’s substantial spending opportunity
A growing market still needs a clear business case. Gartner’s July 2026 forecast projected global software spending would reach $1.468 trillion in 2026, increasing 15.5% year over year. Separately, IDC projected AI infrastructure spending would reach approximately $497 billion in 2026, growing about 56% annually, and surpass $1 trillion in 2029.

Those forecasts describe different markets, but together they illustrate the scale of investment supporting software and AI adoption. Platforms like Microsoft’s Partner Program can help small and medium-sized software development leaders gain a larger share of these markets through access to its cloud, marketplace and AI solutions.

For a founder, the opportunity starts with understanding what customers need that technology to accomplish.

A bigger market gives you more room to compete. A clear business case gives customers a reason to choose you.

Before your next sales conversation, replace a feature-heavy presentation with questions about the customer’s operations. Where does work slow down? Which tasks require repeated manual updates? What would a meaningful improvement look like?

Small workflow improvements
Manish Bhardia, Think AI’s Managing Partner, shared an example from a 300-person logistics company in which approximately 100 employees manually tracked orders and updated customer relationship management records using CultureBanx. Think AI introduced an assistant within Outlook to help summarize tracking information and update the CRM.

The reported improvement was approximately 20 to 30 seconds per task. The customer estimated roughly $1,000 in annual savings per affected employee, or about $100,000 across that group. Those were customer estimates, rather than independently verified financial results.

What makes the example useful is its specificity. There was an identifiable task, a defined group of employees and an improvement the customer could estimate.

“Disconnect is where people are not clear on what we are trying to get out of AI,” Bhardia said.

Custom growth lessons
Peter Carson’s experience offers another growth lesson: Pay attention when different customers keep asking you to solve the same problem. “Once you’ve built the same solution for half a dozen clients, you think, you know what, is there a common pain point here?” he said.

Envision IT’s offerings include Extranet User Manager for external collaboration and Tenant Dashboard for Microsoft 365 management and governance. Carson described the challenge of turning custom solutions into products that are repeatable, supportable and configurable.

That’s a distinction for entrepreneurs who want to move beyond selling project hours. Repeated demand can reveal an opportunity, but the next step is understanding how much of the solution customers actually share.

Review recent engagements and separate common requirements from customer-specific requests. Test whether a standard offering can solve the core problem, then establish how onboarding, configuration and support will work. A product needs a delivery model you can sustain as customers multiply.

Build experience before scaling
Jeffrey Goldstein, Co-Founder and Managing Director of Queue Associates, described internal AI adoption as preparation for serving customers. “The applications that we are recommending and supporting for our customers are the applications that we’re using ourselves,” he said.

For software founders, that creates a learning loop. Your employees encounter implementation challenges, discover useful applications and build experience they can bring into customer engagements.

Goldstein also advocated a gradual rollout: Introduce existing capabilities, help customers understand what they can do, then develop customized agents around clearer business needs.

Justifiable investment
The opportunity lies in connecting software development with customer outcomes. Choose a problem customers recognize, demonstrate an improvement they can measure and make the solution easier to deliver repeatedly.

That gives software development leaders a foundation for growth as AI spending expands. Your next product decision should begin with the work customers need done and end with evidence that your software helps them do it better.