The Future of Business: Using AI to Create Bespoke Software

Every business has them: the spreadsheet that keeps an entire department running, the report someone spends hours assembling, the customer request copied manually between three systems. These workarounds often persist because fixing them has seemed too expensive or too complicated.

AI is changing that calculation.

Advances in AI-assisted development are creating new opportunities to build software around the way a business operates. For startups, mid-market companies, and enterprise departments, bespoke software is becoming a more practical option for solving problems that once sat indefinitely on the backlog.

Shorter development cycles can make it affordable to build tools for recurring problems, such as manual data entry or time-consuming reporting. The value of those tools depends on how much they improve the work employees do.

A new equation for custom software

For years, companies faced a familiar tradeoff. They could buy an existing platform and adapt their processes to its limitations, or invest in custom software with a substantial budget and a long delivery timeline. Many settled for a patchwork of subscriptions, spreadsheets, and manual processes.

AI is widening the range of projects worth considering.

Agentic coding tools such as Claude Code can carry out sequences of development tasks, helping teams move from requirements to working software. In an analysis of 500,000 coding interactions, Anthropic classified 79% of Claude Code conversations as automation, illustrating how developers are delegating work to these tools. That measures usage patterns rather than delivery speed, but it shows a meaningful shift in how software gets built. Anthropic’s research on AI and software development.

There is also evidence of measurable productivity gains. Across three randomized field experiments involving 4,867 developers, researchers found that access to an AI coding assistant increased completed tasks by approximately 26% in the combined results. Outcomes varied across the experiments, so this is evidence of potential rather than a guaranteed improvement for every project. Study published in Management Science.

For business leaders, the implication is straightforward: when development requires less effort, more targeted software investments can become economically viable.

A startup might build a customer onboarding workflow tailored to its service. A mid-market distributor might connect inventory, quoting, and order management. An enterprise finance team might automate the collection and reconciliation of information from several internal systems.

A focused application can address a costly gap between existing systems while allowing the business to continue using its current platforms.

Using AI in Development and Daily Operations

The strongest opportunities combine two uses of AI: using it to help build software, and embedding it into the software employees use.

Consider a team processing incoming customer requests. A bespoke application could collect requests, retrieve relevant account information, classify the issue, and prepare a response. Routine cases could follow an automated workflow, while exceptions go to an employee with the necessary context already assembled.

In this workflow, automation handles clearly defined tasks with predictable outcomes, while AI assistance helps employees with work that requires judgment, relationships, or accountability. Each step needs an appropriate level of human involvement.

Research offers a concrete example of augmentation’s potential. A study of 5,172 customer-support agents found that access to AI assistance increased issues resolved per hour by 15% on average, with benefits varying across workers. The result demonstrates how AI integrated into an everyday workflow can improve performance. Generative AI at Work, published in The Quarterly Journal of Economics.

Turning time saved into business value

Enterprise departments can be especially attractive places to apply this approach because small improvements can accumulate across large volumes of work.

As a simple illustration, saving ten minutes on a task performed 6,000 times each month would release 1,000 hours of capacity. Whether that becomes a financial return depends on implementation costs and how the business uses the recovered time. It could support faster customer service, greater throughput, or more attention to complex cases.

Smaller companies can benefit for a different reason: a focused improvement may remove a bottleneck that is limiting growth. Reducing administrative work can allow an existing team to serve more customers without adding the same amount of operational overhead.

Start with the workflow

The business case should begin with that bottleneck.

Where are employees repeatedly moving information between systems? Which approvals stall because someone must gather context manually? Which customer interactions take longer than they should? These questions reveal practical opportunities for custom software.

Development speed alone, however, does not guarantee a successful investment. Research on AI coding tools remains mixed, and METR’s follow-up work emphasizes how difficult it is to measure productivity gains reliably as tools and working practices evolve. METR’s developer productivity research update.

Experienced engineering still matters. The application must fit the workflow, connect reliably to existing systems, protect business information, and remain maintainable as requirements change. Those decisions determine whether a promising prototype becomes dependable business software.

A sound starting point is one valuable workflow with a measurable baseline. Establish how long it takes today, where errors occur, and what successful improvement would look like. Build a focused solution, test it with the people who will use it, and expand when the results justify the investment.

AI gives businesses more freedom to create software suited to their operations. Processes that once seemed too specialized to support with technology now deserve another look.

Our teams have spent more than 15 years building custom software for businesses ranging from startups to enterprises. We bring that experience to identifying useful automation opportunities and developing solutions that fit the way your business works.