Build vs. buy in the age of AI: Are we underestimating the true cost of building?

AI has made it easier than ever to build your own software. But just because you can build something, does that mean you should?

For Revenue Operations (RevOps) teams, the build vs. buy debate is nothing new. What’s changed is how quickly teams can now develop their own solutions, thanks to advances in AI and the rise of vibe coding.

With AI coding assistants, low-code platforms and automation tools, it’s now possible to develop applications in days that would previously have taken months. RevOps teams can build custom dashboards, automate workflows, connect data sources and create internal tools without necessarily relying on dedicated engineering resources.

It’s easy to see the appeal. Why invest in another software platform when you can potentially build something tailored to your organisation’s exact requirements?

However, while AI has significantly reduced the barriers to building software, it hasn’t eliminated the complexity of maintaining it. As more organisations experiment with developing their own tools, there’s an important question worth asking: are we comparing the cost of buying software with the cost of building it, or just the cost of getting a prototype up and running?

How AI is changing the build vs. buy debate

Traditionally, building software internally required significant investment in development resources, technical expertise and time. For many RevOps teams, that made purchasing an established platform the more practical option.

AI is changing that equation. Today, teams can experiment with custom applications, develop proofs of concept and automate processes much faster and at a fraction of the initial development effort.

For organisations with specific requirements that aren’t adequately addressed by existing software, this creates valuable opportunities. A team might build an internal reporting dashboard, automate an approval process or develop a lightweight tool that connects information across several systems.

But there’s a difference between developing a solution that works today and creating something the organisation can depend on long term.

A tool initially designed for a handful of users might eventually need to support an entire sales organisation. What begins as a relatively simple integration between two systems could develop into a complex network of dependencies involving CRM, finance, HR and other business-critical platforms.

As the application becomes more important to the business, the requirements around reliability, security, governance and ongoing development grow alongside it. These are the areas where the true cost of building often starts to emerge.

The hidden costs of building software internally

One of the biggest challenges with the build vs. buy decision is ensuring that both options are being evaluated on the same basis. When assessing an existing platform, the subscription cost is usually clear. When considering an internal build, however, the initial development effort can be much easier to estimate than the ongoing resources required to support it.

There are several costs that organisations need to factor into the decision.

Maintenance and ongoing development

Getting an application into production is only the beginning. Business requirements change, APIs are updated, integrations break and new functionality becomes necessary. Internal tools need regular testing, updates and support to remain reliable.

This also raises questions about ownership. Who is responsible for maintaining the application after it’s launched? Does that person have the capacity to support it alongside their existing responsibilities? And what happens if they leave the organisation?

For RevOps teams, where resources are often already stretched across planning, forecasting, reporting and operational support, maintaining custom software can create a significant additional workload.

Security, compliance and governance

As internally developed applications become more sophisticated, they often require access to increasingly sensitive business information. Sales performance, customer records, financial data and employee compensation are just some of the datasets that RevOps tools may need to handle.

Managing this information securely requires appropriate access controls, testing, monitoring and governance processes. Organisations also need to consider how these applications fit into existing security and compliance requirements.

AI can accelerate software development, but it doesn’t remove these responsibilities. In some cases, the speed at which tools can now be created makes effective governance even more important.

Data integration and reliability

Integrating business systems is another area where complexity can be underestimated. Connecting an application to Salesforce or another platform may be relatively straightforward at first, but maintaining accurate, consistent information across multiple systems is considerably more challenging.

Take sales capacity planning as an example. An organisation might need to combine CRM data with historical sales performance, hiring plans, ramp times, quota allocations and employee costs. Each source has its own structure, definitions and update cycles, and changes to any one of them can affect the reliability of the overall solution.

The challenge isn’t simply accessing the data. It’s ensuring that the information remains accurate, consistent and usable as the business evolves.

The opportunity cost of internal resources

Beyond the direct financial investment, organisations also need to consider what their teams could be doing instead.

Every hour spent developing, troubleshooting or maintaining an internal application is time that could potentially be allocated to other priorities. For RevOps leaders, this might mean less time spent improving sales productivity, identifying growth opportunities or supporting strategic planning.

This doesn’t automatically make building the wrong decision. However, the value of an internal solution needs to justify not only its direct costs but also the resources being diverted from other activities.

Build vs. buy: What does the first year actually cost?

To illustrate how these costs can add up, let’s consider a hypothetical 50-person sales organisation evaluating whether to build its own sales planning platform using AI-assisted development or purchase an existing solution such as Lative.

While AI may significantly reduce the time required to create an initial prototype, getting that application ready for production and maintaining it over time involves considerably more work.

In this scenario, the estimated first-year cost of building internally ranges from $240,000 to $605,000, compared with a $25,000 annual subscription for Lative. That represents a potential difference of $215,000 to $580,000, with the internal build costing approximately 10 to 24 times more.

Of course, these figures aren’t representative of every software project. A simple internal application could cost substantially less to develop and maintain, while a more complex commercial implementation might involve additional expenses for onboarding, integrations or customisation.

What the comparison highlights is the importance of looking beyond the initial development cost. A meaningful build vs. buy assessment should consider the total cost of ownership over several years, including the investment required to keep the solution secure, reliable and aligned with changing business requirements.

When does building make sense?

Despite the potential challenges, there are situations where building internally is the right approach. AI has opened up opportunities for RevOps teams to solve problems that might previously have been too expensive or time-consuming to address.

Building can be particularly valuable when an organisation has a highly specific requirement that existing platforms don’t adequately support. It may also make sense for relatively simple applications, internal workflows or experimental projects where the risk and ongoing maintenance requirements are limited.

For example, a RevOps team might develop a custom workflow that automates a particular approval process or creates a specialised report using information already available within its existing technology stack. If the solution is straightforward, well-defined and unlikely to require significant ongoing development, building it internally could be more efficient than purchasing another application.

The availability of internal technical expertise is also an important consideration. Organisations with established engineering resources, clear ownership and the capacity to maintain custom applications are in a stronger position to manage the long-term responsibilities that come with building.

Ultimately, the decision comes down to whether the flexibility and value of a custom solution outweigh the investment required to develop and support it.

When does buying make more sense?

As the complexity and business importance of a solution increase, the case for purchasing an established platform often becomes stronger.

Sales planning is a good example of where the complexity of building internally can be underestimated. What starts as a relatively straightforward capacity model can quickly become much more sophisticated as the organisation grows.

Revenue teams need to account for historical productivity, ramp times, hiring plans, attrition, quota allocations and the financial implications of different scenarios. They also need to connect those plans with actual performance, understand whether they’re on track and identify where adjustments may be required throughout the year.

Supporting this internally involves more than building a calculation model or dashboard. It requires reliable data integrations, consistent business logic, scenario modelling, ongoing development and the ability to adapt as business requirements change.

This is the challenge Lative was built to solve.

Lative is an AI-native sales planning platform that brings productivity insights, capacity planning, scenario modelling and execution tracking together in one place. Rather than developing and maintaining their own planning infrastructure, RevOps teams can use Lative to understand their sales capacity, evaluate different plans and track performance against their targets.

The value isn’t simply avoiding the technical complexity of building software. It’s enabling RevOps teams to spend more time analysing their business, identifying opportunities and making decisions that improve sales efficiency and profitability.

For organisations where sales planning is business-critical but developing proprietary planning software isn’t a competitive advantage, purchasing a purpose-built platform can offer a more efficient path.

Does it have to be build or buy?

One of the most interesting developments in the build vs. buy debate is that the two approaches are no longer necessarily mutually exclusive.

As AI makes custom development more accessible, organisations have greater flexibility to combine established platforms with internally developed capabilities.

A RevOps team might purchase a purpose-built platform such as Lative to manage its core sales planning processes, while using AI and automation to develop additional workflows, reports or integrations tailored to its organisation.

This approach allows teams to benefit from the reliability and functionality of established software while retaining the flexibility to innovate where it adds value.

Rather than trying to build everything internally or relying entirely on off-the-shelf solutions, the focus shifts to identifying which capabilities are worth owning and which are better delivered through a specialist provider.

Five questions RevOps leaders should ask before building or buying

Before committing to either approach, it’s worth evaluating the decision against a few practical questions:

1. What problem are we trying to solve? Is this a genuinely unique business requirement, or does an existing solution already address it effectively?
2. What’s the total cost of ownership? Have we considered development, integrations, security, maintenance and internal resources over the next three to five years?
3. Who will own the solution long term? Do we have the technical expertise, capacity and governance processes needed to maintain it as requirements change?
4. How critical is the application to the business? What are the implications if it becomes unavailable, produces inaccurate information or fails to scale?
5. Where can our team create the most value? Does developing proprietary software offer a meaningful competitive advantage, or would those resources deliver greater returns elsewhere?

These questions help move the discussion beyond what is technically possible and towards what makes the most commercial and operational sense.

The real question isn’t whether you can build it

AI is fundamentally changing how organisations approach software development. For RevOps teams, the ability to create custom tools, experiment with new ideas and automate processes faster presents a significant opportunity.

However, the speed and accessibility of development shouldn’t distract from the responsibilities that come with owning software. Maintenance, security, reliability and scalability remain important considerations, particularly when applications become embedded in business-critical processes.

The build vs. buy debate is no longer simply about whether an organisation has the resources or technical expertise to develop something internally. It’s about understanding where building creates genuine value, where purchasing offers a better return and how the two approaches can complement each other.

Ultimately, the smartest decision isn’t necessarily to build or to buy. It’s knowing where to invest your team’s time and resources to deliver the greatest long-term value.