The Build or Buy Decision: Tech Leaders Answer the Generative AI Conundrum
Integrating generative AI into an organization’s workflow is no simple task.
Beyond the technical complexities, companies must carefully weigh the pros and cons of building their own solutions versus buying pre-built options from the rapidly expanding market.
This build-or-buy decision is fraught with challenges, requiring a deep understanding of the organization’s specific needs, capabilities, and long-term goals.
To help illuminate the key considerations, we turned to a group of prominent tech leaders from the Techronicler community.
We asked them to pinpoint the one factor they believe is paramount in this decision-making process and to elaborate on its significance.
Their answers reveal the multifaceted nature of this choice and provide valuable guidance for organizations grappling with the generative AI revolution.
Read on!
Chetan Honnenahalli - Hubspot
An organization only offers a generative AI solution when the content generated is in the context of the business offering the organization provides.
If an AI solution cannot accommodate this and only works on generally available information, it is not very useful for the organization’s customers and does not offer any incremental value.
Legal Considerations: If an organization choses a gen AI solution that has trained its models on questionable sources and is forced to shut down or pause its operations until its legal issues are addressed, the organization will have to quickly start looking for a different vendor.
This could lead to service disruption and trust erosion with the organization’s customers.
Chetan Honnenahalli
Engineering Lead, Hubspot
Ian Amit - Gomboc AI
The most important factor is to understand what problem they are trying to solve.
It may sound simple, but deciding which TYPE of AI is applicable is more important than deciding on which implementation route to go for.
For example – some problems are better served using deterministic AI (think engineering-focused ones) rather than generative AI.
You’d like the results to be accurate and repeatable rather than statistically close and potentially hallucinatory in nature.
Terry Kasdan - atCommunications
One important factor to consider when deciding whether to build or buy a generative AI solution is how well it aligns with your business’ goals.
If AI is central to your business’ competitive edge, then building a custom solution will offer more control and flexibility to meet unique needs. But if it’s more of a supporting tool, then buying an off-the-shelf option might be quicker and more practical.
It’s also important to think about your long-term plans. Building gives you the freedom to adapt the system as you grow, while buying is great for solving immediate problems without heavy investment.
So start by defining your business’ strategy, and then pick the solution that fits it. You don’t want to spend resources on building something that doesn’t fully meet your needs or maximize impact.
Terry Kasdan
Founder and Creative Director, atCommunications, LLC
Rafael Ulloa - Artin Solutions
When it comes to deciding whether you should custom-build your own AI solutions or purchase a prepackaged one, it comes down to a choice: short term vs long term effects.
It’s relatively easy to integrate AI with various SaaS solutions using automation services such as Zapier or Make and development time will be significantly shorter, but there is a risk: losing efficiency as a project grows in complexity.
Eventually there will be too many moving parts and identifying a point of failure becomes increasingly more difficult.
There is also a risk of inadvertently creating a limitation if an organization has a different way of doing things compared to what are common industry practices.
Building a custom AI solution is likely to take significantly longer but the payoff is in the long run, the solution will be more flexible and will offer a more granular control over how things are run.
Rafael Ulloa
Founder, Artin Solutions
Mehmed Džaferović - FlyRank
When deciding whether to build or buy generative AI solutions, one critical factor is alignment with business needs and goals.
Generative AI isn’t one-size-fits-all; its effectiveness depends on how well it integrates into workflows and solves specific challenges.
Building a custom solution offers unmatched flexibility and ensures the AI system is tailored to specialized requirements. However, it demands significant investment in talent, time, and infrastructure.
Companies must assess whether they have the expertise to develop, train, and maintain such systems or can afford to hire the right people.
On the other hand, buying a pre-built solution is faster and often more cost-effective but may lack customization. It’s ideal for addressing common problems quickly but might not scale seamlessly with business growth or meet niche needs.
Ultimately, the choice should balance short-term needs with long-term goals, ensuring AI investments align with broader strategy and deliver maximum ROI.
Mehmed Džaferović
Marketing Associate, FlyRank
Rainier Mallol - cxgenies
When deciding whether to build or buy generative AI solutions, the single most important factor is strategic alignment—ensuring the AI initiative directly supports both immediate and long-term business objectives.
If you aim to achieve rapid deployment or validate the technology’s impact quickly, acquiring an existing solution may save valuable time and resources, allowing teams to focus on implementation rather than reinvention.
However, once you’ve proven generative AI’s strategic fit, building an in-house solution could offer deeper customization, stronger data control, and potentially lower costs down the road.
Ultimately, the question isn’t just about cost or speed—it’s about whether your chosen path integrates seamlessly into your organization’s overarching mission and growth trajectory.
A lot of companies fail at understanding this, resulting in lackluster implementations, poor results.
Rainier Mallol
President, cxgenies
Erik Gfesser - Fesswise
This consideration can be taken from two different viewpoints: an organization determining whether they should build or buy a generative AI product to support their business, or an organization determining whether to buy another organization that offers a generative AI product.
The reason I’m calling out these two viewpoints is based on my experience building software and data products myself or with my teams, as well as considering purchases of organizations offering products built atop generative AI models.
In both scenarios, one concern is data security.
AI product offerings run the gamut from open source and self-hosted to proprietary and third-party hosted, with the former providing more control than the latter, providing potentially lessened risk.
I’ve discovered software and data product security leaks in the past, but this latter extreme makes discoveries of this type much more challenging due to lack of visibility.
Another main concern of mine is maintainability.
One advantage of buying a generative AI product to support a business is the maintenance package presumably bundled with it.
However, as a business buyer I’ve personally considered purchasing several organizations that offer generative AI products, only to discover that many of these are built as a very thin layer atop the APIs of a single AI model, significantly increasing dependency risks.
Erik Gfesser
Owner, Fesswise
Stephen Greet - BeamJobs
For me, the decision boils down to asking, Is AI a fundamental part of what defines your business?
At BeamJobs, we chose to buy AI solutions initially because building wasn’t where we could add unique value, we’re a resume optimization platform, not an AI development company. But when the limitations of off-the-shelf tools started constraining how we served our users, we knew we had to build.
This factor is pivotal because it forces organizations to prioritize their resources.
Building is expensive and resource-intensive but can deliver a truly differentiated product if AI is at your core. Buying, on the other hand, frees you to focus on areas where your business shines.
Ignore this consideration, and you risk either wasting resources or compromising your competitive edge
Stephen Greet
CEO & Co-founder, BeamJobs
Tiago Pita - Whole Food Earth
When deciding to build or buy generative AI solutions, the most critical factor is your organization’s technical expertise and resources.
Building allows for customization but demands significant investment in skilled talent, infrastructure, and time. Buying offers quicker deployment and lower upfront costs but may limit flexibility and control.
For example, we chose to buy a pre-built AI tool for customer support to save time and focus our team on core operations.
Align the decision with your business goals, budget, and capacity to manage ongoing maintenance.
Tiago Pita
Brand and eCommerce Director, Whole Food Earth®
Danny Veiga - Chadix
As the founder of Chadix.ai and having helped scale businesses to over $50M in online sales, I believe the most critical factor in the build vs. buy decision for generative AI solutions is the organization’s core competency alignment.
From our experience developing AI-powered SEO automation, we’ve learned that organizations should deeply evaluate whether AI development aligns with their existing technical expertise and business focus.
When we built Chadix.ai, we made this decision because SEO automation was central to our value proposition and required specialized capabilities that weren’t available in off-the-shelf solutions.
This factor is crucial because it directly impacts long-term sustainability and competitive advantage.
Building requires significant investment in AI talent and infrastructure, which only makes sense if AI development enhances your core business. Otherwise, buying allows you to focus resources on your primary business objectives while leveraging proven solutions.
Danny Veiga
Founder, Chadix.ai
On behalf of the BoostMyDomain community of readers, we thank these leaders and experts for taking the time to share valuable insights that stem from years of experience and in-depth expertise in their respective niches.
If you wish to showcase your experience and expertise, participate in industry-leading discussions, and add visibility and impact to your personal brand and business, get in touch with the Techronicler team to feature in our fast-growing publication.
