CUSTOMER PORTAL
During a recent family trip to a theme park in North Carolina, my wife and I put together a seemingly solid weekend budget. We mapped out the main line items—admission, hotel, gas, and meals—and felt completely confident in our numbers. But reality set in fast as hotel snacks, unplanned arcade games, and one-of-a-kind souvenirs steadily pushed us over our limit.
Looking back, our budget wasn’t inherently wrong; it was simply incomplete because we overlooked the extra expenses that naturally come with the full experience.
Organizations often find themselves in the same position when budgeting for AI in their third-party risk management (TPRM) programs. After months of demos, evaluations, and business cases, the budget is approved and the software is purchased.
Budget season has always been an exercise in looking ahead. Every year, third-party risk leaders evaluate what worked, what didn’t, and where they need to invest to keep pace with an increasingly complex risk landscape. Traditionally, those conversations centered around expanding assessment programs, increasing analyst capacity, or investing in technology that could automate manual processes.
This year, however, the budgeting conversation has changed.
Artificial intelligence has quickly become part of nearly every discussion around third-party risk management. Nearly every technology provider now offers AI-powered capabilities designed to accelerate assessments, summarize vendor documentation, prioritize risks, or reduce administrative work. The promise is compelling: do more with the resources you already have while improving the speed and consistency of your risk program.
But as organizations move from exploring AI to operationalizing it, many are discovering that budgeting for AI requires more than simply approving another software purchase.
The most successful organizations recognize that AI isn’t simply a feature to switch on. It’s a capability that requires planning, governance, and thoughtful investment. The organizations seeing the greatest return aren’t necessarily spending the most on AI. They’re budgeting for everything that enables AI to deliver meaningful business value.
One of the biggest misconceptions is that AI automatically lowers costs from day one. While AI can absolutely create efficiencies by reducing repetitive work and helping analysts focus on higher-value decisions, those efficiencies don’t happen in isolation. Like any strategic investment, realizing value depends on the quality of the data feeding the system, the processes surrounding its use, and the people responsible for interpreting its output.
That’s why budgeting for AI in a TPRM program should begin with a broader question:
What will it take for AI to become a trusted part of our risk management process?
For many organizations, the answer extends well beyond licensing costs.
The first consideration is understanding exactly what you’re buying. AI has become one of the industry’s favorite marketing terms, but not every AI capability is included in a standard platform subscription. Some vendors charge based on users, others on transaction volume, and still others on AI consumption or usage. Before committing budget dollars, it’s worth understanding whether today’s attractive pricing will remain sustainable as adoption grows across your organization.
Equally important is the quality of the information AI will rely upon. AI can only provide meaningful recommendations when it’s working with accurate, complete, and well-governed data. Organizations with inconsistent vendor inventories, outdated assessments, or fragmented third-party information may find that their first AI investment isn’t actually AI at all. It’s improving the underlying data that powers it. While data governance may not be the most exciting budget item, it is often the investment that determines whether AI delivers meaningful outcomes or simply produces faster, less reliable results.
Governance deserves equal attention. As AI becomes more involved in risk identification and decision support, organizations must establish clear policies for how AI-generated recommendations are reviewed, validated, and ultimately acted upon. Regulators are increasingly focused on transparency and accountability, making human oversight an essential part of any AI strategy. Budgeting for governance today can help organizations avoid far greater compliance challenges tomorrow.
Perhaps the most underestimated cost of AI adoption isn’t technology. It’s change management.
Technology alone rarely transforms a program. People do. Analysts need to understand how AI fits into existing workflows, when its recommendations should be trusted, and when additional investigation is necessary. Building confidence in AI takes training, communication, and time. Without user adoption, even the most sophisticated capabilities struggle to deliver measurable value.
Organizations should also budget for measuring success. AI investments should be tied to outcomes that matter to the business, such as shorter assessment cycles, faster vendor onboarding, improved analyst productivity, or greater visibility into third-party risk. Establishing those metrics upfront not only helps demonstrate return on investment but also provides a stronger foundation for future budgeting decisions.
Much like planning a family trip, budgeting for AI isn’t inherently flawed—it simply needs to account for everything required to make the overall investment truly worthwhile.
The organizations that will gain the greatest advantage from AI won’t necessarily be those with the largest technology budgets. They’ll be the ones that approach AI as a strategic capability rather than a standalone feature.
Budgeting for AI isn’t simply about purchasing new functionality. It’s about investing in the people, processes, governance, and data that allow AI to become a trusted extension of your TPRM program. Organizations that take this broader view will be better positioned to realize AI’s potential while avoiding many of the hidden costs that often accompany rushed implementations.
As AI continues to reshape third-party risk management, organizations should stop asking, “Can we afford AI?” and instead ask, “Are we budgeting for everything it takes to use AI well?”
Contact us today to see how Aravo can help you maximize the value of AI in your TPRM program
Share with Your Friends: