Here's an interesting thought experiment. You are evaluating fund accounting platforms. You have two options.
Option A is an established vendor. Fifteen years in market. Their platform works, more or less. Most of your peers use them. They want a 3-year initial term.
Option B is an AI-native startup. Their demo is impressive. They automate things Option A expects three people to do manually. They also want a 3-year initial term.
Conventional wisdom says Option A is the safe choice. But here's the problem: three years ago, ChatGPT did not exist. The capabilities that make Option B impressive were not possible. What will be possible three years from now? Will Option A have adapted, or will they be selling the same product with a chatbot bolted onto the help desk?
Now consider Option B. The AI landscape is moving so fast that today's breakthrough is tomorrow's table stakes. Will they still be the best choice in 2029? Will they even exist?
The honest answer to both questions is: you do not know. Nobody knows. Yes, there are real reasons GPs have historically accepted longer initial terms: pricing leverage, implementation runway, termination and step-in rights, and the sheer cost of running constant evaluation cycles. But when the underlying technology is shifting this fast, the risk of being locked in outweighs the discount. This is why locking into a 3-year initial term (with either vendor) no longer makes sense.
Why the Old Logic Broke
For decades, 3-year terms were typical in private markets software. Vendors got revenue predictability. Buyers got discounts and avoided constant evaluations. Switching costs were high anyway. And software didn't change fast enough to make you regret a long commitment.
That last assumption has collapsed.
HG Capital's Nic Humphries put it plainly: the enterprise software market is experiencing "a once-in-20-year platform shift with AI."¹ A Moonfare report found 88% of private equity firms have already made meaningful investments in generative AI, with 69% expecting ROI within two years.² The technology landscape is not stable enough to predict what you will need 36 months from now.
The Established Vendor Problem
If you sign a 3-year term with an established platform, you are betting they will successfully navigate the AI transition. That may no longer be a safe bet.
Juniper Square called this the fund administration industry's "Kodak moment." Incumbent tech stacks, they wrote, "depend on human memory, email chains and institutional knowledge — not system logic." And then the counterintuitive part: "You may think size is an advantage. But in this new era, it's often a liability."³
None of this means established vendors are the wrong choice. It means the timeline on which you evaluate that choice should match the pace of change. Right now... three years is a long time.
The AI-Native Vendor Problem
So sign a 3-year deal with an AI-native startup instead? Also no.
The AI tooling landscape is chaotic. Today's frontier capability becomes tomorrow's commodity feature. The startup that wows you in a demo might get leapfrogged six months later — or by a foundation model update that makes their differentiation irrelevant.
This is not a criticism of AI-native vendors. Many are building genuinely transformative products. But "transformative" and "predictable over a 3-year horizon" are not the same thing. Signing a long initial term with an early-stage AI vendor is picking a horse in a race where the track is still being built.
Flexibility is King
The standard structure has been 3-year initial terms followed by annual or multi-year renewals. That assumed the hard part was getting started. The opposite is now true. Implementations are faster, integrations are easier, and vendors hungry for new logos. The hard part is predicting which vendor will still be the right choice as the market evolves.
Shorter initial terms (12-18 months) with renewal options give you flexibility. But "negotiate a shorter term" is not a strategy by itself. Here is what a real negotiation looks like:
Performance benchmarks tied to renewal. Define measurable SLAs for the capabilities you are actually buying: processing accuracy, automation rates, and outcome-based metrics where you can. Build these into the contract so renewal decisions are based on data, not inertia.
Data portability negotiated upfront. The biggest hidden cost of a long-term contract is not the subscription fee — it is the cost of extracting your data when you need to move. Require standardized export formats, API access, and reasonable transition support as part of the agreement.
Quantify the flexibility premium. Vendors may quote higher rate cards for a shorter initial term versus a 3-year rate. Run that against the fully loaded cost of being locked into a platform that falls behind. In most cases, the premium pays for itself within six months of avoiding a bad outcome.
A confident vendor should be willing to earn your long-term business rather than lock it in upfront.
Footnotes
¹ Enterprise Software Investing at an AI Inflection Point, Private Markets Insights, 2025.
² Private equity outlook 2026, Moonfare, 2025.
³ Fund admin's "Kodak Moment", Juniper Square, 2025.
