AI is rewriting the economics of software — and most due diligence processes haven't caught up. For PE firms investing in software assets, the gap between what traditional tech DD captures and what actually determines long-term value has never been wider.
Private equity has always demanded rigour at acquisition — financial models, legal structures, commercial diligence, refined over decades. Technology due diligence, by contrast, has too often been a checklist: is the code maintained, is the architecture scalable, is there meaningful technical debt?
That framing is no longer sufficient. The question is not simply whether a software asset is well-built — it's whether it will still matter in three to five years. Engineering power is no longer scarce, the seat-based pricing model is starting to break, and usage and revenue are beginning to decouple.
The question is not simply whether a software asset is well-built. The question is whether it will still matter in three to five years.
Palladium Digital Perspective
Four things rigorous AI due diligence must address
The full whitepaper expands on each of these — with the questions investors should be asking before they underwrite their next software deal.
Genuine moat vs apparent defensibility
Does the asset hold data that cannot be replicated, or does it simply feel sticky today?
Pricing model durability
Is seat-based or usage-based pricing robust to orchestration-layer adoption in this specific niche?
AI substitution timeline
Which product elements are exposed to commoditisation, and how fast is adoption moving in this market?
AI opportunity identification
Where can AI extend the asset's existing advantages — and does the business have the capability to move?
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About Palladium Digital Group
Palladium Digital works with leading PE firms and their portfolio companies on technology strategy and AI implementation. We'd welcome a conversation about what rigorous Tech & AI due diligence looks like for your next software deal.