Why Private Equity Should Treat Technical Diligence Like Financial Diligence
When it comes to evaluating a deal, most private equity (PE) firms have financial diligence down to a science. Balance sheets, revenue streams, and margin trends are dissected with rigor.
But when diligence turns to technology, the same level of scrutiny isn’t always applied. Yet technical diligence is often where the risk hides. Today, that risk increasingly includes artificial intelligence (AI). For companies building, buying, or deploying AI, the questions are no longer optional. They belong at the top of the diligence checklist.
Risk in Technology
Strong financials can still mask weak technology. In Kickdrum’s work with acquisitions and portfolio companies, we’ve seen the same risks appear time and again:
Infrastructure that won’t scale: Systems that look solid under current demand can crack and degrade when growth accelerates.
Codebases riddled with hidden debt: Years of shortcuts and deferred maintenance slow down future delivery.
Cloud costs that balloon: Without disciplined cloud infrastructure design and cost governance, AWS bills can creep up and quietly erode EBITDA.
Security gaps: Vulnerabilities that remain hidden until a breach can destroy value overnight.
Unexamined AI exposure: From unvetted AI tooling to opaque models embedded in the product, companies are taking on risks they don’t yet understand.
Each of these issues can derail an investment thesis, delay roadmap execution, or require costly remediation post-close.
Why Technical Due Diligence Matters
Financial diligence provides a snapshot of today’s performance. Technical due diligence provides a window into tomorrow’s. It asks critical questions that determine whether growth assumptions are realistic:
Can the current architecture scale with customer demand?
Does the engineering team have the processes and leadership to deliver consistently?
Are cloud costs and infrastructure aligned with business goals?
Do security practices meet the standards required for long-term resilience?
How is AI being used, governed, and secured across the company?
AI is particularly urgent, as its adoption is accelerating faster than most governance practices. PE firms now need to know:
Are engineering teams over-relying on AI-generated code without quality controls?
Are products embedding third-party AI models with unclear IP or regulatory exposure?
Are there opportunities to responsibly leverage AI to accelerate value creation post-close?
Without clear answers, investors risk buying into a company whose growth is capped not only by its technology debt but also by its AI blind spots.
Raising the Bar on Diligence
As deal volumes slow and valuations remain high, the bar for diligence is rising. Operating partners and portfolio executives know that every blind spot increases the likelihood of post-close surprises. Treating technical diligence with the same rigor as financial diligence helps firms:
Negotiate from strength: With a full picture of risks and opportunities, investors can price deals more accurately.
Protect enterprise value: Early identification of risks reduces the likelihood of expensive pivots later.
Accelerate value creation: Insights into software development, cloud optimization, and responsible AI use can shape 100-day plans and unlock growth sooner.
The Bottom Line
In acquisitions, strong financials alone don’t guarantee future performance. Infrastructure, code quality, AI governance, cloud spend, and security all play a decisive role in whether a portfolio company scales or stalls.
The lesson is simple: technical diligence deserves the same rigor as financial diligence. And in today’s market, that means moving AI diligence to the top of the agenda. For PE firms and portfolio company leaders, it’s not just about protecting downside risk. It’s about creating the conditions for long-term, technology-enabled value creation.
