Here's a sobering statistic: The technology sector continues to see the most M&A activity¹, yet only about 10% of companies conduct a thorough cyber due diligence MA assessment². With AI now woven into the fabric of nearly every business operation, this oversight isn't just risky—it's potentially catastrophic.
Picture this: You've just closed a $50 million acquisition of a promising tech company boasting cutting-edge AI capabilities. Six months later, you discover their "proprietary" AI model was built on unlicensed training data, their algorithms contain significant bias issues, and their security protocols can't protect the sensitive data they process. What seemed like a strategic advantage has become a legal and financial nightmare.
This isn't a hypothetical scenario—it's happening right now across boardrooms everywhere. As business leaders rush to acquire AI capabilities in an increasingly competitive landscape, the complexity of AI due diligence has become one of the most critical yet underestimated aspects of modern M&A transactions. In this guide, we'll explore why traditional due diligence falls short when it comes to AI, what questions you need to be asking, and how to protect your organization from the hidden risks that could derail your next deal.
The numbers tell a compelling story. While large deals are still occurring across a wide range of sectors, megadeal activity has been especially concentrated in technology¹, with AI-focused acquisitions driving much of this activity. Companies are no longer just buying for scale – they're buying for transformation³, and AI capabilities have become the new Holy Grail for competitive advantage.
But here's what most business leaders don't realize: acquiring AI isn't like acquiring traditional technology assets. When you buy a company with AI capabilities, you're not just buying software—you're inheriting data relationships, algorithmic decisions, regulatory compliance obligations, and risks that didn't exist five years ago.
Traditional technology due diligence typically focuses on infrastructure, software licensing, and basic cybersecurity measures. But AI introduces an entirely new category of risks that most due diligence frameworks weren't designed to handle.
Consider what happens when you acquire a company that uses AI to process customer data. You're suddenly responsible for ensuring that AI model was trained ethically, that it complies with rapidly evolving AI regulations, that the training data was properly licensed, and that the algorithms don't introduce bias that could expose your company to discrimination lawsuits.
Many companies say they are using artificial intelligence as part of their business. It has become a bit of a marketing buzz word⁴. This "AI washing" phenomenon means that what a target company claims about their AI capabilities and what they actually possess can be dramatically different.
The foundation of any AI system is its data, and this is where many acquisitions run into trouble. Due diligence should entail examining security protocols, vulnerability management strategies, and incident response plans⁵, but it must go deeper when AI is involved.
Key questions to investigate include:
The stakes here are enormous. If a target company used unlicensed data to train their AI models, you could inherit significant legal liability. If they've been processing sensitive customer data without proper safeguards, you could face regulatory fines and reputation damage.
One of the most overlooked aspects of AI due diligence is understanding how the target company's algorithms make decisions. This isn't just a technical concern—it's a business risk that could impact your reputation and expose you to legal liability.
You need to understand:
A financial services company, for example, might discover after acquisition that their target's AI lending algorithm systematically discriminates against certain demographic groups—a discovery that could result in millions in fines and irreparable reputation damage.
AI regulation is evolving rapidly across multiple jurisdictions. The EU's AI Act, various state-level regulations in the US, and emerging international frameworks create a complex compliance landscape that's changing constantly.
During due diligence, you need to assess:
I don't care what your business does, what type of data you have, or how big it is – you will face questions about your cybersecurity plans, training, and insurance in 2025⁴. This is especially true when AI is involved.
AI systems create unique cybersecurity challenges that traditional security measures weren't designed to address. AI models can be subject to adversarial attacks, data poisoning, and model theft—risks that could compromise not just the target company but your entire organization after acquisition.
Many AI capabilities rely on third-party services, from cloud computing platforms to specialized AI tools. A trend in 2024 was for cyber attackers to go after supply chains – enabling them to leverage third-party vulnerabilities to cripple multiple organizations at once⁴.
When you acquire a company with AI capabilities, you need to understand:
The financial implications of AI due diligence extend far beyond the initial acquisition price. Poor AI due diligence can result in:
Unexpected Compliance Costs: Bringing AI systems up to regulatory compliance standards can cost millions, especially in heavily regulated industries like healthcare and financial services.
Integration Complexity: AI systems often require specialized infrastructure and expertise that can significantly increase integration costs.
Ongoing Operational Expenses: AI systems require continuous monitoring, updating, and maintenance that traditional software doesn't need.
Risk Mitigation: Addressing security vulnerabilities, bias issues, or data rights problems discovered after acquisition can be exponentially more expensive than identifying them during due diligence.
Given the complexity of AI due diligence, many organizations benefit from working with specialized partners who understand both the technical and business implications of AI acquisition.
Technical Architecture: How are AI models built, deployed, and maintained? What's the underlying infrastructure, and how scalable is it?
Data Governance: What data management practices are in place? How is data quality maintained? What are the data retention and deletion policies?
Talent and Expertise: Does the target company have the right talent to maintain and improve their AI systems? Are key AI personnel likely to stay post-acquisition?
Intellectual Property: What AI-related IP does the company actually own versus license? Are there any IP disputes or potential conflicts?
Performance Metrics: How does the company measure AI performance? What are the accuracy rates, and how have they changed over time?
While AI due diligence adds complexity to the M&A process, it also creates significant strategic advantages. Companies that properly assess AI capabilities can:
Risk management has evolved, and the technology based on high-volume data for deal intelligence has entered a new era with Generative AI and other new technologies⁶. Organizations that adapt their due diligence processes to address AI-specific risks will have a significant competitive advantage in the M&A market.
The reality is that AI is no longer optional in most industries—it's becoming table stakes for competitive survival. But that doesn't mean you need to navigate AI due diligence alone.
The most successful acquirers are partnering with technology advisors who understand both the promise and the pitfalls of AI integration. They're developing comprehensive frameworks that address technical, legal, regulatory, and business risks. Most importantly, they're treating AI due diligence not as an obstacle to overcome, but as a strategic advantage that helps them make better acquisition decisions.
At Sentry Technology Solutions, we've helped numerous clients navigate the complex landscape of technology M&A, including the emerging challenges of AI due diligence. We understand that every AI acquisition is unique, requiring a customized approach that addresses your specific industry, regulatory environment, and business objectives.
Don't let the complexity of AI due diligence prevent you from pursuing strategic acquisitions—but don't let inadequate preparation turn your next AI acquisition into a costly mistake. The questions you ask today will determine whether your AI acquisition becomes a competitive advantage or a cautionary tale.
Ready to ensure your next M&A deal includes comprehensive AI due diligence? Learn more about our M&A advisory services and discover how we can help you navigate the complexities of technology acquisitions with confidence.
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