In today's fast-paced digital transformation era, where AI is creating both new opportunities and new vulnerabilities, traditional criteria for assessing growth strategies need a rethink. Decision-makers are facing a rapidly changing economic landscape where a company’s ability to integrate and leverage AI is becoming a crucial determinant of its value and long-term viability.
The strong growth in acquisition operations in recent years seemed to confirm the triumph of “buy” over “build.”
On one hand, the strengths of “buy”: proven business models, the ability to scale through synergy effects, accessible financing levers (less so since interest rates have risen, admittedly), available expertise and “capabilities,” along with existing revenues and customer base...
On the other hand, the weaknesses of “build”: sprawling projects going over budget, extended time-to-market, rare skills and talents (which need retention), unpredictable go-to-market strategies, and prohibitive initial acquisition costs.
In short, the match appeared settled. But again, the rise of AI has changed the game. In my view, it's more urgent than ever to develop a fresh perspective on the matter. Here’s a list of blind spots often overlooked during strategic audits that should help balance the scales.
Company's Resilience and Adaptability to AI
Assessing technological resilience: The audit should examine whether the company has infrastructure capable of adapting. This includes system robustness, cybersecurity, and the ability to evolve without disrupting operations.
Transformation capacity: Some companies might appear technologically advanced but lack flexibility in the face of rapid changes. It's essential to evaluate whether the company is resilient or vulnerable to disruptions induced by AI to identify future investment or restructuring needs.
Team's Maturity in Working with AI
Internal skills audit: Due diligence must evaluate the existing AI, machine learning, and data management skills within the targeted company's teams. Identifying a gap in AI skills might indicate the need for additional recruitment or external partnerships, thus increasing costs and timelines.
Innovation culture: The tendency of teams to adopt and use AI technologies should be measured. An innovation culture is crucial for successful AI adoption and performance optimization. This includes evaluating ongoing training efforts in AI and openness to change within the team.
Vulnerability to Disruption and Competitive Risks
Disruption risk: Due diligence must include sector analysis to evaluate if the targeted company could be vulnerable to disruptions by AI, especially in industries where AI is rapidly transforming practices (healthcare, finance, retail, etc.).
AI competitive analysis: It’s essential to compare the AI capabilities of the targeted company with those of its competitors. Weak capabilities or gaps in AI may signal a risk of losing market share.
Data Management and Governance
Data management assessment: Due diligence should examine the quality, security, and accessibility of the company's data. If the company lacks a robust data governance strategy, it can create vulnerabilities.
Regulatory compliance and protection: Given the regulations concerning data protection (AI Act, GDPR), it's crucial for the targeted company to master the legal and ethical aspects of using AI and data. Evaluating privacy policies and practices regarding data storage and usage is imperative to avoid future legal risks.
Legal Aspects and Social Risks
AI legal compliance: Due diligence should include an evaluation of the compliance of AI applications with current rapidly evolving regulations. For instance, if the company uses AI algorithms in regulated sectors (such as finance or healthcare), it must prove transparency, non-discrimination, and privacy protection in its AI practices.
Social implications and employment impact: Assessing AI’s impact on employment within the targeted company is also crucial. Some AI initiatives may reduce the workforce needed, which can lead to internal resistance and a need for transition management for employees. Due diligence should thus include an analysis of training plans, retraining, and technology acceptance by employees.
In conclusion, by 2025, the decision to “buy” or more broadly to invest in a company (regardless of industry) must necessarily be guided by these new criteria. AI auditing is not a marginal topic or a fad, but indeed a vital step in determining the overall sustainability or fragility of a company. And thus, by extension, its valuation.
Conversely, any company aiming to launch a sale or open its capital must have conducted its own assessment, documented it, and placed it at the heart of its “equity story”!
At Insign, we’ve developed a precise analytical framework allowing a multi-factor audit on the subject, led by trained expert consultants. We integrate into broader strategic due diligences with this specific focus.
