How data and AI platforms speed M&A: from faster due diligence to platform-led integration

The useful part

Guen +2 In mergers and acquisitions (M&A), data has become a critical determinant of deal success. Beyond traditional financial metrics, the ability to access, understand and trust data directly impacts valuation, risk assessment and the speed of execution. Accenture research reveals that only 7% of executives have built the AI-ready data capabilities required for scaled AI adoption.

How it works

• Siloed and low-quality data directly inhibits value realization, and transaction contexts that demand speed and accuracy only amplify this risk.
• From finance to supply chain and commercial operations, AI-supported processes depend on seamless, real-time access to high-quality data.
• Organizations that effectively leverage AI and data at scale are already seeing measurable impact, achieving an average 49% ROI.
• In this post, we look at how a modern data and AI platform reshapes both phases: accelerating due diligence before the deal closes and turning integration into a performance driver rather than a costly IT...
• Such platforms unify structured and unstructured data across the enterprise, embed governance and security by design, and provide the scalability required to support both analytics and AI workloads.

What to take from it

Together, these capabilities are designed to accelerate timelines, improve insight quality and reduce execution risk. Post-deal: platform-led integration, separation and synergy activation Post-deal execution, whether integration or separation, remains one of the most complex and risk-prone phases of the transaction lifecycle. Instead of manually reviewing fragmented records, AI can rapidly ingest and analyze the biotech's clinical trial data and IP portfolio, supporting a faster, more informed valuation.

Example or evidence

• Equally important, they support secure collaboration across stakeholders and integrate capabilities for developing, deploying and monitoring AI solutions.
• In today's environment, this type of platform is a prerequisite for value creation.
• This enables a shift toward a more forward-looking assessment of performance.
• Data and AI use cases in pre-deal Data platforms are reshaping how due diligence is conducted.

Details worth keeping

Poor data quality is both a technical issue and a financial one. It's increasingly the foundation for end-to-end AI-driven transformation. Pre-deal: transforming due diligence and secure collaboration Investors are expanding their due diligence beyond financial performance to include data and AI maturity assessment which is transforming the traditional pre-deal phase.

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