How PwC's Deals Team is Redefining Due Diligence With AI

In today’s M&A market, timelines are compressed, risk profiles are more complex, and the cost of incomplete analysis is higher than ever. Across this ecosystem, AI is reshaping how deals are sourced, evaluated, and executed by expanding document coverage and shortening review cycles. And Deals clients are benefitting from this through faster, more precise decision making throughout the entire deal cycle.

By embedding Harvey across the deal lifecycle, from rapid discovery on new targets to structuring and interrogating full VDRs in Harvey Vault, PwC’s Deals team is replacing manual document analysis with actionable insights. The technology is enabling conviction-led advice grounded in comprehensive, citation-backed insights, all while operating in a secure AI environment ensuring confidentiality, data security, and compliance are maintained throughout every stage of the engagement.

In this conversation, Patrick Devine, Deals AI Lead and Partner at PwC Germany, shares how AI-powered workflows are transforming financial due diligence, accelerating client outcomes, and making day-to-day work faster and more rewarding.

Can you tell us about your role within the Deals team and what your day-to-day work typically involves?

As a Deals Partner at PwC Germany with nearly 20 years of experience, I specialize in financial due diligence for clients. I also serve as the Deals AI Leader for PwC Germany and represent the country on PwC’s Global Technology Board for Deals.

Day to day, I’m advising clients on buy and sell side transactions, driving data-backed insights into commercial and financial risks, and orchestrating multidisciplinary teams. In practice, I now collaborate with Harvey throughout every stage of an engagement, from launching the Discovery workflow and quickly orienting myself to a target, to structuring and analyzing the VDR in Harvey Vault, and leveraging workflow-driven analysis to identify and validate issues earlier.

Harvey has become my first stop for most work. Whether I’m preparing for management calls or pressure-testing hypotheses with underlying documents, it all starts in Harvey.

How do you see AI transforming M&A and professional services? What are the primary use cases where you and your team rely on Harvey today, and what bottlenecks are you able to solve?

AI is moving us from manual document hunts and fragmented analysis to conviction-led advice grounded in comprehensive evidence. Historically, time and human bandwidth forced us to triage and teams would sample a subset of documents or rely on management narratives. With Harvey, we can review far more source material in less time, referencing where each answer comes from, and engage clients with sharper, faster, and better supported viewpoints. Being able to do this earlier on in the process means we can help our clients by giving them greater confidence and creating a competitive advantage for them in their M&A processes.

Today, our core use cases are typically: rapid discovery on new targets; ingesting entire VDRs into Harvey Vault; interrogating documents and contracts for specific risk themes such as price pass through; generating first drafts of report sections using context from Vault; and using enriched meeting transcripts inside Vault to maintain a living, searchable knowledge base throughout the deal. These use cases augment the knowledge and expertise of our people with world class technology capabilities.

The bottlenecks we’ve eliminated include the time typically spent organising data rooms and the time-consuming first-draft stage for standardised reporting. Perhaps most importantly, we have materially increased completeness and consistency moving from an approach where we sampled a few to one where we can say with confidence that we checked twenty, and here’s the evidence.

Can you share a specific example where you leveraged Harvey in an M&A, financial due diligence, corporate finance, or restructuring matter?

We used Vault to analyse customer contracts for price pass through clauses, which was previously impractical at scale within compressed timelines. That analysis meaningfully changed the conversation: we could quantify how often price uplifts were permitted and challenge management more precisely on commercial implications.

The combination of speed and evidentiary backing elevated both our effectiveness and client confidence. Instead of spending all of the time working through a small sub-set of contracts, we were able to focus the diligence time on the risks and upsides associated with the insights so our client could confidently price it.

Which parts of the Harvey platform have been the most valuable for your team, and why?

Harvey Vault is foundational. Putting the entire VDR, management materials, and call transcripts into a single, queryable environment unlocks breadth and depth simultaneously. It centralises the evidence, accelerates retrieval, and gives us traceable references. This is a clear example of how we can get deeper insights and more transparency around the key deal issues for our clients during diligence.

The Discovery workflow is also critical in the early days of an engagement; it quickly orients the team to the target’s business model, likely risk areas, and priority questions. I’m really excited about having the ability to build our own workflows with Workflow Builder. Our initial testing is showing positive results, generating high quality first drafts that shift the team’s focus from rewriting to refinement.

What impact has Harvey had on productivity, time savings, quality of work, or client outcomes across the Deals team?

The impact shows up in three ways. First, speed and transparency: we can get to insights early in the due diligence process, including identification of red flags shortly after the data room opens. Second, quality and completeness: we are able to review more documents in less time and defend conclusions with stronger references, including being able to select risk and upside areas to dig deeper in, which materially improves conviction and client outcomes. Third, team and client experience: engagements run more smoothly, teams spend less time on mechanical tasks, and clients receive clearer, faster, and more evidence-based advice — increasing their conviction and ultimately the deal outcomes.

A major, under-discussed benefit is how much more enjoyable and energising the work becomes. When teams can turn curiosity into insight in seconds, you get more “aha” moments and fewer late-night hunts for pages in a data room. The technology nudges the whole team to ask better questions. For example, after Vault flagged a high proportion of contracts without permitted price pass-through, we reframed our management conversation toward resilience and margin protection, not just historic performance. That shift in dialogue is the point: AI helps us be more critical, more complete, and more client relevant earlier in order to ultimately create a successful outcome for our clients in an M&A process.

The exact percentages vary by case, but we consistently see time shaved off document review and drafting phases, and that means that whilst our overall timeline doesn’t change materially, instead of manual work we spend more time placing higher-quality analysis in front of clients earlier in the process.

What advice would you give M&A or professional services leaders considering AI tools like Harvey?

Start with workflows that mirror repeatable tasks in your practice like discovery, contract thematic reviews, and standard report sections. Put your VDR and transcripts into Vault early and treat it as the single source of truth for the engagement. Focus on outcomes: faster, better referenced answers delivered in the flow of client conversations.

It’s also important to build comfort and fluency among your teams by investing in their training and letting them drive the prompts and workflows; the goal is to orchestrate, not to perform every manual step. Finally, be transparent about quality: insist on traceability to source, and lean on references to build conviction and trust. Human judgment plays a critical role and needs to be the final review point for everything that you produce, but with this capability available to you, you have a huge opportunity to re-evaluate how your projects are delivered by your teams.