How AI Is Transforming Corporate Development (Without Replacing Strategy)

For most Corporate Development (Corp Dev) leaders, the job has always been the same:

turn corporate strategy into an actionable M&A thesis, and
turn that thesis into a pipeline of credible targets and closed deals.

What is changing, and changing fast, is the toolkit.

AI is now embedded across the M&A lifecycle, from market mapping and target discovery to CIM triage and outreach. But even as generative AI and data platforms explode in number, one thing has not changed: great deals still start with great strategy.

Modern tools like sc0red do not replace the hard work of defining where your company should play or why a deal makes sense. Instead, they help Corp Dev teams translate those strategies into focused searches for the right targets and bring inorganic growth plans to life with more speed and precision than was possible even a few years ago.¹

1. The AI Moment in Corporate Development

Recent surveys suggest AI has crossed the “nice to have” line in M&A:

Deloitte’s 2025 GenAI in M&A Study reports that about 86% of corporate and PE leaders now use generative AI somewhere in their dealmaking workflows, and roughly two thirds adopted it within the last year.²
Bain finds that roughly one in five practitioners is already using GenAI in M&A, with more than half expecting to adopt it by 2027, and warns that late adopters risk overpaying for bad deals and missing good ones.³

At the same time, a 2025 MIT study highlights that many generative AI projects fail to deliver impact when they are not tightly tied to real business workflows or strategy.⁴

Put together, this paints a clear picture for Corp Dev:

AI is becoming table stakes in dealmaking.
But tools only create real value when they are anchored to a clear corporate strategy and investment thesis, not when they are adopted because “everyone else is doing AI.”

2. From Strategy Slides to Searchable Theses

Historically, Corp Dev teams spent months building market factbases: analyst decks, consultant reports, internal interviews, and spreadsheets capturing adjacencies and white space. This work produced a strategy, but not always a clean bridge to execution.

AI is now tightening that gap in two ways.

AI assisted market and thesis development

Market intelligence platforms like CB Insights, AlphaSense, PitchBook and others use machine learning to monitor funding, patents, and signals of disruption, helping Corp Dev teams spot emerging themes early and refine where M&A could accelerate strategy.¹
Analytics and predictive models can highlight where consolidation is likely, which niches are structurally attractive, or where a build versus buy decision might tilt toward acquisition.⁵

Turning theses into structured, machine readable criteria

Where AI really shines for Corp Dev is in the “translation layer”:

Taking a thesis like “North American industrial services firms with mission critical recurring revenue, high field tech density, and aging founders”
Converting that into specific, searchable attributes (business model, geography, customer type, ownership patterns, leadership age, and so on)
And then applying those attributes across millions of companies, not the few hundred you can manually screen.⁶⁵

This is where tools like sc0red explicitly live: they encode the deal team’s strategy into an assessment that can be run on any company record, rather than simply giving you another database to wade through.¹

3. AI Across the Corp Dev Pipeline

Once the thesis is structured, AI starts changing the day to day work of Corporate Development along the entire front end of the funnel.

a. Market mapping and white space analysis

Corp Dev teams can now:

Map adjacencies and white space by scanning private companies in specific value chains, not just those captured by SIC or NAICS codes. Platforms like Grata emphasize “data driven strategy” by using private company density, financial benchmarks, and trends to highlight promising verticals for expansion.⁷
Quickly test “what if” scenarios, for example what if we focus on field service players in the Southeast with HVAC plus plumbing capabilities?, and see if there are enough credible targets to justify a roll up thesis before burning cycles on CIMs and banker conversations.⁵

b. Target discovery beyond the usual suspects

AI native sourcing platforms (Inven, Grata, and others) use natural language and semantic search on company websites, profiles, and signals to surface targets that never show up in traditional databases, especially in fragmented or niche markets.⁶⁷

Similarly, sc0red was built to help acquirers move beyond “who we already know” by scanning entire markets at once, based on the user’s unique investment thesis rather than just basic firmographics.¹

c. Automated screening and CIM triage

Analyst teams traditionally spent weeks reading CIMs, building one off scorecards, and re creating the same screening logic deal after deal. AI changes that in a few ways:

Deal screening agents can now read pitch decks and CIMs directly, summarize the business model, and flag whether the opportunity aligns with pre set criteria, dramatically improving triage speed.³⁸
AI scoring models, like those in sc0red, standardize how you evaluate targets across dimensions such as strategic fit, leadership, growth signals, and market dynamics, so a global team views an opportunity through the same lens, not ten different spreadsheets.¹

EY and others note that similar AI techniques are already reshaping due diligence, doing first pass document review and risk flagging in hours rather than weeks.⁸⁹ For Corp Dev, that means you can spend more time on judgment and less on document wrangling.

d. Outreach, intent signals and pipeline management

Once you know who might be a fit, the next question is when and how to engage. AI is changing that too:

Relationship intelligence tools map executive networks, showing which board member or BU leader has the warmest path into a target CEO, a theme also highlighted in sc0red’s own overview of M&A technologies.¹
AI based “intent to sell” models watch for hints that an owner might be open to a deal: generational hand offs, PE hold period maturity, leadership changes, or other public breadcrumbs that often precede a transaction.⁶⁵

In our own interviews with corporate acquirers and PE sponsors, we repeatedly heard that getting to interesting, owner led conversations earlier is one of the clearest benefits they expect from AI enabled sourcing and screening.¹

4. How AI Is Reshaping the Corp Dev and Banker Relationship

As Corp Dev teams use AI to do more of their own market mapping, target discovery and early screening, the role of investment banks and M&A advisors is evolving, not disappearing.

Several trends are emerging:

In house origination is getting stronger. With AI native search tools, Corp Dev teams are less dependent on banker lists to see the landscape. They are building their own view of a sector, often before a formal process begins.⁵⁷
Bankers are adopting AI as well. Reports on M&A activity in 2025 note that investment banks are increasingly using generative AI to streamline information gathering and process management, especially in competitive auctions.³⁹
Advisors move up the value chain. Instead of being paid primarily for “access to buyers and sellers,” advisors add more value in complex structuring, valuation under uncertainty, regulatory navigation, and helping to run robust sale processes.

In that world, Corp Dev leaders who have their own AI enhanced view of the market can engage advisors from a position of strength: they know which sectors are attractive, which targets are missing from banker lists, and where a banker can truly add value versus just reselling generic data.

5. Where sc0red Fits: Strategy → Search → Shortlist

sc0red sits squarely in the “strategy translation” layer of this new Corp Dev stack.

Rather than being just another company database, sc0red is designed to:¹

Ingest your specific thesis
- Corp Dev or PE teams describe, in natural language, what a great target looks like, including sector nuances, customer profiles, revenue mix, leadership patterns, geography, owner profile, and more.
- sc0red turns that into a structured assessment with a set of questions that capture how your team thinks about fit.
Scan the market at AI scale
- That assessment is applied across very large company sets, using both public data and curated third party sources to build a view of each company against the thesis.¹
- Instead of manually reading 500 CIMs, teams see a ranked list where the “obvious no’s” have already dropped to the bottom.
Prioritize and act
- Corp Dev teams can quickly identify the top subset of targets that merit deeper human review, relationship building, and eventually full diligence.
- As deals progress, sc0red can also support AI driven document review to accelerate later stage diligence, keeping the same logic that informed the initial screen.¹

The crucial point, though, is this:

sc0red does not decide your corporate strategy. It helps you execute it.

If your thesis changes, for example because you decide to shift from regional roll ups to vertical product expansion, you update the assessment. The tool then re scans the landscape and shows you how that new strategy maps onto real, concrete companies. If there are not enough high fit targets, that is immediate feedback that the thesis may need refinement before you spend months chasing deals that do not exist.⁵¹

In other words, AI becomes a strategy stress test and execution engine, not a substitute for leadership judgment.

6. What This Means for the Future Corp Dev Team

As AI continues to mature, the Corp Dev role is shifting in subtle but important ways:

From list builders to portfolio designers. Instead of manually compiling lists of targets, leaders orchestrate AI tools to design and maintain a dynamic universe of potential deals that map tightly to strategic priorities.
From ad hoc screening to consistent scoring. Target triage becomes more standardized and transparent, which helps align business units, finance, and the C suite around why some deals move forward and others do not.
From reaction to foresight. With always on scanning and intent signals, Corp Dev can spot patterns and engage targets before a banker calls or an auction launches.
From “AI as a side project” to “AI woven into the workflow.” The teams that win will be the ones that marry robust corporate strategy with AI native execution tools like sc0red, using them to turn high level growth ambitions into precise, prioritized, and actionable pipelines.

For Corp Dev leaders, the message is clear: AI will not replace your strategic judgment, but peers who pair strong strategy with strong AI will out execute you.

About the Author

Zack Walmer

Zack Walmer is the co founder of sc0red and has more than 15 years of experience helping organizations grow through both organic initiatives and M&A. Before launching sc0red, he co founded Geigsen Group, where he worked with leadership teams to connect strategy, operations, culture, and people. At sc0red, Zack focuses on building partnerships and applying AI to make complex buying decisions like M&A and vendor selection faster, clearer, and more objective.

References

Walmer, Z. & Menapace, J. (2025). “Navigating the M&A Technology Landscape.” sc0red Insights. https://www.sc0red.com/insights/navigating-the-tech-landscape ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶ ↩⁷ ↩⁸ ↩⁹ ↩¹⁰ ↩¹¹
Deloitte. (2025). “2025 M&A Generative AI Study.” https://www.deloitte.com/us/en/what-we-do/capabilities/mergers-acquisitions-restructuring/articles/m-and-a-generative-ai-study.html ↩
Bain & Company. (2025). “Generative AI in M&A: You’re Not Behind Yet.” https://www.bain.com/insights/generative-ai-m-and-a-report-2025/ ↩ ↩² ↩³
MIT Project NANDA. (2025). “The GenAI Divide: State of AI in Business 2025” (coverage summary). The Times of India Tech News. https://timesofindia.indiatimes.com/technology/tech-news/mit-study-finds-95-of-generative-ai-projects-are-failing-only-hype-little-transformation/articleshow/123453071.cms ↩
Midaxo. (2023). “How AI Can Enhance M&A Deal Sourcing.” https://www.midaxo.com/blog/how-ai-can-enhance-ma-deal-sourcing ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶
Inven. (2025). “AI for M&A: How to Use AI to Find Targets and Improve Deal Sourcing.” https://www.inven.ai/articles/ai-for-ma-deal-sourcing ↩ ↩² ↩³
Grata. (2025). “Corporate Development M&A Platform & Software.” https://www.grata.com/dealmaking ↩ ↩² ↩³
EY. (2024). “How AI will impact due diligence in M&A transactions.” https://www.ey.com/en_ch/insights/strategy-transactions/how-ai-will-impact-due-diligence-in-m-and-a-transactions ↩ ↩²
E78 Partners. (2025). “AI and the M&A Process.” https://e78partners.com/blog/ai-and-the-ma-process/ ↩ ↩²