The State of Deal Sourcing in Private Markets

Introduction

The influx of capital, the rise of new data technologies, and the evolving expectations of sellers have reshaped the way private equity sponsors, corporates, bankers, and consultants identify and pursue opportunities.

Where banker-led auctions once dominated, today’s sourcing toolkit spans AI engines, proprietary relationship-building, speed-driven process advantages, and thematic specialization. This report synthesizes evidence from our proprietary microsurveys, research on acquisition likelihood, industry articles, and the five charts provided.

Technology Enters the Deal Sourcing Arena

Artificial intelligence is no longer a peripheral experiment; it is being actively embedded into sourcing and decision-making processes. Firms increasingly use AI to monitor signals of company performance, automate screening, and compress diligence timelines. While adoption is highest in diligence and portfolio monitoring, sourcing is catching up rapidly.

This chart demonstrates the growing integration of AI across investment functions. For sourcing, the challenge has been the messy, unstructured nature of early-stage signals. Yet the reward is substantial: the ability to detect potential targets months earlier than traditional processes allow. AI does not replace relationships, but it amplifies coverage and prioritization. Importantly, empirical evidence shows that companies displaying faster growth, higher leverage, lower liquidity, greater profitability, and larger revenue bases are far more likely to become acquisition targets. AI-driven models that rank companies on these dimensions raise hit rates and improve efficiency, converting sourcing from guesswork into probability-weighted opportunity identification.

Platforms Industrialize Origination

The maturation of deal sourcing software has industrialized what was once a craft reliant on Rolodexes and conferences. Specialized platforms now index private company data, scrape signals from across the web, and integrate seamlessly into CRM systems.

From universal databases like PitchBook and CB Insights to niche engines such as Grata and Sourcescrub, these platforms do not merely add names; they classify companies by vertical, signal founder intent, and update dynamically as new data emerges. Corporate development teams use them to map adjacencies, while PE sponsors deploy them to discover under-the-radar assets. The trend is clear: sourcing is becoming a process that blends machine-augmented discovery with human-led trust-building.

The Shifting Sources of Deal Flow

As technology rises, it competes directly with traditional relationship-driven and auction-led deal flow. A recent survey reveals how professionals perceive the balance of sourcing channels in the future.

The data of our survey tells a compelling story: technology-enabled sourcing and proprietary relationships are tied as the most promising channels, each at 26 percent of responses, while banker-led auctions lag far behind. Bankers themselves are the most bullish on technology, underscoring how closely those at the funnel’s mouth see its potential. Corporate development teams lean most heavily on founder-led opportunities, reflecting their strategic alignment priorities. Private equity sponsors, by contrast, still exhibit loyalty to auctions, with half citing them as their dominant channel. The divergence highlights a bifurcated sourcing ecosystem—tech-driven discovery on one side, relationship-led trust on the other.

Proprietary Access as the Ultimate Prize

Despite the rise of AI and platforms, proprietary deal flow remains the most coveted and the most difficult to secure. Proprietary transactions reduce competition, improve pricing, and build alignment between buyer and seller. Yet, they are increasingly scarce.

The insight chart shows that accessing proprietary opportunities outranks all other sourcing difficulties, with PE sponsors most acutely feeling the pain. The definition of “proprietary” has also shifted: as more firms employ outbound origination teams, fewer opportunities remain untouched. For this reason, trusted networks and thematic credibility are more important than ever. To consistently access proprietary flow, firms must professionalize origination with dedicated teams, structured playbooks, and scalable adviser networks.

Competitive Edges in Sourcing

If proprietary access is the hardest to achieve, what advantages give firms the ability to win when opportunities do appear? Our microsurvey asked professionals to identify their firm’s greatest sourcing edge, and the results reveal how advantage is diversifying.

Relationships remain central, especially for corporate development professionals, who overwhelmingly rely on founder trust. Bankers emphasize speed and decisiveness, recognizing the power of certainty in competitive processes. Consultants highlight AI and data tools, aligning with their mandate to systematize opportunity discovery. Sponsors lean toward specialization, knowing that thematic depth and credible theses open doors in crowded spaces. The mosaic of responses underscores that no single edge dominates. Success comes from the ability to combine multiple advantages: technology for coverage, relationships for trust, specialization for credibility, and speed for execution.

Challenges, Constraints, and Organizational Design

Operational realities add another layer of complexity. Network-building, sustaining sourcing velocity, and resource constraints are persistent challenges across firms. Corporate development teams often lack the bandwidth to maintain extensive networks. Bankers, meanwhile, face intense process-driven pressure to deliver speed. Consultants grapple with balancing analytical breadth against execution depth.

What unites these challenges is the need for origination to be treated as a first-class function with dedicated resources, clear metrics, and defined ownership. Firms that build repeatable processes—tracking conversion rates from first contact to second meeting, maintaining thematic pipelines, and embedding AI-driven scoring—are able to sustain velocity even with lean teams. Those that leave sourcing to ad hoc efforts or rely too heavily on legacy channels fall behind.

The Role of Financial Characteristics

The academic evidence adds rigor to these strategic findings. By identifying financial traits that consistently predict acquisition likelihood, researchers provide a blueprint that sourcing teams can embed into their models. Growth and profitability matter universally, while leverage and revenue size take on heightened importance in Europe and Asia-Pacific respectively. This empirical framework allows firms to prioritize outreach toward targets that not only fit their thesis but also display a statistical propensity to transact.

The implication is profound: deal sourcing can be simultaneously art and science. Human originators cultivate trust and credibility, while algorithms score and prioritize. Together, they create a sourcing function that is both expansive and targeted, capable of scaling coverage without diluting effectiveness.

Adaptability as the New Alpha

Perhaps the clearest conclusion from all surveys and data is that there is no single formula for sourcing. Banker-led auctions remain important but are no longer dominant. Proprietary relationships are highly valuable but harder to secure. Technology has emerged as a coequal source of deal flow. Speed, brand credibility, and specialization all matter, but differently depending on role and context.

[Insert Chart: Deal Sourcing Under Pressure: Where the Biggest Challenges Lie]

This chart brings the narrative full circle: challenges are spread across access, velocity, and networks, highlighting that fragmentation defines the sourcing environment. The firms that thrive are those capable of flexing across multiple strategies. They know when to rely on technology, when to deploy relationships, and when to press speed or specialization. In short, adaptability itself has become the decisive competitive edge—the “alpha” in private markets sourcing.

Conclusion

Deal sourcing in private markets is no longer about finding the single best channel. It is about weaving together multiple edges into a coherent operating model. Relationships continue to matter, but they must now be complemented by data science. Proprietary deals remain the holy grail, but accessing them requires industrialized processes and thematic credibility. Auctions are still relevant, but success there depends on speed and decisiveness. And technology has matured into a critical sourcing engine, raising efficiency and sharpening prioritization.

As the ecosystem fragments, the firms best positioned for the future are those that operationalize adaptability. They codify their sweet spot, deploy AI-enabled prioritization, invest in scalable networks, and maintain organizational processes that allow them to move quickly without sacrificing rigor. In an era where sourcing itself is a competition, the ultimate edge belongs to those who can evolve fastest.

Sources & References

Bain & Company. (2017). A Two-Pronged Approach to Sourcing More Private Equity Deals. https://www.bain.com/insights/a-two-pronged-approach-to-sourcing-more-pe-deals-forbes/ 

PE150. (2025). Deal Sourcing Gets a Software Update. https://www.pe150.com/p/deal-sourcing-gets-a-software-update-3e48 

PE150. (2025). Proprietary Is the New Unicorn. https://www.pe150.com/p/proprietary-is-the-new-unicorn 

PE150. (2025). The Greatest Edges in Sourcing Quality Deals. https://www.pe150.com/p/the-greatest-edges-in-sourcing-quality-deals 

Private Equity International. (2025). Could a bot find your next deal? https://www.privateequityinternational.com/could-a-bot-find-your-next-deal/ 

S&P. (2024). Deal Sourcing: A Data Science Approach - Impact of Financial Characteristics on Acquisition Likelihood. https://www.spglobal.com/market-intelligence/en/news-insights/research/deal-sourcing-a-data-science-approach-impact-of-financial-characteristics-on-acquisition-likelihood

S&P. (2024). Deal Sourcing: A Data Science Approach - Impact of Financial Characteristics on Acquisition Likelihood (Complete Report). https://www.spglobal.com/content/dam/spglobal/mi/en/documents/general/Deal-Sourcing-A-Data-Science-Approach---Zhao-and-Hauerhof---Feb.-2024.pdf