M&A: AI & Vertical SaaS Consolidation
The market dynamics fueling opportunity for M&A across artificial intelligence & vertical SaaS
Despite broader economic uncertainties that have somewhat muted deal flow, our outlook for M&A, specifically across AI and vertical SaaS, remains positive heading into the mid and back-half of 2025. We believe factors such as the growing AI talent shortage, market redundancies and fragmentation, and EV multiple compressions will present compelling opportunities for consolidation across the private markets in AI and vertical SaaS.
Generative AI Market Structure
Global demand for Gen AI products and services is expanding rapidly. In 2024, the overall market was estimated at $25.8 billion, is projected to reach $37.9 billion in 2025, and to surpass $1 trillion by 2034, growing at an approximate 44.2% CAGR. We segment the sector by 3 categories: [1] Hardware: the infrastructure used to train and deploy artificial intelligence such as GPUs, specialized CPUs, custom silicon (TPUs, LPUs, IPUs), along with all of the upstream fabrication and components required to build these chips (Broadcom, Micron, TSM, AMD, etc.) [2] Foundational Models and Platforms: core large language models (LLMs) and the platforms used to manage and deploy them. This category encompasses early leaders like ChatGPT (OpenAI), Gemini (Google), and Claude (Anthropic) as well as AI platforms like Google’s Vertex AI, Amazon SageMaker, Amazon Bedrock, and Azure Machine Learning. While we see moderate fragmentation across this segment, we believe the most significant opportunity for consolidation lies within the AI application and services layer. [3] Gen AI Applications and Services: AI embedded software designed to solve vertical-specific business problems and the consulting, systems integration, and staffing firms providing related professional services. This segment showcases significant redundancy, comprised of hundreds of vertical AI SaaS solutions and services. We believe these technologies can be deployed to drive operational efficiencies, transform legacy business models, enhance decision-making, and ultimately boost returns for enterprises across verticals, setting the stage for buy-and-build bolt-ons, roll-ups, acquihires, buyouts, and carve out strategies.
M&A Dynamics and Drivers
In our view, the influx of venture capital across the AI sector is a primary catalyst for M&A consolidation. Global VC funding hit $121 billion in Q1 2025, the highest quarterly total in nearly three years. Gen AI startups attracted $56 billion across 885 deals in 2024, a 192% increase from 2023. While a significant portion of this funding was concentrated in mega-rounds ($100 million+) accounting for 69% of total funding, early-stage deals (Seed, Series A) constituted 74% of transaction volume, with the early-stage median deal size reaching a record $2.7 million in Q1 2025. Many of these AI startups raised on aggressive valuations when the market was up and to the right, spanning anywhere from 10x-50x revenue multiples. In comparison, traditional public SaaS revenue multiples peaked near 20x revenue during the 2021 boom, then compressed sharply, falling to lows around 4x-5x in late 2024 before showing signs of stabilization around 6x-7x revenue in early 2025. In light of recent market compression, many of these startups now face a finite runway after burning through these raises, and will be challenged to raise additional capital at previous valuations (“down round”). These dynamics create challenges for both the company and its existing investors, opening the door for alternative transaction structures such as earn outs, equity rollovers, or collars.
We also view AI as a dual purpose competitive advantage in achieving cost cutting efficiencies and new revenue growth post transaction. Traditional post-merger integration activities like streamlining overlapping functions, consolidating operations, optimizing infrastructure, and achieving economies of scale in areas like procurement and R&D can be enhanced through a mix of LLMs, OCR, time-series, and co-pilots, while revenue generating operations can be improved from cross-selling complementary products or services to an expanded customer base, accessing new market segments, enhancing value propositions, and generating new GTM insights from aggregated data assets.
The Evolving Regulatory Landscape
AI-specific regulatory frameworks like the EU AI Act have imposed compliance obligations on AI systems deemed high-risk. These requirements cover areas like data governance, transparency, human oversight, accuracy, and security, adding significant compliance costs and overhead to application development. Global antitrust authorities are increasingly concerned about the risk of market concentration in the AI sector, placing focus on the accumulation of data, computational power, and talent through monopolistic practices. We anticipate M&A transactions, especially larger deals or those involving "killer acquisitions" with the potential to stifle innovation will likely face heightened scrutiny. Finally, as AI is increasingly classified as a critical or strategic technology, cross-border transactions involving AI will be subject to growing regulation under national FDI regimes, resulting in lengthier reviews, conditional approvals, or even outright blocks in sensitive sectors.
Important Information and Disclosures
The views expressed in this presentation are attributable solely to the author, Nick Alonso, in his individual capacity. They do not necessarily represent the collective view, official stance, or investment strategies of Songster Capital LLC or its affiliated entities ("Songster Capital").This content been prepared solely for informational purposes as of May 8, 2025. It should not be interpreted as constituting investment research or a formal recommendation. Furthermore, nothing herein should be construed as investment, legal, tax, or other professional advice, nor is it an offer to sell or a solicitation of an offer to buy any security, financial instrument, or investment product. Readers are encouraged to use this information as merely one component of their own independent assessment and should not rely solely upon it for making any investment or financial decisions.The views presented reflect the author's perspective at the time of writing and are subject to evolution based on changing market conditions or other factors. There is no obligation, express or implied, on the part of the author or Songster Capital to update this information or notify readers of any changes to the views expressed. Any use of terms like "we" or "our" relates to the author and/or Songster Capital as the specific context requires.Please be advised that the commentary provided does not pertain specifically to any Songster Capital investment product or management strategy. Songster Capital and its personnel, potentially including the author, may engage in investment activities, advise clients, hold financial interests (long or short), or formulate recommendations that diverge significantly from, or are contrary to, the perspectives shared in this document. Assumptions made or techniques described by the author may not be utilized in managing client accounts or firm capital.While information presented is gathered from sources believed to be reliable, its accuracy, completeness, and timeliness cannot be explicitly guaranteed by Songster Capital or the author. Any statements anticipating future events, market movements, or performance are inherently speculative, based on current assumptions, and involve significant risks and uncertainties; actual outcomes may vary substantially from any projections or expectations discussed.All investments carry inherent risks, including the potential loss of capital. Past performance is not a reliable indicator or guarantee of future results. The suitability of any investment theme or strategy discussed herein depends heavily on individual investor circumstances, objectives, and risk tolerance.Neither Songster Capital nor the author accepts any responsibility or liability for any direct or consequential loss or damage arising from the use of, or reliance upon, this information, or for any errors or omissions contained within it. By accepting this presentation in its entirety, the recipient acknowledges its understanding and acceptance of the foregoing statement.