AI Ripple Effects: Dark Clouds Over Conga Loan Deal, Lessons from Deutsche Bank's $1.2 Billion Deal

New tensions are rippling through international financial markets. A $1.2 billion (approximately ¥180 billion) financing deal for software company Conga, led by Deutsche Bank, is facing unexpected obstacles. These obstacles stem from nothing less than deep market concerns over the "rapid evolution of AI (artificial intelligence)."This case suggests more than just a delay in a financing deal; it points to fundamental shifts in M&A, private equity (PE) investment, and even the valuation metrics for the entire software industry.

Colunga is a leading provider of solutions in the "revenue operations" domain, covering sales proposals, contract management, and quoting (CPQ). However, lenders have raised significant concerns that its business model could become obsolete in the future due to cutting-edge AI technologies, including generative AI, or at the very least, be forced to undergo major transformation.Specifically, lenders are demanding higher yields, stricter lending terms, and more robust protections against future business risks, making deal closures difficult.

Why is AI having such a profound impact on financial markets, particularly the leveraged finance market? The backdrop is the dramatic improvement in AI's ability to automate and optimize specific tasks, potentially upending the value proposition traditionally provided by software.Lenders are increasingly prioritizing AI-driven disruption risks when evaluating the long-term competitiveness and profitability of their borrowers. The Colonga case highlights an urgent challenge for financial professionals: how to accurately assess a company's true value in the AI era.

This situation is particularly pronounced in lending to companies acquired by private equity (PE) funds (portfolio companies).PE firms acquire companies using high leverage, aiming to accelerate their growth for returns. However, the drastic changes in the business environment driven by AI could jeopardize these growth scenarios themselves. In other words, the Colonga case can be seen as a symbolic example that could significantly impact PE M&A strategies and the associated debt financing approaches.

The Transformation Era for Software Companies: Pressure on Business Models from AI

The Colonga case highlights the reality that the entire software industry is entering an unprecedented period of transformation. Particularly in areas like Revenue Operations, Customer Relationship Management (CRM), and Contract Lifecycle Management (CLM), AI-driven automation and advanced analytics are among the most anticipated innovations. AI has the capability to dramatically streamline sales representative workflows, automate contract creation and management processes, and instantly analyze customer data to propose optimal strategies.

Specifically, AI is pressuring software companies' business models in the following ways:

• Automation and Efficiency: Functions traditionally provided by software to support manual or routine tasks can now be highly automated by AI. This enables equivalent or better results with fewer resources, diminishing the competitive advantage of existing solutions.
• Evolution of Personalization: AI can deeply understand customer data and deliver experiences optimized for individual customers. This creates more sophisticated customer needs that traditional, one-size-fits-all solutions cannot adequately address.
• Intensifying Competition: Startups are rapidly launching new services with AI natively integrated, forcing existing software vendors to constantly innovate. AI evolves extremely quickly, creating a risk of becoming obsolete almost overnight if one pauses.

Lenders keenly sense these dynamic market shifts. The era where stable historical revenue models and customer bases alone secured sufficient valuation has ended. They now demand detailed explanations and concrete roadmaps outlining how companies will integrate AI technology into their strategies to maintain and enhance competitive advantage.

This shift directly impacts M&A strategy. Private equity funds and strategic investors will evaluate software companies under consideration more rigorously than ever before, assessing whether they are "AI-proof" or capable of leveraging AI to create new growth opportunities. Companies with insufficient AI investment or technology integration may face reevaluation of their value and, in some cases, exclusion from investment consideration. Colunga's financing difficulties are a clear signal that these new evaluation criteria have already permeated financial markets.

New Winds in the Leveraged Finance Market: Lender Caution and Tightening Conditions

Colunga's financing difficulties symbolize a new trend spreading across the entire leveraged finance market. Lenders, once relatively lenient toward software companies with growth potential, are now rigorously scrutinizing deals through the new lens of "AI risk." This signifies a significant shift in market sentiment.

Lenders are beginning to take the following specific actions:

• Demand for Higher Yields: Lenders are demanding higher returns (yields) for deals perceived as carrying increased risk. This translates to higher funding costs for borrowing companies.
• Tightening of loan covenants: Loan agreement terms, such as financial metric targets and disclosure obligations, are becoming stricter. This may reduce the financial operational flexibility of companies.
• Enhanced Due Diligence: Beyond traditional financial analysis, detailed investigations using AI will be conducted into business model disruption risks, corporate AI strategies, and technological competitive advantages. The importance of expert technical due diligence is increasing.
• Shortening of Loan Terms: In highly uncertain market environments, lenders tend to shorten loan terms to avoid long-term risks.

This trend directly impacts the M&A market, particularly PE buyout deals. Since PE funds often finance the bulk of acquisitions through leveraged loans, stricter lending conditions and rising costs can suppress acquisition prices and make deals harder to close. Consequently, M&A activity in the software sector may shift toward a more cautious stance.

Historically, SaaS (Software as a Service) companies boasting high growth rates could often secure substantial financing, even with some losses, based on their future potential. However, the seismic shifts brought by AI are forcing a correction to this "growth-first" mindset.Lenders are increasingly prioritizing not just short-term growth, but also medium-to-long-term sustainability and resilience against AI. Companies unable to adapt to this market shift may face an era where securing funding itself becomes difficult.

Proposals for the Future: Software Investment and M&A Strategies in the AI Era

The challenges highlighted by the Colunga case extend beyond a single company's financing issues; they represent a common theme facing all software companies and their investors in the AI era. To thrive in this new financial and business landscape, innovative approaches that transcend traditional paradigms are essential.

The strategies software companies should adopt are diverse, but the following points are particularly crucial:

• Clarifying and Executing AI Strategy: Companies must clearly define how they will integrate AI into their products and services to create new value, and swiftly move to execution. Crucially, AI must be viewed not as a "cost center" but as a "source of competitive advantage."
• Strengthening Resilience: Build business models resilient to AI-driven disruption. This means fostering long-term customer loyalty through diverse value offerings and customer engagement, rather than relying on specific functions.
• Enhancing Data Utilization Capabilities: The evolution of AI heavily depends on high-quality data. How efficiently a company collects, manages, and analyzes its own data to improve AI model accuracy will determine its competitiveness.
• Investment in Continuous Innovation: AI technology advances rapidly. Companies must actively pursue the latest trends and maintain a commitment to investing in research and development.

For investors, particularly PE funds and corporate buyers considering M&A, the Colonga case offers critical lessons.

1. Deepening Due Diligence: Due diligence must extend beyond financial and legal aspects to include technology, particularly AI strategy, more rigorously than ever. It is crucial to assess how the target company plans to address AI threats and whether those plans are realistic.
2. Revisiting Valuation Models: Beyond traditional revenue and EBITDA multiples, a more multifaceted valuation model is needed. This model must incorporate AI-driven future growth potential, disruption risks, and the cost-saving effects of AI implementation.
3. Post-M&A Strategy Reconstruction: During post-acquisition integration, the swift implementation of AI technology and the creation of synergies with existing operations will be more critical than ever to success.

The financing deals by Deutsche Bank and Colunga are striking examples demonstrating how seriously financial markets are taking AI's impact. This heralds the dawn of a new era where software companies are compelled not just to grow, but to answer the fundamental question of "how to survive in the AI era." We may now stand at a historic turning point in the world of M&A and investment.