Margin Expansion for Software Companies: AI as a Catalyst for Deeper Efficiencies

Our analysis of 111 publicly traded enterprise software companies* found that 57% improved gross margins by at least one percentage point in the past year. Yet there’s still room to grow: The median gross margin remains at 74%, falling below our benchmark range of 75% to 85%. In the last two years, many companies have made tough decisions to optimize major cost drivers—cloud hosting, sales and marketing, support, and labor. Now, AI is adding a new dimension to this equation.

Software companies are embedding AI into their products at a rapid pace, both to enhance their offerings and improve internal efficiencies. Some Examples: Salesforce’s AgentForce, Zendesk AI, and Sierra.AI.

AI’s potential is undeniable—but it also shifts the cost structure in ways many software companies haven’t fully accounted for. In the rest of this article, we'll explore how AI impacts cost structures and highlight specific strategies to optimize spending and drive sustainable margin expansion.

*with revenues between $250 million and $2 billion, October 2024

Re-Evaluating Cost Structures for AI Profitability

Done right, AI can drive efficiency, lowering the cost per release while improving quality, speed to market, and competitiveness. West Monroe’s own Product Engineering team has seen over a 20% productivity boost from AI-assisted code generation alone.

However, AI doesn’t interact with infrastructure the same way traditional software does. AI workloads have unique computing, storage, and model-serving requirements that alter costs—sometimes significantly. Many software companies don’t yet have a firm handle on the true cost of providing AI services or how AI changes their development and support models.

Finding More Margin in Cost of Goods Sold: Cloud, Product, and Service Efficiency

Software COGS includes cloud and DevOps costs, customer support, licensing, and other essential services. Benchmarking helps companies gauge efficiency across these areas. Today, COGS accounts for 15% to 25% of revenue for most software firms, yet our analysis found that 46% of companies operate below the median gross margin of 74%—suggesting untapped opportunities to optimize.

A $700 million ERP software provider, for example, restructured its cloud usage, re-architected key products, and streamlined service delivery. The result? A 14-percentage-point increase in gross margin.

Here are three areas often ripe for cost improvement:

1. Cloud Cost Optimization

Cloud spend continues to rise, making it a major target for efficiency. Leading cloud-based SaaS companies keep their cloud spend between 5% and 8% of revenue—a level many companies can move toward with focused effort. Strategies include:

• Eliminating underutilized instances and redundant backups
• Leveraging variable cost models, such as pay-as-you-go contracts based on transaction volume
• Establishing a FinOps team to ensure cross-functional oversight, track spending, and enforce scalable cost management practices

2. Product Architecture

A modernized product architecture reduces hosting, implementation, and support costs. To assess efficiency, software leaders should ask:

• Is our architecture built for scalability (e.g., microservices)?
• How could we streamline or re-architect products to cut costs while maintaining performance?

3. Service Delivery Efficiency

Many software companies can reduce service-related costs by:

• Rebalancing onshore, nearshore, and offshore delivery teams
• Optimizing spans of control within customer support and professional services teams
• Automating support processes with AI and self-service tools to reduce labor costs

Rethinking R&D for Growth and Efficiency

Software companies often lose efficiency by investing in the wrong features and product bets. Our research shows that only 19% of public software companies reduced R&D spend as a percentage of revenue by at least one percentage point in the past year, and nearly half spend above the 22% median R&D-to-revenue ratio—a sign that many could optimize further.

To sharpen R&D efficiency, software firms must move beyond traditional developer productivity metrics like DORA and SPACE, which focus narrowly on engineering velocity. Instead, a balanced scorecard approach that aligns product investments with business outcomes is more effective.

One $550 million customer experience software provider, for instance, consolidated product platforms after a merger and added automation to accelerate new feature rollouts. These efforts cut $30 million from its run rate while improving product focus.

Key areas for R&D efficiency improvement:

1. Product Development Labor Optimization

• Optimize onshore, nearshore, and offshore talent mix
• Improve spans of control: a best-in-class software team has an SOC of 5:1 or higher, while inefficient structures hover at 2:1 or 3:1
• Eliminate unnecessary middle management layers

2. Software Development Lifecycle Optimization

• Increase automation to streamline backlog management, QA, and release processes
• Use AI to boost coding efficiency, testing, and deployment

3. Platform Consolidation

Private equity-backed software companies often inherit multiple platforms through acquisitions. AI-driven product innovation offers an opportunity to rationalize platforms, cutting costs while aligning resources with the highest-value offerings. Companies should prioritize:

• Market-fit and profitability over platform redundancy
• Standardizing and consolidating technology stacks for efficiency gains

The Key to Sustainable Margin Expansion: Continuous Optimization

Margin expansion isn’t a one-time exercise—it’s an ongoing discipline. The next round of optimizations will require a scalpel, not a hammer—precise, data-driven adjustments rather than broad cost-cutting measures.

Making cost optimization a continuous effort is the best way to stay ahead. Software companies that benchmark regularly and apply structured cost analyses will be better positioned to capture AI-driven efficiencies, enhance portfolio value, and maintain long-term profitability.

Authored by: Hubert Selvanathan and Dhaval Moogimane