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Article

Efficient Growth for Software Companies: AI as a Catalyst for Deeper Efficiencies

February 06, 2025

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Software companies have long worked to balance growth with profitability. While top-line expansion remains a priority, competitive pressures and a shifting macroeconomic environment have made it harder to hit growth targets. That’s why margin expansion is taking center stage.

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.

To scale AI-powered products profitably, companies must reevaluate their cost structures. That means taking a hard look at cost of goods sold (COGS) and R&D investments, using AI as a catalyst to unlock greater efficiencies.

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

Key areas for R&D efficiency improvement:

1. Product Development Labor Optimization

  • Optimize onshore, nearshore, and offshore talent mix; ensure the choice of location strategy for product and R&D is optimized for fast time to market, collaboration, and efficiency
  • 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
  • Ensure release strategy and version support policies are consistent across the portfolio and balances needs of installed base with cost to serve considerations

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
  • Leveraging AI tools to accelerate platform modernization efforts such as code conversion and data migration

The Key to Sustainable Efficient Growth: Continuous Optimization

The shift to efficient growth won’t occur at a single point in time. 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