AI is changing the economics of software companies. Capabilities that once justified a premium are increasingly available through general-purpose models and agents at a fraction of the cost. As these features become easier to replicate, traditional software businesses face a growing challenge: differentiation erodes, pricing power weakens, and customers begin to question what they’re really paying for. Against that backdrop, a necessary question emerges for B2B SaaS leaders: which parts of your product features are being replaced or augmented by AI, and does your pricing still match the value customers actually receive?
To answer that, start by mapping your product to outcomes and label each as commoditized, augmented, or differentiated by AI. In practice, this means bucketizing your product into the following groups:
Commoditized: Capabilities such as searching uncurated content, summarizing, classifying routine items, and basic content generation are losing value as LLMs, retrieval-augmented systems, and workflow agents increasingly replace them.
Augmented: Areas where AI accelerates workflows, such as pre-filled drafts, ranked actions, but your platform still supplies context, orchestration, or human verification.
Differentiate: Where you control proprietary first-party data, deep integrations, security/compliance, or other areas where generic AI performance struggles.
Next, reevaluate your pricing metric: if seats, transaction counts, or manual-hours tie revenue to usage that AI reduces, revenue will likely fall despite maintained or improved customer KPIs. Consider outcome-based models (per saved FTE, per dollar retained), hybrid structures (base subscription plus usage), or tiered offerings that separate a low-cost AI-first self-serve from premium enterprise plans emphasizing governance and certified data.
Move fast but experiment. Run customer interviews to surface outcomes the market values, instrument telemetry linking features to KPIs, and pilot pricing and product experiments with cohorts. Track ARR retention, expansion, churn, NPS, and margin.
AI disruption is a catalyst to clarify value. Companies that precisely identify what remains differentiated, align pricing to outcomes, and run disciplined pilots can defend and even grow value in the next era.
