The argument lands bluntly: AI didn't hollow out SaaS margins, flawed pricing and revenue management did.

That thesis drives an opinion piece published on jpost.com. The author reframes the current margin-compression narrative in software, telling operators to look inward at how they price, package, and renew rather than blame generative AI for eroding profitability.

Why does the AI-blaming narrative persist?

Public market analysts have spent recent quarters warning that AI features would commoditize core SaaS workflows. The fear runs like this: foundation-model wrappers and vertical AI tools compress pricing power, forcing incumbents to discount aggressively while expansion revenue evaporates.

The opinion rejects that storyline. The piece frames AI as a convenient scapegoat that distracts boards from harder, internal problems: misaligned packaging, opaque discounting, neglected price increases, and revenue teams operating on stale assumptions about willingness-to-pay.

Where SaaS pricing typically fails

The framing implies recurring failure modes that erode SaaS gross margin long before any AI competitor enters the market:

• Seat-based models that decay as buying committees shrink. Procurement pools licenses, per-user activity drifts downward, and vendors that resist migration to outcome- or consumption-based pricing watch retention metrics erode across multi-year horizons.
• Discounting without guardrails. Sales-led motions hand out deep discounts off list without tracking margin by deal. Without discounting floors tied to gross-margin targets, list price becomes fiction.
• Price increases deferred through renewals. Companies that skip annual list increases to "protect retention" often discover churn doesn't improve—and they've trained customers to wait for the next markdown.
• Revenue operations disconnected from product. When pricing changes ship without telemetry on adoption and value delivery, finance eventually writes down deferred revenue.

What should product managers do on Monday?

The implication for PMs is that margin protection has become a product-management responsibility, not a finance cleanup job. Three shifts the thesis implies:

1. Treat pricing as part of the product roadmap, not a sales-enablement afterthought. Repackage tiers around measurable customer outcomes and sunset SKUs that confuse buyers.
2. Instrument the discount waterfall. If average discount across new bookings is material relative to gross-margin targets, the product likely has positioning problems that sales is hiding.
3. Tie renewals to quantified value. Track realized ROI per cohort. If customers cannot articulate the dollar value they get from your product, your renewal motion is a margin donor, not a margin protector.

When does the "it's not AI" argument fail?

The framing is strongest for horizontal SaaS incumbents with mature GTM motions. It weakens in three situations:

• Pre-PMF vertical SaaS where AI features genuinely change the workflow. Here, AI is a margin headwind, not a scapegoat, because unit economics rely on differentiation the model erodes.
• Pure API or infrastructure businesses where compute costs have risen because of model serving expenses. Margins compress from input-cost pressure, not pricing.
• Companies whose customers build in-house AI replacements. That is a substitution threat, not a pricing problem.

Product leaders should treat the opinion as a corrective to lazy AI-narrative thinking, not a universal exoneration.

Where product practice is heading

Pricing and packaging competence will separate durable SaaS businesses from the rest. Expect PM job descriptions to list monetization, packaging strategy, or price optimization as core duties by 2026, alongside discovery and roadmap work. Companies that cannot defend unit economics through a cycle of AI commoditization will face the question this jpost.com opinion forces: was it ever really AI, or was it always us?