VEEVA SYSTEMS : Pourquoi l'IA va détruire ces actions SaaS en bourse

Business impact of AI on SaaS (seat-based pricing)

• Core question: What happens to SaaS economics when AI reduces “users” (employees who log in), not “customers” (companies)?
• Modern B2B SaaS typically charges per seat / per employee via a Software-as-a-Service (SaaS) model, creating two “exceptional” economic properties:
  • Recurring revenue: if the customer stays, revenue repeats annually.
  • Revenue scales with workforce: more employees → more seats → more revenue.

How AI “agents” challenge seat economics

• If AI can complete work autonomously, the client may need fewer humans.
• Under seat-based billing, fewer employees can mean fewer billable seats → economic erosion.

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Framework / playbook: the “right” next pricing model for survivorship

The speaker argues that survivors will shift from selling access to selling work/outcomes, but only if two conditions are met.

1) New monetization direction

• Move from tool licensing (software billed at HQ / per seat) to work/result monetization.
• Example framing: AI agents process cases; the customer pays per document processed or pharmacovigilance case resolved.

2) Two gating conditions to make result-based billing viable

• Proprietary data
  • Unique to the incumbent; not starting from scratch like generic models.
• Regulatory criticality / cost-of-failure alignment
  • In regulated domains, classification or process errors can cause:
    • authorization delays
    • multi-year impacts
    • large financial losses
  • Clients will entrust work only to vendors that share/understand the cost of failure.

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Viva Systems as the main case study (pharma SaaS → AI agentic work)

Company described

• Industry: pharmaceutical lifecycle / compliance software
• Use cases:
  • Clinical trial management
  • Regulatory compliance
  • Pharmacovigilance (adverse drug effect monitoring)
• Positioning: described as a “near sectoral monopoly”
• Margins: ~45% operating margin
• Growth (reported):
  • Q1 FY2027 revenue: $883M, +16% YoY (speaker notes “nothing to report” on the surface)

The strategic pivot: “Falcon” (AI agent + outcome pricing)

• Founder Peter (Peter Gasner mentioned) spends most of the results discussion on Falcon.
• Key business model change: Falcon is not billed like the old headquarters tool.
• Falcon is billed based on:
  • documents processed
  • pharmacovigilance cases resolved

Business rationale

• Pharma currently generates ~100M documents annually from clinical trial sites that must be verified/classified by humans using Viva tools.
• The thesis: agents do the work, humans shift to higher-value tasks, and Viva earns based on processed/resolved work, capturing value even if workforce shrinks.

Why cannibalize the old SaaS model?

• Logic presented:
  • If Viva doesn’t do the agentic conversion, a competitor will or clients build their own agents on general models.
• Therefore the choice is framed as:
  • cannibalize yourself and capture the new economics
  • vs. be cannibalized by others and lose the old revenue stream.

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Actionable investor/operator checklist (“Which product drives growth?”)

The speaker emphasizes analyzing what customers are actually buying and whether revenue is at risk from AI-driven automation:

• Ask whether the company sells:
  • “doomed seats” (revenue linked to headcount/user activity), or
  • “irreplaceable work” (revenue linked to outcomes that remain necessary even as humans decline)

Dissection inputs (the “prompt library” / Top Invest promise)

• What the product does for the customer
• Who uses it (and whether AI changes the user base)
• Why the product cannot leave (switching costs / lock-in)
• Revenue model and economic units
• Product-specific risks

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Quantitative highlights and targets (as presented for Viva)

(These are valuation/expectation figures from the speaker, not formal guidance.)

Profitability and margins (high level)

• EBITDA margin roughly around ~30%
• Prior low of ~18% (timeline referenced around 2022 for an inflection/circumstance)
• Speaker notes positive margin trajectory and discusses stability/growth in margins.

Operating leverage assumption

• The company “can literally double in size by 2030”
• This implies average growth ~15% (per speaker)

SBC / earnings normalization

• Stock-based compensation (SBC) mentioned as ~14.45%
• Speaker assumes SBC may become less problematic due to AI productivity gains, but tests scenarios:
  • Conservative: keep SBC similar
  • “Remove SBCs” case: assumes SBC ~15% under a different normalization approach

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Valuation range (profit multiple method)

• Typical multiple asserted: 20–25x profits
• Scenarios:
  • If “remove SBCs,” profits normalization is estimated, then:
    • apply 20x and 25x
• Final implied price points discussed:
  • ~$284 “with” assumptions including net cash logic (speaker’s stated target)
  • current price referenced around $164 in one comparison scenario
  • another “minimum” anchor around $228 (minimum multiple case)

Balance sheet / cash

• Speaker claims ~26% cash relative to market cap
• Argument: the company could buy back a large fraction of market cap with cash (framed as “buy back 26% of its market capitalization”)
• Adds net cash adjustment to valuation but also says he may not fully rely on it.

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Buyback / shareholder return

• Buybacks described as “timid” now, with potential acceleration due to strong net cash.

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Bottom-line business thesis

• SaaS survivability depends less on “pretty growth” and more on:
  • whether revenue is tied to an AI-resistant unit of value (data + regulatory criticality + outcome/work processing)
• Speaker’s claim:
  • A conversion to digital labor billed on results could be the most profitable model of the next decade—if the two conditions (proprietary data + regulated criticality) are satisfied.

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Presenters / sources

• Presenter / speaker: narrator/investor commentator (no name given in the subtitles)
• Company executive/source referenced:
  • Peter Gasner (founder of Veeva Systems, mentioned by name)
  • Financial director of Veeva Systems (referenced as stating Falcon revenue would be “almost intangible” this year)
• Company referenced: Veeva Systems (Veeva)