How Christina Caci Changes Trust Management at Scale with Vanta

When I saw OpenAI’s post saying that Christina Caci is reshaping how trust works at scale with Vanta, I paused for a second. Not because it was flashy, but because “trust at scale” is one of those topics everyone in SaaS nods along to—right up until the first enterprise deal stalls, a security questionnaire lands in your inbox, or a customer’s legal team asks for evidence you can’t neatly produce.

If you’ve ever tried to sell software into larger organisations, you already know the feeling: you can have a great product, great pricing, and a great team—and still lose momentum because you can’t prove you’re safe, compliant, and well-managed. In practice, trust becomes an operational system, not a slogan.

In this article, I’ll unpack what it really means to manage trust “at scale”, why platforms like Vanta matter, and how you can connect trust work to revenue—without drowning your team in spreadsheets and last-minute panic. I’ll also share how we approach this at Marketing‑Ekspercki when we build AI-assisted workflows and automations in make.com and n8n, because trust isn’t just a compliance task; it’s also a process design problem.

Source reference used for context: OpenAI posted on 22 Jan 2026: “@christinacaci is reshaping how trust works at scale with @Vanta.” (OpenAI on X/Twitter).

Trust at scale: what people usually mean (and what they often miss)

“Trust” gets tossed around as if it’s purely emotional—brand perception, tone of voice, good PR. That’s real, sure. But in B2B software, especially when you sell to serious buyers, trust becomes auditable. If a prospect can’t validate how you manage risk, your sales cycle slows down. If a customer can’t monitor your posture over time, renewals become tense. If you can’t show evidence quickly, your best people end up doing admin work.

Here’s the bit that tends to get missed: trust isn’t one thing. It’s a bundle of repeatable behaviours that need documented proof.

What “trust” looks like in a B2B buying process

• Security reviews that ask about access control, encryption, incident response, and vendor management
• Procurement steps that require standard frameworks (often SOC 2, ISO 27001, or similar)
• Ongoing reassessments, customer audits, and external risk ratings
• Clear ownership: who is responsible for controls, evidence, and remediation

If you’re smaller, you can sometimes brute-force this with a couple of sharp people and a lot of late nights. At a certain point, though—more customers, more systems, more staff—manual trust work simply stops working.

Why “at scale” changes everything

In my experience, teams struggle with scale for three reasons: evidence sprawl, ownership ambiguity, and timing.

1) Evidence sprawl

Your proof lives everywhere: cloud consoles, HR systems, ticketing tools, password managers, device management, training records, and “temporary” spreadsheets that somehow become permanent. When a customer asks, “Show me your last access review,” you don’t want to start a treasure hunt.

2) Ownership ambiguity

Trust programmes cut across departments. Security might own policies. IT owns devices. Engineering owns code and deployments. HR owns onboarding. Sales owns questionnaires. If responsibilities aren’t clear, you end up with silence, finger-pointing, and rushed work.

3) Timing (the silent killer)

Trust tasks are recurring. Reviews, attestations, risk assessments, and evidence updates need to happen on schedule. When you only remember them when a buyer asks, you operate in reactive mode—and that’s expensive.

So when OpenAI highlights someone “reshaping how trust works at scale,” I read it as a signal: the market is finally treating trust operations as a practical discipline with systems, tooling, and measurable outcomes.

Where Vanta fits in: trust management as an operating model

I’m not going to invent product claims here. What I can safely say is this: platforms like Vanta are widely associated in the market with helping organisations manage security and compliance workflows, gather evidence, and stay audit-ready. That matters because it shifts trust work from “heroic effort” to “repeatable process”.

When you operationalise trust, you aim for three things:

• Continuous visibility into important controls and security hygiene
• Faster evidence collection so questionnaires and audits don’t derail delivery
• Clear accountability so tasks land with the right people at the right time

That’s the real prize: not a certificate on a slide deck, but a system that keeps your organisation honest and predictable under scrutiny.

Who benefits when you manage trust well?

It’s easy to frame compliance as a cost centre. I get why. But when you build the right process, the value spreads across the whole business.

Sales teams: fewer stalled deals

Sales doesn’t want to become your internal messenger between a prospect’s security team and your engineers. A tidy trust programme reduces back-and-forth and helps reps maintain momentum.

Security and IT: fewer fire drills

If you’ve ever worked through an audit with missing records, you’ll know the pain. Good trust operations reduce surprises. Your team can focus on real improvements, not scrambling for screenshots.

Engineering: less disruption

Engineers hate random interruptions for “one quick question” that becomes a two-day distraction. When you systemise evidence and access, engineering stays in flow.

Leadership: clearer risk posture

Executives don’t need every technical detail, but they do need confidence that risks are being tracked and treated sensibly. A real system makes that visible.

Trust management and revenue: the connection people underestimate

In marketing and sales support, I’m obsessed with levers that improve conversion without gimmicks. Trust is one of the most underused levers in B2B growth because it affects:

• Sales cycle length (how long it takes to get to “yes”)
• Enterprise readiness (which accounts even consider you)
• Deal risk (how often procurement or security blocks the signature)
• Renewals (how safe customers feel with you year after year)

I’ve watched teams increase pipeline and still miss targets because late-stage trust requirements weren’t prepared. The painful part is that the fix is rarely “more leads”. It’s usually “better operational readiness”.

What “reshaping trust” can look like in practice

We don’t have details from OpenAI’s post beyond the headline, so I’m not going to attribute specific methods to Christina Caci. But I can describe the patterns I’ve seen in high-performing teams who treat trust as a scalable system.

Pattern A: run trust work like a product

They keep a roadmap, define ownership, measure completion, and iterate. They don’t store everything in someone’s head. They document decisions. They treat internal stakeholders as customers.

Pattern B: prioritise evidence that maps to real buying friction

They focus on what prospects actually ask for: access control, logging, incident response, vendor management, data handling, and employee onboarding/offboarding. They don’t waste time polishing low-impact artefacts.

Pattern C: reduce the “busywork tax” with automation

They automate reminders, task creation, evidence requests, and reporting. And they do it gently—enough structure to stay consistent, not so much bureaucracy that people rebel.

How we approach trust workflows with make.com and n8n (practical examples)

At Marketing‑Ekspercki, we build business automations with AI in make.com and n8n. When clients ask us for “AI automation”, I usually steer the conversation towards workflows that reduce organisational friction. Trust operations are a great candidate because they involve recurring tasks, multiple systems, and high stakes.

Below are examples you can adapt. They’re written in a tool-agnostic way, but they map nicely to either make.com scenarios or n8n workflows.

1) Security questionnaire triage and routing

Goal: stop questionnaires living in inboxes and being answered inconsistently.

• Trigger: new email with “security questionnaire” / “SIG” / “SOC 2” keywords, or a form submission from sales
• Parse: extract customer name, deadline, document link
• Create: a ticket in your task system (e.g., Jira/Linear/Asana) with a checklist
• Assign: route to the right owner based on topic (IT, security, engineering, legal)
• Assist: propose draft answers using an LLM based on your approved policy text (with strict review required)
• Log: store final answers in a controlled knowledge base so you don’t rewrite the same thing next month

Personally, I like adding a step that flags “high-risk” questions—things about incident history, sub-processors, or data residency—so they always get human review. It sounds obvious, yet teams skip it when they’re rushing.

2) Access review reminders that people actually follow

Goal: ensure periodic access reviews happen on time without nagging everyone manually.

• Trigger: monthly schedule
• Pull: list of users/groups from your identity provider (where possible)
• Compare: detect changes since last review and highlight anomalies
• Notify: send a concise summary to the system owner (Slack/Teams/email)
• Track: open a task that requires approval/attestation before it can be closed

The trick is keeping the message short. If you send a novel, people ignore it. I’ve learned to keep it to: what changed, what needs approval, and the deadline.

3) New hire and offboarding checklists with proof

Goal: make onboarding/offboarding consistent and auditable.

• Trigger: HR system event (new hire / termination) or a form submission
• Create: tasks for device setup, account provisioning, training assignment, role-based access
• Collect: evidence artefacts (timestamps, tickets, confirmations) into a single record
• Escalate: alert if any step is overdue past a defined threshold

When I’ve seen offboarding go wrong, it’s rarely malicious; it’s usually someone forgot a system. A workflow that tracks access removal across your stack can save you from that slow-burn risk.

4) “Trust page” updates driven by reality, not vibes

Goal: keep customer-facing trust information aligned with your actual practices.

• Trigger: policy updated, audit completed, or major control change approved
• Draft: a change summary for your website trust page and sales collateral
• Review: require approvals (security + legal + marketing)
• Publish: update the page and notify sales so they use the latest wording

This helps marketing avoid accidental overpromising. In enterprise sales, sloppy claims can come back to bite you in procurement.

SEO angle: what people search for when trust becomes a blocker

If you want this article’s ideas to pull organic traffic, align your content with what buyers and operators type into Google when they feel pressure. These are common themes I’ve seen perform well:

• “SOC 2 preparation checklist”
• “security questionnaire how to respond”
• “vendor risk management process”
• “how to pass security review SaaS”
• “compliance automation”
• “trust centre for SaaS”

I’m mentioning this because SEO isn’t magic. If you write elegantly but ignore search intent, you’ll get applause from your colleagues—and tumbleweeds from Google.

Building a trust programme that won’t collapse under growth

If you’re early-stage, you don’t need a huge apparatus. You do need habits that scale. Here’s a structure I often recommend when I’m advising teams.

Step 1: define your scope and your “trust boundary”

Write down what systems handle customer data, where data lives, who can access it, and who your subcontractors are. Keep it simple and accurate. You can refine later, but you can’t manage what you haven’t mapped.

Step 2: decide which framework(s) matter for your market

Different buyers expect different signals. Some look for SOC 2. Some prefer ISO-aligned language. Public sector might have its own requirements. Pick what matches your deal profile, then focus.

Step 3: assign named owners for recurring controls

I’m a big fan of explicit ownership. Not “IT”. Not “Engineering”. A person. When ownership is fuzzy, tasks become optional.

Step 4: design the evidence flow

Where does proof come from? Where will it live? How do you show it quickly when asked? This is where platforms like Vanta are often brought in, because they help reduce manual collection and keep records tidy.

Step 5: connect trust work to sales workflows

Sales needs a clear path: where to find documents, how to request exceptions, how to handle questionnaires, and when to pull in specialists. If sales improvises, you’ll get inconsistent answers—and eventually, mistrust.

Common mistakes I’d help you avoid

I’ve seen smart teams trip over the same issues. If you want a smoother run, steer away from these.

Overpromising in customer-facing material

It’s tempting to sound reassuring. Still, if your trust page says one thing and your evidence says another, you’ve created unnecessary friction. Keep claims precise and defensible.

Letting exception handling become the norm

Every business has exceptions. The problem starts when exceptions aren’t recorded, reviewed, and sunsetted. That’s how “temporary” risk becomes permanent exposure.

Keeping knowledge in DMs and meeting notes

If the person who “knows the security stuff” goes on holiday, everything stalls. Put answers and evidence in a controlled repository with clear access rules.

Measuring activity instead of outcomes

It’s easy to track “number of policies written”. Harder, but better, to track outcomes like: time-to-answer questionnaires, audit readiness, and reduction in late-stage deal blockers.

Where AI helps, and where I’d keep it on a tight leash

AI can genuinely reduce the boring parts of trust management—sorting requests, drafting boilerplate responses, summarising evidence, and highlighting anomalies. I use it for drafts all the time.

Still, you need guardrails. Trust work is high-consequence. I’d keep humans accountable for anything that goes to customers or auditors.

Good AI use cases

• Drafting first-pass questionnaire answers from approved internal text
• Summarising policies into short, readable snippets for sales
• Classifying inbound requests and routing them to owners
• Spotting inconsistent statements across documents

Use cases I’d treat with caution

• Making factual claims about certifications, audits, or control operation without verification
• Auto-sending customer responses without human review
• Generating policies “from scratch” without aligning to your real processes

If you take one idea from this section, take this: AI should speed up your process, not replace your accountability.

What this means for you if you’re selling B2B software

If you’re reading this as a founder, head of sales, marketer, or ops lead, I want you to treat trust as a growth enabler, not a checklist you begrudgingly complete.

Here’s how you can act on it this week:

• Pick one recurring trust task (access review, onboarding evidence, questionnaire handling) and make it repeatable
• Write a single source-of-truth doc for sales: what you can share, where it lives, who approves exceptions
• Automate one step that currently causes delays—task creation, reminders, or evidence gathering
• Stop storing final answers in email threads; build a small internal knowledge base

I’ve watched this sort of housekeeping unlock deals that were stuck for months. It’s not glamorous, but it moves the needle.

How we’d implement a “trust ops” workflow for a client (a realistic blueprint)

If you asked me to set this up for your team, I’d start with a short discovery and then build a lean workflow that grows with you.

Phase 1: map systems and requests

• Where do questionnaires enter the business?
• Which systems hold evidence?
• Who answers what?
• What’s the average time-to-response today?

Phase 2: build a request intake pipeline

• Single intake form for sales + shared mailbox monitoring
• Automatic ticket creation with SLA and owners
• Template library for standard answers

Phase 3: add AI assistance carefully

• Draft responses based on your approved content
• Auto-suggest attachments and evidence references
• Enforce “human must approve” gates before sending

Phase 4: reporting for leadership

• Weekly snapshot: requests received, requests overdue, deal impact
• Monthly snapshot: repeated blockers (so you fix root causes)

That’s it. No theatre. Just reliable operations.

Final thought: trust scales when it becomes boring

OpenAI’s line about Christina Caci reshaping trust at scale with Vanta is short, but it points to something practical: the best trust systems feel almost boring. They run in the background. They produce evidence without drama. They keep promises small and accurate. They help sales move faster because answers are ready.

If you want help building these workflows—especially if you’d like to connect trust operations with marketing and sales enablement—we do this sort of work at Marketing‑Ekspercki using make.com, n8n, and AI-assisted process design. You bring your current mess; we’ll turn it into a process your future self will thank you for.