Trust is emotional. It is built on experience and on the belief that something will work the way we expect it to.
CRM is no different. If sales reps repeatedly find information that is accurate, complete, and current, they learn to rely on it. When they don’t, trust starts to disappear.
If that sounds familiar, you are far from alone. Validity’s State of CRM Data Management 2025 found that 76% of CRM users say less than half of their organization’s CRM data is accurate and complete.
Salesforce data quality is therefore more than a question of keeping records clean. For sales teams, it shapes whether the information they find in CRM is information they believe they can trust.
For sales reps, that brings us back to how information gets into CRM in the first place, but also to what happens when information is missing, outdated, or incorrect. Building trust means making it easier to keep CRM accurate, complete, and current—and creating a better experience for the moments when it isn’t. Because those moments will always happen.
This is where aiola brings conversational AI into the CRM experience: making it easier for sales reps to get information in and out through natural conversation, while helping identify and address missing information along the way.
Because getting sales teams to trust CRM isn’t about promising perfect data. It’s about creating an experience they can learn to rely on.
What Happens When You Can’t Trust What’s in CRM?
The problem is bigger than finding an outdated phone number or an empty field. It can show up in different ways across a sales organization, but they all point to the same thing: a lack of trust and the impact that can have on productivity and target attainment.
We looked at research from the last three years to see how consistently this problem appears and what happens when businesses cannot trust the information in their CRM.
2024 — Validity, The State of CRM Data Management in 2024
24% of CRM administrators said less than half of their CRM data was accurate and complete.
Research base: More than 600 CRM administrators globally were surveyed for the report.
What else was happening: Among organizations struggling with CRM data quality, 68% reported incomplete data, 65% missing data, 61% incorrect data, and 49% expired data.
The impact: 31% of CRM administrators reported that poor-quality data cost their organizations at least 20% of annual revenue.
2025 — Validity, The State of CRM Data Management in 2025
A year later, the trust gap was still visible.
76% of CRM users and stakeholders said less than half of their organization’s CRM data was accurate and complete.
Research base: 602 CRM users and stakeholders across the United States, United Kingdom, and Australia participated in the study.
What else was happening: Poor CRM data was not staying inside the CRM. 37% of respondents said their organization had lost revenue as a direct result of poor data quality.
The impact: Organizations reported losing an average of 16 sales deals per quarter because of poor-quality data.
2026 — Salesforce, State of Sales, 7th Edition
By 2026, Salesforce’s research shows Salesforce data quality becoming even more important as sales organizations introduce more AI into their workflows.
46% of sales professionals using AI agents said data-quality issues were hurting their sales.
Research base: Salesforce surveyed 4,050 sales professionals across 22 countries, including sales representatives, managers, directors, and executives.
What else was happening: Incomplete data was among the leading data challenges reported by sales teams using AI agents.
The impact: The information inside CRM is no longer only supporting the sales rep. It is increasingly becoming context for AI and agents as well. When that information is incomplete or inaccurate, the trust question expands: can the sales rep trust what CRM says, and can they trust what AI does with it?
Three Years, the Same Trust Question
These studies look at CRM information from different perspectives, but together they make one thing clear: trust cannot be separated from the information people experience when they use CRM.
Adding AI makes that trust problem even more evident. When AI depends on the same CRM information sales teams already question, the problem becomes impossible to ignore. The cost to the organization grows too: on top of the impact on productivity and sales targets, businesses are now investing in AI technology whose value also depends on the quality of the information behind it.
So how do we start changing that experience?
It starts with two moments: how information gets into CRM, and what happens when a sales rep needs to get information back out.
Trust Starts With What Goes Into CRM
If we want to change trust in CRM, the first place to start is with the information going in.
For sales reps, manual CRM updates have traditionally been an ask: remember what happened, decide what matters, enter the information, complete the right fields, and keep the system up to date.
We need to change that experience. Intake needs to become a win-win, not a chore.
Conversational CRM transforms this experience, making intake not just a place where sales reps drop information, but an interaction that is easier and valuable to them too.
The rep can share what happened naturally, while the conversation takes on more of the work required to turn that information into CRM data. At the same time, the interaction can give something back—asking the right questions, adding context, and surfacing relevant information when it is useful.
The rep contributes what they know, while CRM starts carrying more of the burden and creating value in return.
That gives sales reps a different reason to engage with CRM—and gives the organization a better starting point for building trust in what goes into it.
Trust Is Tested When the World Isn’t Perfect
Even if we improve intake, trust will still be tested every time a rep asks CRM for information.
Missing, outdated, or incorrect information will always happen. The goal isn’t to pretend CRM knows everything.
Conversational AI changes the experience of those moments. If a rep finds missing or incorrect information, it no longer has to become a dead end—or another task added to the to-do list.
The conversation can look for context elsewhere in CRM, connect information that may help fill the gap, or turn what is missing into an action. If the answer isn’t available right now, it can become part of the next customer conversation, with CRM bringing it back when it becomes relevant.
The experience changes from “I found another CRM problem I need to fix later” to “this is something CRM and I can work through together.”
That sense of collaboration is the foundation for building trust. The CRM may not always have the answer, but when it doesn’t, the experience keeps moving instead of ending at a wall.
The Cost of Not Fixing Trust Is Getting Bigger
Sales organizations are already investing in AI. Salesforce reports that 87% of sales organizations use some form of AI, while Gartner found a wide gap in the returns organizations are seeing from those investments.
Building more AI on top of CRM information that sales teams don’t trust is like building on a shaky foundation. Another layer of technology doesn’t make the foundation stronger. It makes the weakness more evident.
And that makes the cost of doing nothing bigger.
It is no longer only about the investment in technology, lost deals, or productivity. Companies are investing in AI to support the next stage of growth. But if that AI depends on CRM information sales teams don’t trust, the problem starts disrupting the very future that investment is meant to create.
The cost of not fixing trust is no longer just what it costs the business today. It is what it could prevent the business from achieving tomorrow.
What Does Technology Built for CRM Trust Look Like?
Building trust in CRM puts a different set of demands on the technology behind the experience.
Here is what that technology needs to do:
| Technology requirement | What it needs to do | How it supports trust |
|---|---|---|
| Natural conversation | Let reps communicate naturally instead of learning commands, field names, or CRM processes. | Makes contributing and accessing information part of the way reps already communicate. |
| Context understanding | Understand customers, people, products, terminology, commitments, and other context within the conversation. | Helps preserve more of what actually happened instead of reducing the interaction to simple input. |
| Voice-to-data | Turn natural conversation into structured information connected to the correct CRM records and fields. | Creates a stronger connection between what happened in the field and what appears in CRM. |
| Validation and clarification | Follow CRM validation rules and recognize when required information is missing or needs clarification. | Makes gaps something the rep and CRM can work through rather than discover later. |
| Two-way CRM communication | Let the same conversation both contribute information and bring relevant CRM information back to the rep. | Makes CRM intake a value exchange rather than a one-way chore. |
| Business-process understanding | Work with the company’s existing fields, forms, workflows, terminology, validation rules, and business logic. | Keeps the conversation connected to how the business actually uses CRM. |
| Conversational AI analytics | Track conversations, updates, accuracy, completeness, usage, and agent performance over time. | Gives the business visibility into whether the experience and information are improving. |
Building Trust Into the CRM Experience — aiola’s Vision
Conversation comes naturally to people, and for salespeople, it is already at the center of how they work.
At aiola, our vision is simple: technology should learn to speak our language, rather than asking us to learn its.
We are committed to creating a Salesforce experience that feels less like using a system and more like talking to a helpful colleague—one you want to talk to more and more because it listens, understands context, asks questions, remembers, and brings information into the conversation when you need it.
What sounds like a very human experience is our vision for transforming what people thought was possible when communicating with systems.
That is why we continue to invest in the technology behind that experience: making voice more natural, conversational AI more intelligent, and the interaction between salespeople and CRM more valuable with every conversation.
For us, building trust in CRM isn’t a feature to add. It is an experience we are committed to making better.
Final Thoughts
Building trust in CRM is not tomorrow’s problem. It needs to be addressed today.
Sales organizations are already building their future around AI, and that future increasingly depends on the information inside CRM. Leaving an existing trust problem unresolved doesn’t only carry the costs we see today in productivity, lost deals, and technology investment. It can stand in the way of the growth that investment is meant to create.
Building trust therefore isn’t about preparing for what comes next. It is part of making what comes next possible.