While leaders are racing to implement AI, employees are more hesitant about the potential impact on their work and livelihoods.
Customers are also skeptical of the technology, as noted by Gartner, with many rightfully questioning AI outputs related to product information and recommendations.
In this environment, companies that focus on true AI alignment within their organization — not just speedy implementation — stand to gain the biggest competitive advantage.
Here’s how your brand can accelerate AI adoption without compromising employee or customer trust.
In commerce, shoppers are turning to AI tools for product discovery and research, but AI recommendations don’t determine their buying decisions alone.
This is the AI trust gap.
Consumers are willing to use AI, but only up to a point. While 22% of consumers use AI tools like ChatGPT to shop, only 14% trust AI recommendations enough to actually purchase without seeking additional information elsewhere, according to Salsify’s “2026 Consumer Research” report.
The remaining 86% scour other marketplace sites, reviews, and gather intel on social media before they complete a purchase.
The AI trust gap isn’t just an issue in commerce. It’s also happening across organizations.
A global IBM CEO study found “many employees see generative AI as something that’s happening to them, not a tool that works for them.”
In the study, 64% of CEOs say their organizations must integrate technologies that are changing faster than employees can adapt to, and 61% admit they’re pushing their organizations to adopt generative AI (GenAI) more quickly than some people are comfortable with.
This internal AI divide only widens the AI trust gap. Employees already fear job loss and displacement because of AI, so it’s up to leaders to reassure them that these tools aren’t a replacement, but rather a complement to their work.
Starting from the inside out can help organizations build trust with employees — and eventually consumers — as their operations become more AI-led.
The AI trust gap has potential implications for brands both internally and externally.
Internal AI misalignment could mean slower or less impactful adoption. Organizations are already grappling with shadow AI, where employees use unsanctioned AI tools at their own discretion — which could jeopardize data security, according to IBM. They’re likely doing this because their organizations don’t have a clear AI strategy or governance policy.
AI learning and development is another critical consideration. Only 44% of CEOs have assessed the impact of GenAI on their workforce. CEOs also say 35% of their workforce will require retraining and reskilling over the next three years, according to the IBM study.
However, that number should be much higher.
AI requires organizations to reimagine how they work. Going forward, AI will overlay nearly every part of business operations, so both technical and non-technical users must be equipped to use and apply the technology to their work, from C-suite leaders and digital marketers to customer success managers.
Organizations have to invest in both enterprise-level and role-specific AI training to build buy-in and increase adoption.
These internal changes will also impact the customer experience.
Nearly 70% of shoppers will pay more for a brand they trust, and 67% cite product quality and value as key to brand trust, according to Salsify’s research.
At the same time, 86% of shoppers either don’t use or fully trust AI shopping tools:
33% don’t use AI shopping tools
27% trust them for some purchases, but verify with other sources
20% are skeptical, but occasionally use them
6% don’t trust them at all
This creates a potential minefield for brands that plan to use AI to drive customer personalization and optimize their marketing campaigns: If AI-driven experiences feel disjointed, irrelevant, or intrusive, brands will see the AI trust gap widen even more.
How they use the technology — and the guardrails they place around it — will either erode or reinforce customer trust.
As organizations race to implement AI, how they apply the technology must reflect their brand values. Here’s how they can execute responsible AI adoption that strengthens, rather than undermines, employee and customer trust.
There’s a lot of hype and hysteria surrounding AI, so it’s up to leaders to cut through that noise with a clear, mission-driven message.
They must align AI to their organization’s larger purpose, positioning it as a tool that will help the company fully embody its mission and deliver on its brand promise.
In this way, leaders can give employees something to rally around, or at the very least, show there’s a clear AI vision guiding them.
According to IBM, only 44% of CEOs reported assessing the workforce impact of GenAI. That means the majority, or 56%, haven’t.
This creates a huge trust gap even before the technology is implemented. Organizations must do their due diligence and carefully assess AI’s potential impact on various business units and what their work may look like going forward.
Employees need and deserve this clarity if your company hopes to build buy-in and engage them as true partners in AI transformation.
Your company’s AI governance policy will evolve just as the technology does.
However, organizations can start by crafting a responsible AI policy, with input from cross-functional stakeholders, ideally at various leadership and employee levels.
Once your company works through this internally, it’s important to be just as transparent with customers. Tell them how you plan to use AI, how you will or won’t use AI to support your customer experience, and how you’ll safeguard and not exploit their data.
Clarity drives responsible implementation, and that ultimately drives trust.
Organizations will have to develop both enterprise-level and role-specific AI training.
At the enterprise level, this will likely involve governance training on responsible AI use, an overview of the company’s AI tools and key use cases, guidance on best practices, and other AI literacy fundamentals.
Role-specific training will vary by business unit, but it could include topics such as using AI to generate product descriptions and analyze customer reviews, and verifying AI-generated product tags and listings.
Training should also be multimodal, offering diverse learning experiences that cater to employees' different learning styles. On-demand microlearning courses and live, interactive, or small-group training sessions are just a few ways your organization can develop an impactful AI learning and development program.
Organizations should identify internal power users, AI enthusiasts, and AI-curious individuals.
These employees can serve as AI champions, sharing use cases, best practices, and potential pitfalls. They can also serve as an advisory council to leadership as the organization’s use of AI grows.
Boston Consulting Group (BCG) reports that “when employees are more familiar with AI agents, they see them as a valuable tool rather than a threat.”
Innovate and Adapt
Your organization will need to constantly test, learn, and adapt as you incorporate AI into your workflows and processes.
Building a clear, organized process to determine what works and what doesn’t can help you develop a scalable, effective AI strategy that fosters internal alignment — and external growth.
By taking these steps, you can convert AI from a trust risk into a key asset that increases your competitive advantage.