The EU AI Act's Article 50 took effect on August 2, bringing new transparency rules for customer-facing AI. The regulation requires businesses to inform people when they are interacting with AI systems, including chatbots and AI agents, and to label AI-generated or manipulated content. For sales and marketing teams, this shifts AI disclosure from a technical consideration to a core part of how brands build trust with customers.
Colleen Jones, President at Content Science, told CX Today that transparency should be designed into the customer experience from the first interaction, not treated as a disclosure added after the fact. "The test should be whether a reasonable customer can tell, without having to stop and investigate, that they're interacting with AI," she said. "Transparency works best when it is immediate, plain-language, and part of the experience, not buried in a policy."
AI sales agents face a new disclosure test
Article 50 requires providers of customer-facing AI systems to inform users that they are interacting with AI, unless it is objectively obvious. For sales and marketing teams, this puts a spotlight on whether prospective customers can recognize AI's role before they rely on an interaction to make a decision.
Jessy Van Steenkiste, Senior Global Counsel for Regulatory Compliance, Product, Privacy, and AI Governance at Parloa, argues that businesses should be cautious about relying on the exception for interactions where AI is considered obvious. "Sales and marketing leaders should treat 'obvious' as a low bar to lean on and a high bar to prove," she said.
As AI agents become more capable of replicating natural conversations, a customer may enter a "human-appearing" conversation without realizing that an automated system is responsible for the responses. "If your customer caller has to ask 'wait, am I talking to a bot?', you may have successfully rolled out a remarkably lifelike automated journey, but the moment for transparency and establishing trust has already passed," Van Steenkiste cautioned.
Disclosures should be placed at the beginning of the interaction, while also providing a clear escalation route for when a customer wants human assistance. As Van Steenkiste puts it: "Name the AI, name the company, and offer a human within one line."
Deepfakes raise the stakes for marketing trust
Providers of generative AI systems must ensure synthetic audio, images, video and text outputs are marked in a machine-readable and detectable format, where technically feasible. Deployers also have obligations to disclose AI-generated or manipulated content that qualifies as a deepfake.
For sales and marketing teams, this creates an important distinction between using AI to assist content production and using it to create something that could make an audience believe a real person said, did or endorsed something that never happened. Suv Viswanathan, Head of Marketing at Zoho, suggests businesses can establish practical internal boundaries around these uses.
"A practical rule for sales and marketing is that stock imagery and editing of a real photo or video shoot using AI steers clear of deepfake territory," he said. "This allows teams to continue using AI for routine creative tasks, while drawing greater scrutiny around fabricated content."
Viswanathan emphasized: "Where the line starts to be crossed is when AI starts to create voiceovers pretending to be people, or fabricated customer testimonials." Even where synthetic content may appear harmless, audiences may interpret it differently if they are unaware that AI was used to create it. "Content like this must have an explicit label stating the use of AI, regardless of how flattering or low stakes the content seems," he concluded.
Community automation needs a clear identity
With more customer journeys beginning in online communities, brands are increasingly using AI to manage these interactions. Article 50 extends the transparency question into social selling and community engagement, requiring businesses to consider how customers are informed when an AI system is responding.
Dr. Islam Gouda, Global Brand Ambassador for Marketing at revenue marketing alliance, told CX Today that businesses should view this as part of the wider customer relationship. "AI disclosure should not be treated merely as a compliance requirement; it should become part of an organization's customer-trust architecture," he said.
For social selling teams, this means considering whether an AI agent should be presented as an automated assistant, instead of a named salesperson or community manager. Gouda suggests asking: "Would knowing that AI is involved reasonably change how this customer interprets, trusts, or responds to this interaction?"
AI can also create commercial implications by allowing sales and community teams to handle more conversations at scale. "AI can scale the interaction, but trust determines whether the relationship, and therefore the revenue, is durable," he highlighted. For marketers looking to build these skills, AI for Marketing training can help teams understand how to apply AI tools while maintaining customer trust.
Turning AI disclosure into a business process
Article 50 creates a practical distinction between companies that provide AI systems and organizations that deploy them. Sales and marketing teams are responsible for how they use AI tools, not just how they were developed. This requires teams to assess whether vendor AI products support appropriate disclosure, machine-readable marking and reliable content provenance, particularly when AI-generated material becomes part of customer-facing campaigns.
Gene Foca, Chief Marketing and Revenue Officer at Getty Images, highlighted to CX Today that this requires businesses to consider how transparency fits into their wider operations. "The most forward-thinking organizations are treating AI transparency as a trust issue, not just a compliance issue," he said.
Foca noted: "A more comprehensive approach is to build transparency into content workflows from the outset." Rather than relying on European guidelines alone, enterprises should establish clear internal rules for labeling AI-generated content, documenting how content was created, and defining when human review or escalation is required. "The greater the transparency in the content supply chain, the easier it becomes to apply governance processes consistently, mitigate legal and reputational risk, and maintain customer trust," he explained.
For teams managing customer-facing AI interactions, AI for Customer Support resources can help clarify how disclosure requirements apply in service journeys.
Why this matters for marketers
Article 50 turns AI transparency into a customer trust issue with legal weight behind it. Marketers should audit every customer-facing AI touchpoint - chatbots, AI sales agents, community automation, and synthetic content - to confirm disclosures appear at the start of the interaction, in plain language, with a clear route to human support. The teams that treat disclosure as a design feature rather than a compliance checkbox will be better positioned to maintain customer confidence as AI becomes more embedded across the buyer journey.
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