Digital Authenticity Index

The front door to your brand no longer belongs to you.

Customers are discovering, evaluating, and judging brands long before they visit your website or speak to your team. AI, search, social platforms, and digital recommendations are reshaping how first impressions are formed. Brands have less time to earn trust, and every digital experience carries more weight. Scaling digital faster across channels and markets is now a trust decision. The Index shows 58% of consumers have already disengaged after an inauthentic digital experience. Require every global content plan to show how it protects accuracy, transparency, and human access before it scales.Scale can dilute the signals customers use to recognize the brand. Consistency is the smallest gap in the Index at 9pp, so the foundation is already there. Turn voice, claims, and disclosure standards into reusable rules for every market and AI-assisted content workflow.Scale is now more than a delivery challenge. Human accountability is the widest gap in the Index at 39pp, so faster digital journeys can lose trust when escalation and ownership are absent. Build support visibility, data explanations, and content validation into product requirements before optimizing for speed.

That raises three critical questions for marketers:

• How are consumers experiencing the impact of AI on digital experiences?
• How well are brands meeting rising consumer expectations?
• Where should brands focus next?

The Digital Authenticity Index was built to answer them.

The research shows authenticity is now won and lost online. 68% of consumers place equal or greater weight on digital touchpoints when judging brand authenticity. Expectations continue to rise, with 89% saying brands need to do more to protect and improve authenticity in digital experiences. Yet consumers also see significant gaps between what they expect and what brands deliver. 68% of consumers weight digital touchpoints equally or more heavily than offline ones, so the brand gets rebuilt in channels the central team rarely sees firsthand. Treat digital authenticity as a board-level growth metric. Assign one accountable owner across content, data, and service, and report it next to revenue and retention so it competes for investment with the channels that created the exposure.Online journeys now carry the same trust weight as human interactions for most consumers. The risk reaches beyond broken transactions, because 58% have already disengaged. Map the journeys where customers make high-stakes choices and add reassurance, clear explanations, and human escalation before frustration becomes abandonment.Digital touchpoints often serve as storefront, salesperson, and service desk at once. 15% calling retail as the most authentic and 15% the least. Use product-detail accuracy, returns clarity, and visible help pathways as differentiation levers.Digital authenticity carries extra behavioral weight for younger consumers. 80% of 18 to 29 year olds say digital interactions matter at least as much as real-world experiences, and 68% have disengaged after an inauthentic digital experience against 58% overall. Prioritize fast, credible, and transparent journeys, because this group lets the digital experience define the brand.Digital experience sits especially close to brand reality for millennials. 78% say digital interactions matter at least as much as real-world ones, and 62% have disengaged after an inauthentic experience against 58% overall. Invest in personalized journeys that explain themselves, because relevance without clarity can feel like manipulation.This is a conversion risk that starts before checkout. Retail is evenly split on perceived authenticity, so small failures in product accuracy, delivery transparency, returns, or support access can swing perception either way. Audit the paths where shoppers compare, question, or return products, and make human help easy to find there.

The Digital Authenticity Index turns those expectations into something measurable. It evaluates digital authenticity across nine signals grouped into three pillars: credibility, relevance, and responsibility. The result is a practical framework that helps marketing leaders understand where trust is being earned, where it's being lost, and where to focus first.

Based on global consumer research conducted by Sitecore and Ipsos, the Index measures the gap between consumer expectations and perceived brand performance today. It helps marketing leaders understand what matters most to consumers, where brands are falling short, and where to act to deliver digital authenticity at scale. The Index turns authenticity into a gap analysis. Every one of the nine signals rates 85% or higher in importance, and delivery falls as low as 56%. Build dashboards around expectation-to-performance gaps by signal and audience so the business can prioritize where trust is most underdelivered.This framework gives you a practical way to decide where authenticity investment belongs. Broad brand tracking can hide that responsibility gaps run more than twice as large as credibility and relevance gaps. Use the nine-signal model to move budget toward the trust signals where brands are furthest behind.

2026 Digital Authenticity Index: the results

Unpacking the digital authenticity gap

A structural gap between expectation and delivery

Consumers expect brands to deliver high-quality, trustworthy digital experiences across every interaction.

This expectation is both broad and consistent. Across the Digital Authenticity Index, all nine signals score over 85% in importance, reflecting a near-universal expectation of excellence.

Accuracy and honesty sits at the top, with 96% of consumers rating it as important. At the lower end, signals such as brand consistency and experience coherence still score close to 85%, meaning even the least critical areas remain highly valued. At 96% importance, accuracy is the first test of authenticity. Inaccurate or misleading information already damages confidence for 40% of consumers. Put claims, product facts, and AI-generated copy through a shared review system so content scale avoids creating credibility debt.Accuracy is the governance signal consumers notice most. 96% expect accurate information, and 65% say undisclosed AI use decreases trust. Manage content controls and AI disclosure together, set approval thresholds for high-impact claims, and require traceable sources for AI-assisted outputs.The 96% accuracy expectation turns product information into a trust asset. Spec sheets, compatibility details, safety information, and availability claims are the digital evidence customers use before they reach sales or service. Treat accuracy governance as part of product quality, with named ownership for every claim across web, ecommerce, partner, and support channels.A 96% accuracy expectation raises the stakes for every symptom guide, eligibility page, appointment message, and AI-assisted answer. Healthcare is the most positively perceived sector among older consumers, with 35% of those aged 62+ selecting it as most authentic. Protect that advantage with clinical review, source clarity, and fast correction across patient-facing content.Accuracy is part of product trust. Buyers and users judge the brand through documentation, release notes, pricing, AI outputs, and support answers long before they engage a human. Build content validation into product launches and AI enablement so feature claims, guidance, and support responses stay aligned.The 96% accuracy expectation makes accuracy a product risk control. AI features and automated support can scale incorrect guidance quickly, and 80% support AI only when it improves accuracy, relevance, or credibility. Set release gates that test AI outputs against approved product knowledge before launch.

In other words, consumers aren’t prioritizing one aspect of authenticity over another: they are expecting brands to deliver across all of them.

Performance falls short across every signal

While expectations are consistently high, performance is far more variable.

At the upper end, brands perform strongest on signals such as brand consistency and reliability over time, reaching around 80%. At the lower end, performance drops significantly with human accountability falling to just 56%, the lowest level of delivery across the Index.

This spread in performance, against consistently high expectations, is what creates the digital authenticity gap.

The gap is not limited to a single area. It is visible across every signal in the Index.

The largest gap sits in human accountability (39pp), followed by perceived brand intent (33pp) and transparency (31pp). Steer attention toward the signals with the largest expectation gaps. Human accountability, perceived brand intent, and transparency are where consumers feel brands fall furthest short. Before funding more content, personalization, or new channels, check whether customers can reach support, understand how their data is used, and believe experiences are built in their interests. Closing these three gaps will likely return more trust than incremental gains elsewhere.This is the clearest prioritization logic in the Index. Average performance would point to broad improvement, and the 39pp, 33pp, and 31pp gaps show responsibility is where consumers feel the greatest shortfall. Segment future tracking around these three gaps and identify which journeys make customers question ownership, motive, or data use.The largest gaps point to moments where journeys feel ownerless. A smooth interface fails to compensate when customers cannot reach a person, understand how data is used, or believe the brand acts in their interests. Redesign escalation, consent, and high-stakes decision points before optimizing lower-risk steps.A 39pp human accountability gap makes escalation design a core trust lever. Human access ranks as both the top trust builder and the top trust breaker. Audit self-service, chatbot, and help-center flows for the exact moment a customer needs a person, then make that path unmistakable.These gaps cut deep in financial services, where digital trust often forms before an advisor, banker, or agent enters the conversation. The category is polarizing, with 20% calling it most authentic and 20% least. Prioritize transparent data use, visible support routes, and customer-first explanations across onboarding, pricing, claims, and advice journeys.Treat the responsibility gaps as commercial risk indicators. Human accountability, intent, and transparency map directly to the concerns that make financial services feel complex or self-serving. Put these three signals at the top of digital scorecards, ahead of self-service efficiency metrics.

At the other end of the spectrum, brand consistency shows the smallest gap (9pp) but still falls short of expectations.

Even accuracy and honesty, the most important signal, shows a meaningful gap (23pp), highlighting that even the most critical expectations are not being fully met.

Not all gaps are equal

A clear pattern emerges when comparing signals across the Index.

Signals related to credibility, such as accuracy and consistency, tend to perform relatively better, with smaller but still meaningful gaps.

Signals linked to relevance, including personalization and contextual fit, sit in the middle, reflecting uneven delivery across experiences.

The most significant gaps sit within responsibility.

Human accountability, transparency, and perceived brand intent all show the largest disconnect between expectation and delivery. These are not simply executional gaps: they reflect how consumers interpret brand behavior. These three signals are interpretation gaps, which places them inside the governance mandate. Responsibility shows a pillar gap near 35pp, more than double credibility or relevance. Move governance from policy documents into the experience itself through plain-language data notices and visible escalation, so responsible practice becomes something customers can see.

Rising expectations, moderate perceptions

Consumers are clear that brands need to improve.

89% say brands need to do more to improve digital authenticity across all nine signals, and 40% say much more. 86% believe it should be a top or high investment priority.

At the same time, overall perceptions remain relatively moderate.

While 60% of consumers say brands are digitally authentic, only 9% describe them as very authentic, leaving a lot of ground for brands to make up.

A systemic challenge, not a single-point failure

Digital authenticity is not created in a single interaction or owned by a single team.

It is the cumulative result of thousands of decisions across content, data, AI, and experiences. As brands scale, the risk of inconsistency increases.

Because consumers experience authenticity holistically, the weakest point in that system defines the overall perception. Brands are not judged on their best-performing signals but on the areas where they fall furthest short. Because consumers judge authenticity as a whole, the weakest point defines overall perception. That places it above any single channel owner. People remember the weak moments that call the brand into question. Create a cross-functional review that evaluates content, data, AI, support, and journey performance together.If the weakest signal defines perception, channel-only scores mislead. The same customer can rate reliability well and lose trust when human accountability or transparency fails. Build measurement that flags the lowest-performing signal within each critical journey, because that weak point most likely defines the brand.When the weakest point defines perception, platform fragmentation becomes a trust risk. A well-performing app cannot carry the experience when consent, content, or support breaks elsewhere. Prioritize shared data, content, and escalation infrastructure so the customer feels one accountable brand across the journey.The weakest-point dynamic shifts attention from individual touchpoints to the transitions between them. Trust often erodes when customers move from browsing to support, from personalization to privacy, or from automation to escalation. Map the handoffs where authenticity can break and assign a clear owner to each one.In retail, the weakest point is usually a handoff between product content, checkout, fulfillment, returns, and support, and the category sits in the middle on perceived authenticity. Use journey audits to find the single step most likely to make shoppers question the brand, and fix that before adding new experience features.Returns, delivery issues, and support access deserve as much attention as acquisition journeys. A polished storefront can lose trust when post-purchase communication feels confusing or ownerless. Measure authenticity at the journey-transition level, especially where service recovery begins.

How authenticity connects to trust

The Digital Authenticity Index identifies the signals that determine whether digital experiences feel authentic to consumers. Across the Index, the same themes emerge consistently: accuracy, honesty, relevance, transparency, accountability, and responsible delivery.

What makes these signals so important is their direct connection to trust.

To understand that relationship more explicitly, we asked consumers a simple question: what strengthens trust in digital experiences, and what undermines it?

What builds and breaks trust

Consumers say trust increases when brands make digital experiences feel clear, accurate, human, honest, and safe.

The reverse is also true. When consumers were asked what damages their confidence in brands’ digital experiences, they pointed to the same underlying areas.

The finding confirms a central point: when consumers experience authenticity, trust increases.

Authenticity is how trust is earned in digital experiences

The trust data confirms that authenticity and trust move together.

Consumers don’t separate digital trust from the quality of the experience. They judge trust through what a brand does: whether it is accurate, honest, transparent, human, and accountable.

That makes digital authenticity one of the practical mechanisms through which trust is earned online.

The relationship is symmetrical

One of the clearest findings is that the same factors appear on both sides of trust.

Human access builds trust, but its absence is the biggest trust breaker. Accuracy builds trust, but misleading information damages confidence. Privacy protection builds trust, but privacy concerns erode it. Automation can help, but when it feels robotic or evasive, it weakens trust. Trust is earned and lost in the same moments. Easy human access is the top trust builder at 45%, and the absence of a clear human route is the top trust breaker at 46%. Make escalation visibility a design standard across complaints, decisions, account changes, and service failures.Contact access works as a brand-protection function. The fastest self-service flow can still damage trust when customers feel trapped by automation. Track containment alongside trust outcomes, and build escalation triggers for confusion, repeat contacts, and high-risk issues.Controls build trust only when they are visible in the experience. Privacy protection builds trust for 34%, privacy concerns damage it for 32%, and robotic interactions damage confidence for 33%. Review data, AI, and automation disclosures alongside support access so customers see accountability before they search for it.Human access is a stronger trust signal for older consumers than the average. 62% say no clear route to a human damages confidence against 46% overall, and 66% want to reach a real person quickly when something goes wrong. Place phone, chat, and escalation options near complex decisions.The trust risk already runs above average for Gen X. 50% say lack of human access damages confidence, and 54% want to reach a real person quickly when a digital experience goes wrong. Design escalation for time pressure and responsibility, especially in payments, account changes, and unresolved service issues.For older consumers, containment should protect confidence. This audience over-indexes on needing a person quickly when things go wrong, so a hidden escalation path can turn a solvable issue into a trust failure. Add clear human fallback before chatbot loops, knowledge-base dead ends, and account recovery steps.

This symmetry shows that trust is not created by excelling in one area while failing in another. Consumers experience authenticity as a whole. If one core signal fails, the entire experience becomes less trustworthy.

Human accountability is the strongest proof point

Human access is the clearest example of the link between authenticity and trust.

Consumers say easy access to human support is the top trust builder. They also say no clear way to reach a human is the top trust breaker. The strongest opportunity may sit in redesigning escalation journeys ahead of acquisition ones. Human access is the biggest trust builder at 45% and the biggest trust breaker at 46%, so support visibility carries an outsized effect on perception. Review where customers hit uncertainty, complaints, or high-stakes decisions, and make a clear path to a person available before trust slips.

That mirrors the Index finding that human accountability has the largest expectation-to-performance gap (39 pp). Together, the findings show that human accountability is one of the strongest signals of whether a brand feels authentic and therefore trustworthy.

This becomes even more important as brands automate more of the customer journey. Consumers may accept automation, but they still want to know a person is reachable, and responsible for stepping in when needed.

Consumers are questioning brand responsibility

Responsibility is where the gap is widest

The Digital Authenticity Index is built around three pillars: credibility, relevance, and responsibility.

At a pillar level, the gap between expectation and delivery is not evenly distributed. Credibility and relevance each show a gap of around 15 percentage points, while responsibility shows a much wider gap of around 35 percentage points.

Responsibility is the weakest pillar, with a gap more than twice as large as credibility or relevance. Responsibility is the weakest pillar, ahead of capability. Consumers judge how and why you deliver, and whether you can comes second. Direct your next wave of digital investment toward demonstrating intent and accountability, because the largest trust returns sit in signals the technology roadmap rarely prioritizes.This validates governance as a customer-experience priority. Consumers signal a larger shortfall in responsibility than in relevance or credibility, so invisible policies leave the gap open. Translate governance into front-end cues: plain-language data explanations, AI disclosure, accountability labels, and escalation pathways.The responsibility gap maps onto the category's polarization. Consumers see regulation and security, or they see complexity, fees, data use, and misaligned incentives. Use customer-first explanations, fee clarity, and visible expert access to make responsibility tangible in account, advice, lending, and claims journeys.A strong authenticity position can weaken when responsibility signals are unclear. Healthcare ranks among the most trusted sectors, and patients still need proof that data, automation, and support decisions serve their interest. Make consent, triage logic, and human follow-up easy to understand before moments of anxiety become moments of doubt.Treat the 35pp responsibility gap as a risk-prioritization tool. It points to the moments where customers question motive, control, and accountability, especially around data use, automated decisions, and product terms. Review high-volume digital journeys for customer-first explanations before adding further automation.

This is a critical finding: it shows that the biggest challenge is not simply whether brands can deliver functional, relevant, or consistent digital experiences.

The biggest gaps sit in responsibility signals

The pattern becomes even clearer when looking at the individual signals. The three largest gaps in the Index all sit within the responsibility pillar.

Responsibility is where authenticity is most fragile

The responsibility signals carry a different kind of meaning.

Credibility tells consumers whether a brand can be believed. Relevance signals whether a brand understands the moment. Responsibility determines whether consumers trust the brand behind the experience.

That’s why the gaps here matter so much.

When brands fall short on responsibility, consumers begin to question what’s really driving decisions. The brand can start to feel less human, less trustworthy, and more focused on efficiency than care. That’s where authenticity begins to break down.

The issue is not capability. It is confidence.

Many brands have invested heavily in digital capability. They can personalize experiences, automate journeys, scale content, capture data, and respond across channels faster than ever before.

But capability does not automatically create authenticity.

The more advanced digital experiences become, the more consumers look for evidence that the brand is using that capability responsibly. Advanced capability builds trust only when its purpose is visible. Responsibility is the widest pillar gap, so personalization, automation, and AI can feel like progress inside the business and pressure outside it. Add customer-facing rationale, controls, and escalation points to advanced features before scaling them across journeys.This is the bridge between policy and product. As data and AI become more central, consumers look for evidence that systems are used responsibly. Require product teams to document customer benefit, disclosure approach, and human oversight for every automation or AI-enabled experience.Customers buy capability and trust together. A sophisticated AI or platform feature can still damage authenticity when users cannot understand its limits, data use, or escalation path. Package advanced features with clear controls, explainability, and support ownership as part of the product experience.Digital capability increasingly runs through partner portals, configurators, product data, and service automation. Customers value speed, and they still need evidence that specifications, recommendations, and availability are accurate and accountable. Build responsible-use checks into product information management and dealer or distributor experiences.Advanced personalization raises the standard of proof. Consumers expect helpful personalization at 85%, and only 68% believe brands deliver it well. Use preference controls, recommendation explanations, and easy access to support so personalization feels useful rather than commercially aggressive.Personalization investment needs an authenticity guardrail. Before expanding AI recommendations or automated journeys, test whether shoppers understand why they see offers and whether they can correct bad assumptions. The goal is fewer moments that feel intrusive, repetitive, or impossible to resolve.

Automation still needs a human touch

The largest authenticity gap is human accountability

If responsibility is where digital authenticity is most fragile, human accountability is the clearest proof point.

Across all nine signals in the Digital Authenticity Index, the largest gap is in whether consumers feel they can reach a real person when it matters.

95% of consumers say human accountability is important. Yet only 56% believe brands deliver it well. This is the clearest mandate in the Index. A 39pp gap on human accountability shows consumers accept digital service and reject journeys where ownership disappears. Redesign chatbot, help-center, and escalation flows around the moments where reassurance matters more than containment.The 39pp gap means human accountability belongs in the journey as a feature. Human access also ranks as the leading trust builder and breaker, so support visibility carries outsized influence on perception. Review the high-stakes points where customers need reassurance and place human fallback routes before frustration accumulates.The headline gap understates the issue for older consumers. Human access widens to a 56pp gap among those aged 62+, where 97% say it matters and only 40% say brands deliver it well. Make human contact routes highly visible in account, care, payment, and problem-resolution journeys.Human accountability carries extra weight in healthcare, where digital journeys often begin in moments of concern. The sector ranks among the most authentic, so hidden escalation paths can undermine a valuable trust advantage. Make clinical or service handoff options clear in symptom, appointment, billing, and results journeys.Human accountability is where digital convenience becomes digital risk. Customers accept self-service for routine tasks, and decisions about money, claims, credit, or advice demand an obvious route to accountable expertise. Add visible escalation and named support ownership to automated journeys.The human accountability gap matters most when plans change. Half of consumers want fast issue resolution when digital experiences go wrong, and half also want to reach a real person quickly. Design disruption journeys around rapid handoff, clear status, and human support during time-sensitive moments.The 56pp age gap makes hidden contact options a high-risk design choice. Older consumers are more likely than average to want a real person quickly when something goes wrong, so deflection tactics can weaken trust even as they cut volume. Separate routine self-service from reassurance-critical journeys, and route the latter to human help faster.

That creates the widest gap in the Index - 39 percentage points. This is a critical authenticity issue.

Consumers may begin their journey in digital channels, but they still expect evidence that a brand is present, accessible, and willing to stand behind the experience it creates.

Human accountability makes digital experiences feel owned

Digital experiences can be efficient and technically seamless while still feeling distant or impersonal.

Human accountability reassures consumers that there are real people behind the experience who are reachable, responsible for outcomes, and willing to step in when moments become complex or sensitive.

The human touch is moving in the wrong direction

The challenge is not just that brands are underperforming today. Consumers increasingly believe the human element of digital experiences is disappearing altogether.

51% say the human touch in digital experiences has worsened over the past two years. And 50% expect it to decline further over the next two years. The perceived decline in human touch means customers may enter service journeys already expecting distance. That mindset raises the cost of every chatbot loop, unresolved ticket, and missing contact route. Use proactive routing and escalation thresholds to prove the brand is present before the customer goes looking.This is a warning that automation roadmaps need a human-reassurance layer. Consumers are split on AI overall, and loss of human contact is the top concern in AI-driven personalization. Treat human fallback, handoff transparency, and support status as product requirements.A perceived decline in human touch is a journey-design problem. Customers judge the brand through moments of uncertainty, and those moments often sit between channels. Identify where the journey feels automated, stalled, or ownerless, and add visible accountability before it feels impersonal.The decline is more pronounced for Gen X. 58% say human touch has worsened over the past two years, and 58% expect further decline. Build reassurance into digital experiences for this group through clear escalation, proactive updates, and proof that someone owns the outcome.This is one of the sharpest warning signs in the data. 70% of older consumers say human touch has worsened, and 68% expect further decline. Place contact routes, named ownership, and clear next steps directly in the digital journey so this audience never has to infer accountability.For older consumers, automation should start from a human-fallback assumption. Anxiety about human touch already runs well above average, so invisible escalation can make a working feature feel unsafe. Add persistent help access and plain-language handoffs to account, payment, health, travel, and service journeys.

That makes human accountability one of the most urgent authenticity challenges for brands.

As digital systems become faster and more automated, consumers increasingly worry that experiences will feel less personal, less accountable, and less real.

Human accountability is what makes scale feel authentic

Human accountability becomes even more critical as digital experiences scale.

That means making support channels visible, escalation paths intuitive, and human oversight accessible where it matters most. Human accountability is what makes scale feel trustworthy and credible.

AI is an authenticity multiplier

Consumers are divided on AI’s impact

AI now sits at the center of the digital authenticity debate because it shapes many of the signals consumers care about most.

For brands, AI creates powerful opportunities to scale content, personalize experiences, improve service, and operate more efficiently across channels. But for consumers, the growing presence of AI also introduces uncertainty.

The result is a divided picture.

50% of consumers say the increasing use of AI will reduce digital authenticity. 39% say it will improve it. 11% expect no impact. The even split is a governance opening. Half of consumers expect AI to reduce authenticity, so disclosed and well-governed use becomes a visible differentiator. Stand up review for accuracy, data use, and human oversight before expanding AI into customer-facing experiences, and treat governance as the lever that converts the skeptical half. Resistance concentrates with age. 56% of Gen X and 67% of consumers aged 62 and over expect AI to reduce authenticity, against 42% of Gen Z. For older audiences, lead AI rollouts with disclosure and a clear human alternative, because the feature that feels modern to younger users can read as distance to these groups.

This split suggests consumers are not rejecting AI outright. But they’re also not assuming that AI will automatically improve digital experiences.

Instead, AI appears to be judged by its effect on the experience: whether it makes interactions more accurate and relevant, or whether it makes them feel generic, opaque, automated, or less accountable.

Responsible AI is the clearest opportunity

The picture becomes more positive when AI is framed around responsible use.

80% of consumers agree that AI can be useful or beneficial when used responsibly to improve accuracy, relevance, or credibility. The 80% who back responsible AI mark a path through consumer skepticism. Since 50% still expect AI to reduce authenticity, acceptance depends on whether AI improves the qualities consumers already value. Invest in AI use cases that make information more accurate, content more relevant, and journeys more credible before scaling low-value content production.Responsible AI earns trust through experience outcomes. Consumers back AI when it improves accuracy, relevance, or credibility, which maps onto the Index signals. Prioritize AI pilots that reduce incorrect content, improve contextual fit, or speed service recovery, and measure trust impact alongside efficiency.This is a constructive AI-governance mandate. Consumers stay open to AI when it improves credibility, relevance, and accuracy, and 65% say undisclosed AI use decreases trust. Pair AI quality controls with disclosure standards so responsible use stays visible.Responsible AI is a market-permission signal. Customers ask whether AI makes the experience more accurate and credible. Demonstrate responsible AI through product documentation, explainability, human oversight, and proof that AI improves outcomes customers can verify.The AI opportunity runs stronger than the total market for millennials. 86% agree responsible AI can be beneficial, and 71% are comfortable with AI personalization against 58% overall. Use AI to improve relevance and speed, then explain why recommendations appear so acceptance holds.Responsible AI can support authenticity for Gen Z when it improves the experience in ways they recognize. 83% agree AI can be beneficial, and 74% say AI-generated content is easy to spot. Use AI to make interactions faster and more relevant, and keep content quality high for an audience that readily notices generic output.Responsible AI is a product-adoption requirement. The market stays open to it, and disclosure and accountability remain the conditions. Build release checks around accuracy, data-use explanation, and human override so the product proves its responsibility inside the user experience.

This is an important distinction.

Consumer concern is not necessarily about the presence of AI itself. It is about whether AI improves or undermines the qualities that make digital experiences feel authentic.

Responsible AI can strengthen authenticity when it enhances the signals consumers already value: accurate information, relevant experiences, seamless journeys, clear communication, and genuinely useful support.

Younger consumers are more open to responsible AI

Acceptance of AI isn’t evenly distributed across audiences.

Younger consumers are more likely to see the potential for AI to support digital authenticity when used responsibly. 83% of Gen Z consumers agree that AI can be beneficial when used responsibly, compared with 70% of consumers aged 62 and over.

This doesn’t eliminate the need for caution, but it does show that expectations around AI are beginning to diverge by generation.

Younger consumers are more likely to view responsible AI as part of a better digital experience, particularly when it improves things like relevance, speed, usefulness, and responsiveness. Older consumers, by contrast, often expect greater transparency, clearer explanations, and more visible access to human support.

These are significant implications for brands. AI governance cannot be treated as one-size-fits-all. The same experience may feel intuitive and valuable to one audience while creating uncertainty and distrust for another.

Disclosure is a condition of AI-enabled authenticity

Transparency is one of the clearest requirements for AI-enabled digital experiences.

65% of consumers say undisclosed AI use decreases or significantly decreases trust. Disclosure is the cheapest trust mechanism in the research, and it is yours to mandate. Two-thirds of consumers lose trust when AI use is hidden, rising to 84% among consumers aged 62 and over. Make AI disclosure a standard component of content and experience templates so transparency scales automatically as AI adoption grows.Hidden AI use can turn content scale into credibility loss. Since 60% say AI-generated content is easy to spot, undisclosed use can fail twice: customers notice it, then question the brand's honesty. Create brand standards for AI labeling, source clarity, and human review of high-visibility content.Design disclosure into the interaction itself. When AI use is hidden, consumers question accuracy, motive, and accountability. Add clear AI cues, edit options, and human escalation near recommendations, answers, and automated decisions.Undisclosed AI is a higher-than-average trust risk for Gen X. 74% say it decreases trust against 65% overall, and 56% expect AI to reduce digital authenticity. Use explicit AI disclosure and human-review signals in journeys where this group makes financial, health, service, or purchase decisions.Undisclosed AI is one of the strongest trust breakers in the age data. 84% of older consumers say it decreases trust, far above the 65% overall, and only 38% say AI content is easy to spot. Make AI use plain, explain what is automated, and give a direct path to a person when the outcome matters.For older audiences, disclosure should reduce uncertainty. This group is less likely to spot AI and more likely to lose trust when it stays undisclosed. Use plain-language disclosure that explains purpose, data use, limits, and human support in the same moment.

Consumers care about whether brands are open about when and how AI is being used. When AI use is hidden, consumers may question the accuracy of the content, the motives behind the experience, and who is accountable for the outcome.

Disclosure therefore functions as an authenticity signal. It shows that the brand is willing to be clear about the systems shaping the interaction.

AI raises the stakes for human accountability

AI also intersects with the largest gap in the Index: human accountability.

55% of consumers selected loss of human contact as their biggest concern about AI-driven personalization. AI-driven personalization creates contact anxiety before a service issue occurs. Loss of human contact is the top AI concern at 55%, and human accountability is the widest Index gap. Keep human escalation visible inside personalized journeys, especially when automation changes offers, eligibility, recommendations, or routing.This finding should shape AI-personalization requirements. Consumers want relevant content, and they want to know a person stays reachable when the system gets it wrong. Add correction tools, opt-down choices, and human-handoff triggers to AI-personalized experiences.Loss of human contact is an accountability risk. AI can personalize for many customers at once, and customers still need assurance that a person owns the outcome. Review AI-personalization use cases for escalation, appeal, and data-correction processes before launch.This concern runs far stronger than average for older consumers. 67% cite loss of human contact against 55% overall. Use AI sparingly in reassurance-heavy journeys, and make human support clearly available when personalization affects decisions or service outcomes.Loss of human contact also runs high for Gen X. 60% cite it as a top concern, and the human-access performance gap reaches nearly 48pp for this group. Design AI-personalized journeys with visible ownership, especially in account management, billing, service changes, and issue resolution.AI personalization for Gen X should include a clear path to correction. This group is more likely than average to expect AI to reduce authenticity and to worry about losing human contact. Add controls that let users change preferences, challenge assumptions, and reach support inside the same personalized experience.

This concern matters because human accountability is already the largest gap in the Digital Authenticity Index. As AI becomes more embedded in personalized experiences, consumers are increasingly sensitive to whether brands still feel reachable, responsible, and present behind the interaction.

AI-generated content is increasingly visible

Consumers are also becoming more aware of AI-generated content.

60% say AI-generated content is easy to spot. Among Gen Z consumers, this rises to 74%. AI content quality is now visible to the audience. With 60% saying AI-generated content is easy to spot, generic or repetitive output can become a brand signal. Use AI to sharpen message discipline and content operations, then require human review for tone, originality, and factual grounding.Visibility runs especially high for Gen Z. 74% say AI-generated content is easy to spot, and 68% have disengaged after an inauthentic experience. Use AI to improve speed and relevance only when quality and brand fit stay obvious.The opportunity comes paired with scrutiny for millennials. 73% say AI-generated content is easy to spot, and 86% agree responsible AI can be beneficial. Give this audience AI-enhanced personalization that feels useful and clearly explained.For technology brands, spotting AI affects credibility, because customers expect both sophistication and transparency. AI-generated product pages, documentation, and support answers that feel generic can undermine confidence in the underlying technology. Combine AI content systems with expert review and visible source cues so quality reinforces product trust.This is a creative-quality warning for Gen Z work. The audience stays open to responsible AI, recognizes synthetic content readily, and disengages quickly after inauthentic experiences. Use AI for versioning and testing, then protect distinct voice, cultural relevance, and source credibility before publishing.

This has important implications for content strategy.

AI-generated experiences that feel generic, repetitive, or disconnected from the brand are unlikely to go unnoticed. Consumers may not always know exactly how AI is being used, but they are increasingly sensitive to content that feels synthetic or low-quality.

As AI increases the volume of content brands can produce, the standard for quality control becomes more important.

AI amplifies existing strengths and weaknesses

AI does not automatically reduce digital authenticity. But it can accelerate the conditions that already exist inside a brand’s digital experience system.

Where content governance is weak, AI can scale inconsistency. Where data practices are unclear, AI can increase concern. Where human accountability is already hard to access, AI can make the brand feel further away. This is the strongest argument for treating AI as an operating-model issue. AI magnifies the standards already present in content, data, support, and governance. Fund the governance and workflow foundations first, because scaling weak systems multiplies the gaps consumers already see.AI readiness is mostly experience-system readiness. Where data practices, escalation, or content ownership are unclear, AI exposes those weaknesses faster. Assess AI pilots against the nine authenticity signals before deployment, and fix the weakest control before expanding volume.This points to a practical audit sequence. Start where AI can scale harm: inaccurate content, unclear data use, and missing accountability. Require evidence of source control, disclosure, oversight, and escalation before approving any AI-assisted experience workflow.The multiplier effect is part of the product promise. Customers judge AI-enabled platforms by how well they hold accuracy, transparency, relevance, and oversight as volume grows. Build governance into the product experience through audit trails, permission controls, source transparency, and human override.AI trust needs more than documentation. When the platform helps customers scale content or decisions, it also needs guardrails that prevent inconsistency, unclear data use, and lost accountability. Prioritize controls that help customers operationalize authenticity inside their own workflows.

But where brands have strong standards for accuracy, transparency, relevance, and oversight, AI can help extend those strengths across more interactions.

Authenticity varies by industry

Digital authenticity is not evenly distributed

Consumers do not perceive all industries in the same way.

While the Digital Authenticity Index shows that brands are under pressure across every signal, perceptions of authenticity vary meaningfully by category.

Some industries are more likely to be seen as digitally authentic. Others face greater skepticism.

This matters because consumers bring different expectations, risk sensitivities, and levels of trust to different categories. A digital experience in healthcare, finance, travel, or media is not judged in exactly the same way.

Healthcare and food-related categories are most likely to be seen as digitally authentic, while travel and financial services also appear among the leading sectors. Sitting among the most authentic sectors is an advantage to defend. The age data shows 35% of consumers aged 62+ select healthcare as most digitally authentic, its highest positive age cut. Protect that trust by keeping clinical information, appointment flows, billing, and support access consistently accurate and easy to understand.A place among the leading sectors gives permission to lean into digital service moments. Travel runs time-sensitive, and fast resolution and quick human access are the top needs when digital experiences go wrong. Prioritize disruption communications, itinerary clarity, and live support during delays, cancellations, and booking changes.A place among the leading sectors is both promising and fragile. The category also appears among the least authentic at 20%. Use the positive baseline to separate trusted brands from skeptical perceptions through clearer terms, data transparency, and visible human expertise. Authenticity tracks perceived dependability more than digital sophistication. The leading categories are ones consumers associate with accurate information and practical value. Benchmark your category against these leaders on trust drivers, then steer investment toward the signals that move perception in your sector.

This suggests that authenticity is not only about digital sophistication.

Some of the highest-ranked categories are sectors where accuracy, reliability, and trust are especially important. Consumers may be more likely to recognize authenticity when digital experiences support clear information, dependable service, and practical value.

Beauty, media, and real estate-related categories face the strongest skepticism, while financial services is notable for appearing in both the most and least authentic rankings.

These categories may face different authenticity challenges.

In some cases, consumers may be more alert to exaggerated claims, image-led content, influencer activity, or promotional messaging. In others, skepticism may be shaped by complexity, high stakes, unclear terms, or inconsistent digital experiences.

Financial services is polarizing

Financial services is the clearest outlier.

It appears among both the most authentic and least authentic industries, with 20% selecting it in each ranking. The 20% split shows the category holds no settled authenticity position. Trust, regulation, security, and reliability work in its favor; complexity and perceived self-interest cancel that out. Focus digital investment on the responsibility gaps that explain the polarization: human access, transparent data use, and customer-first explanations.Polarizing categories show that reputation creates no stable trust floor. The same brand behavior gets read through confidence or skepticism depending on the experience. Identify which audiences see your category as trustworthy and which see it as opaque, then tailor digital proof points accordingly.Financial services is the only category to land in both rankings at 20%. Perception is divided. The same brand can read as secure and regulated to one customer and opaque to another. Segment your authenticity tracking to find which customers sit on each side, then target the experiences, fee clarity, and access that move the skeptical group toward the trusting one.Manage polarization as a strategic growth constraint. A digital onboarding or advice journey reinforces security and expertise, or it triggers concerns about motive and data use. Set accountability, transparency, and intent metrics for every major digital product journey.

That suggests the category is not viewed consistently. For some consumers, financial services may signal trust, regulation, security, and reliability. For others, it may raise concerns about complexity, transparency, fees, data use, or whether the experience is designed in the customer’s interest. The negative half of this split centers on the governance remit: complexity, transparency, fees, and data use. These map to the transparency signal, which carries a 31pp gap across the Index. Translate disclosures into plain language at the point of decision, surface total cost clearly, and explain data use in context, so the concerns that push customers toward the least authentic perception get addressed where they form.

This polarization matters because it shows that industry perceptions are not fixed.

Even in high-trust or highly regulated categories, digital authenticity can vary sharply depending on the quality of the experience and the clarity of the relationship.

Authenticity reflects priority, not just category

The industry data points to a broader conclusion: digital authenticity is not determined by industry alone. Sector context matters, but it does not decide the outcome.

Industries with higher perceived authenticity are not necessarily the ones with the most advanced digital capabilities. They are the ones consumers are more likely to associate with dependable information, clear value, and a sense of responsibility. This is a useful counterweight to digital feature-chasing. Consumers reward dependable information, clear value, and responsibility, which map to product accuracy, availability, service documentation, and channel consistency. Invest in product content governance and dealer or distributor experience quality before adding more digital complexity.Sophistication alone fails to make experiences feel authentic. Customers need dependable information, clear value, and responsible delivery from the tools they use and the guidance around them. Make transparency, documentation accuracy, support ownership, and AI governance visible inside the product experience.The lesson for retail is to compete on confidence as much as convenience. Retail ranks as no standout authenticity leader, so dependable product information, clear value, and responsible service become the differentiators. Prioritize accurate product pages, transparent fulfillment, simple returns, and responsive support over more promotional touchpoints.Perceived authenticity strengthens when digital experiences feel useful and responsible. Patients need dependable information and clear next steps, especially when health, coverage, or care decisions are involved. Use digital investment to reduce uncertainty through plain-language content, reliable scheduling, and clear support ownership.Authenticity is often earned through dependable service during moments of change. Consumers value a slick booking experience, and trust is tested when plans shift. Focus on clear itinerary data, proactive updates, and human support during disruption before expanding lower-value personalization.

Likewise, lower-ranked categories are not automatically inauthentic. But they may face a higher burden of proof because consumers are more sensitive to overclaiming, opaque practices, or experiences that feel commercially motivated.

The generational authenticity divide

Age shapes how consumers experience authenticity

As brands scale digital experiences across increasingly diverse audiences, age becomes one of the most important factors shaping how authenticity is perceived.

The data reveals a clear generational divide. Among Gen Z consumers aged 18–29, the gap between expectation and performance averages 15 percentage points. Among consumers aged 62 and over, that gap nearly doubles to 29 percentage points. A one-size-fits-all digital experience strategy is now a trust risk. Gen Z's average authenticity gap is 15pp, against 29pp for consumers aged 62+. Set experience standards that flex by audience, especially around AI disclosure, support visibility, and reassurance in high-stakes journeys.Age is a segmentation priority. The near-doubling of the authenticity gap among older consumers means aggregate scores can hide very different trust thresholds. Track authenticity signals by age, and model which signals most strongly predict disengagement within each generation.The same journey may need different reassurance layers for different ages. Younger users accept AI and self-service more readily, and older users show larger gaps around responsibility and human access. Design adaptive journeys that surface contact options, explanations, and controls based on customer need.A smaller gap does not mean authenticity matters less to Gen Z. This group is more likely than average to say digital interactions are as important as real-world ones, and more likely to disengage after inauthentic experiences. Maintain speed and relevance, and keep AI content quality high for an audience that spots it.The larger gap shows digital experiences often give older consumers too little reassurance. This audience is less likely to see brands as digitally authentic and more sensitive to hidden AI and missing human access. Make transparency and contact options visible by default, especially in financial, health, travel, and service journeys.The 29pp average gap among older consumers should trigger a separate diagnostic view. This group holds different authenticity thresholds around responsibility. Report the 62+ experience separately for AI disclosure, human access, and data-use clarity so teams avoid over-optimizing for younger digital fluency.

The authenticity gap among older consumers is nearly twice as large.

That means the same digital experience may feel intuitive and trustworthy to one generation while feeling impersonal, opaque, or unaccountable to another. Younger consumers tend to be more digitally fluent and more comfortable with AI-enabled interactions. Older consumers often place greater weight on reassurance, transparency, and visible human accountability.

For brands, this creates a more complex authenticity challenge. Trust can no longer be built through a single universal digital experience.

Responsibility is the pressure point for older consumers

The divide becomes even sharper when looking at the responsibility pillar.

Among consumers aged 62 and over, the responsibility gap - across transparency, human accountability, and perceived brand intent - reaches 48 percentage points. The 48pp responsibility gap shows where reassurance is missing for older consumers. This group needs to know what is happening, why, how their data is used, and how to reach a person. Make responsibility signals visible in the interface itself, ahead of policy pages or help-center searches.The 48pp gap among older consumers is a priority segment signal. Standard disclosure can satisfy the law and still fail the experience test for this group. Use clearer labels, simpler data explanations, and visible accountability cues in journeys with older users or high-stakes decisions.A 48pp responsibility gap means older consumers may enter service interactions with a heightened need for ownership. A fast automated response can feel hollow when it fails to show who is responsible. Route complex, unresolved, or sensitive issues to human support earlier for this audience.Older consumers make the responsibility gap especially consequential in financial services. These journeys often involve savings, retirement, insurance, credit, or fraud concerns, where unclear data use or missing human access quickly damages confidence. Add clear expert access, plain-language terms, and visible accountability to digital decision points.The 48pp responsibility gap among older consumers is a call to protect trust in patient-facing journeys. Older patients may need stronger reassurance around data use, care ownership, and next steps. Make human follow-up, clinical accountability, and plain-language explanations visible across portals, scheduling, billing, and results.For older financial-services customers, responsibility is the core design requirement. The 48pp age gap intersects with a category already split between trust and skepticism. Review retirement, claims, fraud, and advice journeys for data-use clarity, human escalation, and customer-interest explanations before adding more automation.

This is one of the strongest age-based findings in the study.

It suggests that older consumers are not simply less satisfied with digital experiences overall. They are especially sensitive to whether brands feel accountable, transparent, and acting in their interests.

For this audience, authenticity is closely tied to reassurance. They need to understand what is happening, why it is happening, how their data is being used, and how to reach a person if something goes wrong.

Younger consumers are more open to responsible AI

The age divide is especially visible in attitudes toward AI.

Younger consumers are more likely to see AI as beneficial when it is used responsibly. 83% of Gen Z consumers agree that AI can be beneficial when used responsibly, compared with 70% of consumers aged 62 and over (Baby Boomers and Silent Gen). Responsible AI reads as an expected service layer for Gen Z. 83% agree it can be beneficial when used responsibly, and 68% have disengaged after inauthentic experiences. Use AI where it improves speed, relevance, or content usefulness, and keep disclosure and quality strong for an AI-literate audience.The responsible-AI opportunity runs even stronger with millennials. 86% agree AI can be beneficial when used responsibly, above the 80% overall, and 71% are comfortable with AI personalization. Focus AI investment on personalized relevance and service speed, then explain the value exchange so useful personalization stays clear.Age differences should shape AI feature design. Younger audiences are more open to responsible AI, and older audiences need stronger explanations and human access. Build configurable disclosure, controls, and escalation into AI features so the same capability meets different trust thresholds.This argues against one uniform AI-disclosure pattern. Acceptance varies by generation, and undisclosed AI use damages trust for 84% of consumers aged 62+ against 52% of 18 to 29 year olds. Set a baseline disclosure standard, then add stronger explanations in high-stakes or older-audience journeys.Responsible AI can accelerate relevance for millennials. This audience is more comfortable with AI personalization than average, and the main risk is unexplained targeting. Add recommendation reasons, preference controls, and easy correction paths so personalization feels earned.

This does not mean younger consumers are uncritical; they’re also more likely to say AI-generated content is easy to spot, with 74% of 18–29s saying they can identify it, compared with 38% of consumers aged 62 and over.

AI may be more acceptable for younger users, but poor-quality, generic, or visibly artificial experiences are more likely to be noticed.

Older consumers need stronger reassurance

Older consumers show different sensitivities. They are less likely to say AI-generated content is easy to spot, but more likely to say undisclosed AI use damages trust.

84% of consumers aged 62 and over say undisclosed AI use decreases trust, compared with 52% of consumers aged 18–29. Undisclosed AI is a major trust hazard for older consumers. 84% say it decreases trust, and only 38% say AI-generated content is easy to spot. Use direct disclosure, plain explanations, and human contact routes so the experience never asks this audience to detect automation on its own.Disclosure needs calibrating to audience risk. Older consumers are far more likely to lose trust when AI is hidden, even though they are less likely to say they can spot it. Treat undisclosed AI as a high-risk practice in older-audience and high-stakes journeys.This is a credibility issue as much as a disclosure one. Older consumers may not always identify AI content, and they are much more likely to lose trust when they discover it was hidden. Make AI-assisted content feel honest through labeling, source quality, and clear human-review signals.For older audiences, content strategy should favor clarity over clever automation. This group has the strongest negative reaction to undisclosed AI, so hidden use can undermine even accurate messaging. Label AI-assisted experiences plainly and direct customers to a person when the content influences decisions.

Younger consumers may be more comfortable navigating AI-enabled digital experiences, but older consumers are more likely to need transparency, explanation, and visible routes to human support.

For brands, the implication is that AI disclosure and accountability cannot be designed for the most digitally fluent audience alone.

Human accountability becomes more important with age

The largest individual age gap sits in human accountability.

The gap between expectation and performance on human access widens from 24 percentage points among consumers aged 18–29 to 56 percentage points among consumers aged 62 and over. The 56pp human-access gap is one of the highest-leverage findings in the report. Older consumers over-index on wanting a real person quickly when something goes wrong, at 66% against 50% overall. Put human contact options in the main journey flow for account, payment, care, and service tasks.Gen Z's 24pp human-access gap is smaller, but human accountability still matters. 34% say no clear route to a human damages confidence, and 35% want a person quickly when things go wrong. Provide lightweight escalation through live handoff, callback, or clear ticket ownership.The age spread shows escalation design cannot stay uniform. Younger users accept more self-service, and older users need a much clearer route to human help. Segment support pathways by journey risk and customer need rather than channel cost alone.The human-access gap widening with age makes reassurance a design variable. A single help pattern can feel efficient to Gen Z and inaccessible to older consumers. Test high-stakes journeys by age group and adapt the prominence of human contact, explanations, and issue ownership.This gap argues for earlier human routing in complex journeys for older customers. A 56pp gap shows the current experience sits far from the reassurance this group expects. Create rules that surface phone, live chat, or callback options before repeated self-service failure.

This reinforces the broader responsibility pattern emerging between these two groups.

Authenticity cannot be one-size-fits-all

The generational divide does not mean brands need entirely separate digital strategies for every age group. But it does mean that authenticity signals need to be designed with different thresholds in mind.

Younger consumers may be more open to AI and personalization, but they are also more likely to notice when digital experiences feel artificial or generic.

Older consumers may be less confident identifying AI-generated content, but they are more likely to be affected by undisclosed AI use, unclear data practices, and lack of human access.

For marketing leaders, the challenge is to design experiences that can flex across these expectations.

CMO mandate: make digital authenticity an operating discipline

From insight to directive

The findings point to a clear conclusion: digital authenticity has become a strategic imperative for CMOs.

Consumer expectations are rising faster than brands are keeping pace. At the same time, the systems shaping digital experience - AI, automation, personalization, content, and data -are becoming more consequential to authenticity and trust.

Consumers demand more

The urgency is clear.

Consumers already see gaps across every signal in the Digital Authenticity Index. They expect brands to be accurate, relevant, transparent, accountable, and responsible. But performance falls short across the board.

They want brands to act.

89% of consumers say brands need to do more to improve digital authenticity. 40% say they need to do much more.

86% say digital authenticity should be a high or top investment priority. Consumers are giving permission to invest: 86% call digital authenticity a high or top priority, and 89% say brands must do more. Demand is rarely this clear. Move authenticity from brand sentiment into a funded operating discipline with an owner, a measurement model, and a roadmap, so the mandate consumers describe translates into budget. The 86% investment priority is a mandate the evidence can shape. The research already points to where returns concentrate: the responsibility signals with the widest gaps. Highlight the gap analysis when you brief leadership, so investment follows the signals that move trust instead of spreading evenly across experience improvements.

The commercial consequence is just as clear. 58% of consumers reduce or eventually abandon engagement when digital experiences are inconsistent or feel untrustworthy or inauthentic. At 58%, disengagement makes digital authenticity a growth and retention issue. 86% believe it should be a high or top investment priority. Connect authenticity metrics to churn, conversion, loyalty, and service cost so investment decisions reflect the behavior already happening.Disengagement is the penalty for experiences that contradict the brand promise. When customers reduce or abandon engagement after inauthentic digital moments, campaigns cannot fully repair the damage. Align claims, content, personalization, and support language so the brand promise holds in the journey itself.The 58% figure shows where authenticity becomes measurable behavior. Customers step away without a long pattern of failure, especially when support, accuracy, or transparency breaks in a high-stakes moment. Use abandonment and repeat-contact data to locate experiences that feel untrustworthy, then redesign the moment first.In retail, disengagement can follow a single product detail, delivery promise, return issue, or support failure. Retail ranks as no clear authenticity leader, so these moments become opportunities to stand apart. Tie product-content accuracy, fulfillment transparency, and service recovery to retention metrics.The commercial consequence runs sharper than average for Gen Z. 68% of 18 to 29 year olds have disengaged after an inauthentic digital experience, against 58% overall. Protect loyalty by keeping digital journeys fast, transparent, and credible, especially where AI content or personalization could feel generic.Disengagement runs above average for millennials, at 62%. This group stays highly open to responsible AI and personalization, so the opportunity is to use digital sophistication while showing why an experience is tailored. Make personalization explainable and easy to adjust before relevance turns into discomfort.Treat authenticity failures as leakage in the customer lifecycle. Product content, delivery updates, returns, and support are the touchpoints most likely to determine whether a shopper stays engaged. Monitor disengagement after these moments and fix the trust break before increasing acquisition spend.

Digital authenticity is not just a future concern. It is already shaping behavior.

The digital authenticity opportunity

As brands expand the use of AI, automation, personalization, data, and content systems, digital experiences can easily become more efficient but less human.

But those same capabilities also create the opportunity to strengthen authenticity when applied responsibly.

AI can improve accuracy. Personalization can increase relevance. Automation can make service faster and more seamless. Data can make journeys more useful. Content systems can create greater consistency across channels, markets, and moments. The opportunity is to aim digital investment at the right trust outcomes. AI, personalization, automation, data, and content systems strengthen authenticity when they close known gaps. Prioritize initiatives that improve accuracy, relevance, service recovery, and consistency, and pause investments that add volume without moving any of the nine signals.This passage turns the Index into a roadmap. Each capability ties to a trust signal: AI to accuracy, personalization to relevance, automation to service speed, data to journey usefulness, and content systems to consistency. Use those signal links as acceptance criteria for new features and platform investments.This is a product-strategy opportunity. Customers increasingly need tools that help them scale trusted experiences. Build capabilities that improve content accuracy, explain personalization, coordinate data, and preserve human oversight across customer workflows.Aim these capabilities at confidence as much as conversion. AI can improve product discovery, personalization can make offers more relevant, and automation can speed returns or service. Each can also feel intrusive when poorly designed, so tie them to product accuracy, delivery transparency, preference control, and fast issue resolution.The strongest use of these capabilities may be making complex information dependable and easy to act on. AI can improve product search, data can support compatibility and availability, and content systems can keep specs aligned across markets and partners. Prioritize use cases that reduce errors in product selection, configuration, and service.Govern these capabilities by the outcomes they produce for customers, because AI, data, personalization, automation, and content systems can close or widen responsibility gaps. Require each initiative to state its customer benefit, data-use explanation, disclosure plan, and human accountability model before launch.Pair the personalization roadmap with trust controls. Use AI for better discovery and service recovery, then give customers clear preference controls, recommendation explanations, and fast access to support. Measure whether these capabilities reduce returns, complaints, and abandonment alongside engagement.

What leading brands will do differently

Consumers are not asking brands to choose between scale and authenticity. They are asking brands to prove they can deliver both.

Leading brands will treat digital authenticity as an operating discipline, not a campaign message. This is the management shift the Index calls for. With 89% saying brands must do more and 86% calling authenticity a high or top investment priority, it needs governance, budget, and accountability. Assign executive owners for the nine signals and review progress like a business performance metric.Treating authenticity as an operating discipline means moving beyond campaign expression. Voice, claims, AI use, personalization, and service language need shared standards, because consumers judge the brand through every touchpoint. Create content and experience rules teams use before work goes live.An operating discipline means building authenticity into requirements and release criteria. The largest gaps are human accountability, intent, and transparency, so features should show who owns the experience, why something is personalized, and how customers get help. Add authenticity checks to discovery, QA, and post-launch optimization.An operating discipline is the path from policy to customer confidence. Governance belongs inside the experience, because consumers judge responsibility through what they can see and do. Embed privacy, AI disclosure, data-use clarity, and accountability checks into the same workflows that ship content and journeys.An operating discipline requires a measurement system that guides decisions. Track the nine signals over time, connect gaps to disengagement, and segment by audience group. The goal is to show leaders which authenticity investments most likely move trust, loyalty, and growth.This is where the Index becomes a planning tool. Use the nine signals to set investment priorities, then connect those priorities to business outcomes such as churn, conversion, service volume, and loyalty. That turns authenticity from a broad message into a growth discipline the business can measure.

They will build it into the systems, standards, and decisions that shape every interaction, and measure digital authenticity as a driver of trust, loyalty, and growth. They will shift from managing authenticity as a brand idea to operationalizing authenticity as a business discipline.