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Home Market Research Market Analysis

Trust And Privacy Amid GenAI, Deepfakes, And Privacy Tech

by TheAdviserMagazine
1 month ago
in Market Analysis
Reading Time: 3 mins read
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Trust And Privacy Amid GenAI, Deepfakes, And Privacy Tech
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In 2026, the world’s trust landscape will be more fragmented than ever. Consumers and businesses alike are learning to operate in a permanent state of skepticism, where trust is earned through action, not assumption. Forrester’s 2026 trust and privacy predictions reveal how organizations must adapt to survive — and thrive — in this environment. Here’s a preview of three pivotal trends that will shape the year ahead.

Consumers Will Embrace GenAI In High-Risk Scenarios — Despite Low Trust

Trust in institutions and brands has eroded globally, with consumers turning to personal networks and curated sources for guidance. Trust is also low in artificial intelligence — especially in high-stakes contexts. For example, Forrester’s Global Government, Society, And Trust Survey, 2025, finds that only 14% of online adults in Australia, the UK, and the US trust AI in scenarios like self-driving cars. We predict, however, that by 2026, 30% of consumers will use generative AI tools for high-risk decisions such as personal finance and healthcare.

Why the paradox? AI usage is climbing globally. As we highlighted in our other research, in North America, 38% of US online adults have used generative AI, with 60% of those using it weekly. In Europe, nearly a third of consumers have tried genAI tools. And in APAC, adoption is highest in metro India, where over half of online adults report using it. We initially hypothesized that consumers would use genAI in low-risk use cases such as translation tools or chatbots,but many consumers have become fairly savvy when it comes to AI. Particularly, those who consider themselves knowledgeable about AI are aware of both the risks and the opportunities. Where access or affordability limits access to services — e.g., financial or healthcare advice — many consumers are choosing to leverage genAI while mitigating risks by cross-referencing AI outputs, validating sources, and consulting professionals after using AI tools. This means that organizations must continue to experiment in this area — while mitigating AI risks.

Deepfake Detection Spending Will Surge As Deepfakes Go Mainstream

Emerging technologies often see adversaries act first, with enterprises scrambling to catch up. Deepfakes are no exception. In 2026, deepfakes will become mainstream, and the threat will shift from reputational damage to direct monetization by bad actors. Enterprises are responding: We predict that spending on deepfake detection technology will grow by 40% in 2026, with adoption spanning industries and use cases.

For example, media firms are deploying deepfake detection for content authentication while help desk teams use it to defend against social engineering attacks, such as those seen in the Scattered Spider campaign. Financial services are leveraging detection tools to prevent fraud, and HR teams are integrating them into interview processes to combat synthetic identity scams, including those linked to North Korean IT worker schemes. The global imperative is clear: Organizations must evaluate deepfake detection providers now and update processes that are most at risk to stay ahead of this rapidly evolving threat.

Privacy-Preserving Technologies Will See Consolidation

As data privacy regulations tighten and AI adoption accelerates, privacy-preserving technologies are becoming essential for organizations seeking to protect personal data while enabling innovation. In 2026, Forrester predicts five or more acquisitions of privacy-preserving tech companies as large vendors and data platforms race to augment their offerings.

The focus is shifting from traditional privacy filtering — like masking and tokenization — to advanced controls that protect data during processing. Techniques such as homomorphic encryption, secure multiparty computation, runtime encryption, and synthetic data are gaining traction globally. For example, synthetic data allows organizations to reduce risks associated with real data samples but requires careful compliance with all applicable regulations. Companies must evaluate the privacy-preserving technologies that best fit their risk profiles and compliance needs as these capabilities become a competitive differentiator in the global market.

To explore all of Forrester’s 2026 trust and privacy predictions and access the full report, read the published research here. Forrester clients can also register for our upcoming webinar on November 20, 2025.



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