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Generative AI-powered Social Engineering and Deepfake Detection - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026-2031)

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    Report

  • 181 Pages
  • July 2026
  • Region: Global
  • Mordor Intelligence
  • ID: 6260208
The generative aI-powered social engineering and Deepfake Detection Market size is expected to increase from USD 1.35 billion in 2025 to USD 1.65 billion in 2026 and reach USD 4.88 billion by 2031, growing at a CAGR of 24.22% over 2026-2031. This report is Segmented by Component (Software, and Services), Detection Modality (Video, Audio, Image, Text and Document), Deployment (Cloud, On-Premises, and Hybrid), Enterprise Size (Large Enterprises, and Small and Medium Enterprises), End-User Industry (BFSI, IT and Teleom, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Generative AI-powered Social Engineering and Deepfake Detection Market Trends and Insights

Rising Deepfake-Enabled Fraud in Digital Identity Workflows

The Generative AI-powered Social Engineering and Deepfake Detection Market is being pushed most directly by the industrialization of identity fraud across digital verification systems. AU10TIX reviewed more than 9 million identity verification transactions in Q1 2026 and found 3 active fraud rings running coordinated campaigns, with 1 campaign peaking at 1.3 million fraud events in a single day. The same report showed AI-generated selfie attacks rising 54.5% quarter over quarter in Q1 2026, while 67.6% of identity verification sessions still lacked deepfake detection. The Federal Reserve stated in April 2025 that deepfake attacks had increased twentyfold over the prior 3 years and urged banks to strengthen facial, voice, and behavioral identity checks. This pattern is widening the role of the Generative AI-powered Social Engineering and Deepfake Detection Market from a fraud tool into a required control for regulated digital identity workflows.

Agentic AI and Voice Cloning Increasing Social Engineering Attack Surface

The Generative AI-powered Social Engineering and Deepfake Detection Market is also rising because agentic AI can now sustain longer voice and video interactions that feel believable enough to bypass older verification habits. Pindrop stated in February 2026 that more than half of healthcare contact center fraud attempts now include AI-generated elements, which shows that the threat is no longer limited to consumer scams or isolated spoofing. The company also reported a 1,210% surge in AI-driven fraud attempts in 2025, reinforcing why telephony and contact center defenses are rising enterprise spending lists. Voice cloning tools can now generate convincing synthetic speech from as little as 3 seconds of source audio, weakening older methods that relied on familiarity with a caller’s voice or simple callback procedures. As a result, the Generative AI-powered Social Engineering and Deepfake Detection Market is seeing stronger demand for real-time audio analysis that can operate during the call rather than after the loss is already recorded.

False Positive Sensitivity in High-Stakes Verification Flows

The Generative AI-powered Social Engineering and Deepfake Detection Market still faces a hard adoption limit when legitimate users are flagged during sensitive verification events. iProov announced in February 2026 that its Dynamic Liveness solution achieved CEN/TS 18099 Level 2 High and Ingenium Level 4 certification, while maintaining a Bona Fide Presentation Classification Error Rate of 1.3%, a notable achievement that demonstrates deepfake resilience without a significant increase in false positives. That performance level is still difficult for much of the Generative AI-powered Social Engineering and Deepfake Detection Market to match consistently in real operating conditions. In contact centers, public telephone quality, mobile compression, and background noise narrow the practical accuracy gap between leading and average vendors, often forcing additional review steps. The result is slower deployment in healthcare, government, and financial workflows, where a wrongful denial can create operational, legal, and customer service costs.

Other drivers and restraints analyzed in the detailed report include:

  • Enterprise Shift Toward Multimodal Fraud Detection
  • Real-Time Verification Demand in Remote and Hybrid Workflows
  • Data Access Constraints for Model Training and Benchmarking

Segment Analysis

Software held a 61.02% share of the market in 2025, which shows that buyers still prefer platforms they can run continuously rather than isolated project work. The software layer in the Generative AI-powered Social Engineering and Deepfake Detection Market covers deepfake detection and authentication tools, biometric liveness checks, social engineering detection, and risk analytics that support the full identity attack chain. Enterprises favor software because detection logic must be updated often, and that makes recurring platform relationships more practical than one-time implementations. Reality Defender launched a public API and a free tier in July 2025, with 50 free detections per month, reflecting how software vendors are opening access to developer teams and large security buyers.

Services are projected to grow at a 25.41% CAGR through 2031, making them the fastest-growing component of the Generative AI-powered Social Engineering and Deepfake Detection Market. This growth reflects the need for continuous model retraining, managed detection, red-team operations, deployment support, and ongoing tuning as attack methods change. The 2025 Springer Nature research on audio deepfake detection supports this pattern, showing that performance degrades when models encounter unfamiliar synthesis methods. Service-heavy operating models are becoming increasingly important because many enterprises want help with response rules, human review paths, and ongoing testing, rather than just buying raw detection software.

Video detection accounted for 29.18% of the market in 2025, reflecting the weight of face-related fraud risk across onboarding, KYC, and live meeting environments. The Generative AI-powered Social Engineering and Deepfake Detection Market still places video first because face deepfakes can affect customer account opening, employee screening, and executive impersonation inside the same enterprise. Image detection supports adjacent use cases such as manipulated identity documents, while text and document detection are becoming more relevant as generated phishing content and fabricated records become easier to produce. iProov’s 2026 Threat Intelligence Report said that image-to-video tools are making it easier to create realistic synthetic identities from limited source material, which supports continued investment in video-focused defenses.

Audio detection is projected to grow at a 25.52% CAGR through 2031, making it the fastest-growing modality in the Generative AI-powered Social Engineering and Deepfake Detection Market. Pindrop said its platform can detect synthetic and bot-generated speech with up to 99.2% accuracy using 2 seconds of inbound audio in real time, which shows why category leaders are gaining attention in call-heavy workflows. Audio is scaling faster because voice remains a trusted channel in banking, insurance, healthcare, and account recovery, even though cloning tools have become easier to use and harder for humans to recognize. The gap between how quickly video defenses matured and how recently audio defenses started to scale suggests that fresh investment in voice-layer protection will remain strong across the forecast period.

Complete Report Scope:

  • By Component
    • Software
      • Deepfake Detection and Authentication Software
      • Biometric Liveness Detection Software
      • Social Engineering Detection and Prevention Software
      • Threat Intelligence and Risk Analytics Software
    • Services
  • By Detection Modality
    • Video
    • Audio
    • Image
    • Text and Document
  • By Deployment
    • Cloud
    • On-Premises
    • Hybrid
  • By Enterprise Size
    • Large Enterprises
    • Small and Medium Enterprises
  • By End-user Industry
    • BFSI
    • Healthcare and Life Sciences
    • Information Technology and Telecom
    • Retail and E-commerce
    • Industrial Manufacturing
    • Government and Public Sector
    • Other End-user Industries
  • By Geography
    • North America
      • United States
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Rest of South America
    • Europe
      • Germany
      • United Kingdom
      • France
      • Italy
      • Spain
      • Russia
      • Rest of Europe
    • Asia-Pacific
      • China
      • India
      • Japan
      • South Korea
      • Australia
      • Rest of Asia-Pacific
    • Middle East and Africa
      • Middle East
        • Saudi Arabia
        • United Arab Emirates
        • Rest of Middle East
      • Africa
        • South Africa
        • Nigeria
        • Rest of Africa

Geography Analysis

North America held a 32.13% share of the market in 2025, maintaining its lead in the Generative AI-powered Social Engineering and Deepfake Detection Market. The region benefits from a dense base of financial institutions, public agencies, and technology platforms that run high-assurance identity workflows every day. The Federal Reserve warned in April 2025 that deepfake attacks had increased 20-fold over the previous 3 years, reinforcing the need for stronger biometric and behavioral verification in banking. The SEC said in March 2025 that 25.9% of executives reported their organizations had experienced 1 or more deepfake incidents, which added further pressure on financial and corporate controls.

Europe is the second-largest regional market for generative AI-powered social engineering and deepfake detection, with Germany, the United Kingdom, and France as the main centers of enterprise demand. Regional adoption is being shaped by strong compliance expectations and by the need to protect digital identity, financial approvals, and corporate communications from manipulated media. Enterprises across the region are showing rising interest in auditable detection tools that can support disclosure, review, and evidentiary needs when suspicious content appears in regulated workflows. Data handling caution around biometric and identity media is also encouraging deployment choices that keep tighter control over sensitive inputs.

Asia-Pacific is projected to grow at a 25.96% CAGR through 2031, making it the fastest-growing region in the Generative AI-powered Social Engineering and Deepfake Detection Market. Growth is supported by the rapid expansion of digital payments, high transaction volumes, and a rising need to protect onboarding and verification systems from synthetic identity abuse. China’s synthetic content labeling rules took effect on September 1, 2025, and require platform-level content labeling and provenance controls, thereby increasing the operational need for detection infrastructure at scale. South America remains an earlier-stage opportunity, with Brazil standing out as digital banking and government identity programs broaden the number of exposed workflows. The Middle East and Africa are led by the United Arab Emirates and Saudi Arabia, where digital government programs and financial modernization are raising interest in deepfake defense tools. South Africa and Nigeria contribute to regional demand because mobile and digital banking channels create a larger base of customer interactions exposed to fraud.



List of Companies Covered in this Report:

  • Sensity AI
  • Paravision
  • Facia.ai
  • GetReal Security
  • identifAI
  • Reality Defender
  • Pindrop Security, Inc.
  • iProov Limited
  • BioID GmbH
  • Deepware A.S.
  • Attestiv, Inc.
  • ValidSoft Limited
  • AU10TIX Ltd.
  • HyperVerge Technologies Private Limited
  • Jumio Corporation
  • FaceTec, Inc.
  • Truepic, Inc.
  • Resemble AI, Inc.
  • DeepBrain AI, Inc.
  • Hive AI, Inc.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

Table of Contents

1 INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2 RESEARCH METHODOLOGY3 EXECUTIVE SUMMARY
4 MARKET LANDSCAPE
4.1 Market Overview
4.2 Market Drivers
4.2.1 Rising Deepfake-Enabled Fraud in Digital Identity Workflows
4.2.2 Enterprise Shift Toward Multimodal Fraud Detection
4.2.3 Real-Time Verification Demand in Remote and Hybrid Workflows
4.2.4 Expansion of API-Led Trust and Safety Integrations
4.2.5 High-Value Use of Synthetic Media Detection in BFSI and Government
4.2.6 Agentic AI and Voice Cloning Increasing Social Engineering Attack Surface
4.3 Market Restraints
4.3.1 False Positive Sensitivity in High-Stakes Verification Flows
4.3.2 Data Access Constraints for Model Training and Benchmarking
4.3.3 Fragmented Adversarial Attack Patterns Across Languages and Modalities
4.3.4 Budget Friction for Continuous Model Refresh and Human Review
4.4 Industry Value-Chain Analysis
4.5 Regulatory Landscape
4.6 Technological Outlook
4.7 Porter’s Five Forces Analysis
4.7.1 Bargaining Power of Buyers
4.7.2 Bargaining Power of Suppliers
4.7.3 Threat of New Entrants
4.7.4 Threat of Substitutes
4.7.5 Intensity of Competitive Rivalry
5 MARKET SIZE AND GROWTH FORECASTS (VALUE)
5.1 By Component
5.1.1 Software
5.1.1.1 Deepfake Detection and Authentication Software
5.1.1.2 Biometric Liveness Detection Software
5.1.1.3 Social Engineering Detection and Prevention Software
5.1.1.4 Threat Intelligence and Risk Analytics Software
5.1.2 Services
5.2 By Detection Modality
5.2.1 Video
5.2.2 Audio
5.2.3 Image
5.2.4 Text and Document
5.3 By Deployment
5.3.1 Cloud
5.3.2 On-Premises
5.3.3 Hybrid
5.4 By Enterprise Size
5.4.1 Large Enterprises
5.4.2 Small and Medium Enterprises
5.5 By End-user Industry
5.5.1 BFSI
5.5.2 Healthcare and Life Sciences
5.5.3 Information Technology and Telecom
5.5.4 Retail and E-commerce
5.5.5 Industrial Manufacturing
5.5.6 Government and Public Sector
5.5.7 Other End-user Industries
5.6 By Geography
5.6.1 North America
5.6.1.1 United States
5.6.1.2 Canada
5.6.1.3 Mexico
5.6.2 South America
5.6.2.1 Brazil
5.6.2.2 Argentina
5.6.2.3 Rest of South America
5.6.3 Europe
5.6.3.1 Germany
5.6.3.2 United Kingdom
5.6.3.3 France
5.6.3.4 Italy
5.6.3.5 Spain
5.6.3.6 Russia
5.6.3.7 Rest of Europe
5.6.4 Asia-Pacific
5.6.4.1 China
5.6.4.2 India
5.6.4.3 Japan
5.6.4.4 South Korea
5.6.4.5 Australia
5.6.4.6 Rest of Asia-Pacific
5.6.5 Middle East and Africa
5.6.5.1 Middle East
5.6.5.1.1 Saudi Arabia
5.6.5.1.2 United Arab Emirates
5.6.5.1.3 Rest of Middle East
5.6.5.2 Africa
5.6.5.2.1 South Africa
5.6.5.2.2 Nigeria
5.6.5.2.3 Rest of Africa
6 COMPETITIVE LANDSCAPE
6.1 Market Concentration
6.2 Strategic Moves
6.3 Market Share Analysis
6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
6.4.1 Sensity AI
6.4.2 Paravision
6.4.3 Facia.ai
6.4.4 GetReal Security
6.4.5 identifAI
6.4.6 Reality Defender
6.4.7 Pindrop Security, Inc.
6.4.8 iProov Limited
6.4.9 BioID GmbH
6.4.10 Deepware A.S.
6.4.11 Attestiv, Inc.
6.4.12 ValidSoft Limited
6.4.13 AU10TIX Ltd.
6.4.14 HyperVerge Technologies Private Limited
6.4.15 Jumio Corporation
6.4.16 FaceTec, Inc.
6.4.17 Truepic, Inc.
6.4.18 Resemble AI, Inc.
6.4.19 DeepBrain AI, Inc.
6.4.20 Hive AI, Inc.
7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK
7.1 White-Space and Unmet-Need Assessment

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • Sensity AI
  • Paravision
  • Facia.ai
  • GetReal Security
  • identifAI
  • Reality Defender
  • Pindrop Security, Inc.
  • iProov Limited
  • BioID GmbH
  • Deepware A.S.
  • Attestiv, Inc.
  • ValidSoft Limited
  • AU10TIX Ltd.
  • HyperVerge Technologies Private Limited
  • Jumio Corporation
  • FaceTec, Inc.
  • Truepic, Inc.
  • Resemble AI, Inc.
  • DeepBrain AI, Inc.
  • Hive AI, Inc.