AI FAQs for Business in 2026

AI BASICS

What is artificial intelligence (AI)?

Artificial intelligence (AI) refers to computer systems designed to perform tasks that normally require human intelligence, such as language generation, image recognition, decision-making, prediction, and automation.

Modern AI systems can analyze large amounts of data, recognize patterns, generate content, and assist with complex business workflows across industries including health care, manufacturing, finance, and cybersecurity.

What is generative AI?

Generative AI is a category of artificial intelligence capable of creating new content such as text, images, video, audio, software code, and summaries. Popular examples include ChatGPT, Microsoft Copilot, Gemini, Claude, and image-generation tools.

Businesses increasingly use generative AI for productivity, customer support, automation, marketing, software development, and data analysis.

What's the difference between AI and machine learning?

Artificial intelligence is the broader concept of machines performing tasks associated with human intelligence. Machine learning is a subset of AI focused on systems that learn patterns from data rather than relying solely on explicitly programmed instructions.

Learn more about the difference between AI and machine learning.

AI SECURITY & RISK

What are the cybersecurity risks of AI?

AI introduces risks including data leakage, prompt injection, credential theft, deepfake impersonation, insecure plugins, hallucinated outputs, privacy violations, and shadow AI adoption. Scammers are also increasingly using AI to improve phishing campaigns, automate reconnaissance, and create synthetic media for fraud.

Businesses should establish AI governance controls, employee usage policies, and monitoring procedures before deploying AI tools broadly.

What is Shadow AI?

Shadow AI refers to employees using unauthorized or unapproved AI tools without formal oversight from IT, cybersecurity, legal, or compliance teams. This can expose organizations to data leakage, regulatory violations, intellectual property risks, and inconsistent governance practices.

Learn more about Shadow AI risks.

DEEPFAKES & AI IMPERSONATION

What is a deepfake?

A deepfake is a video, image, or audio clip generated or manipulated using AI to make someone appear to say or do something they didn't. Deepfakes can be highly convincing, particularly in compressed video or low-bandwidth call environments where quality artifacts are harder to spot.

How common are deepfake attacks on businesses?

According to a Deloitte poll, nearly 26% of executives reported their company experienced at least one deepfake incident in a 12-month period. Incidents are underreported due to reputational concerns, so actual prevalence is likely higher.

Can you always detect a deepfake visually?

No. Detection rates depend on the quality of the deepfake, the viewing conditions, and the observer's experience. Low-resolution video calls, compressed recordings, and high-quality synthesis tools all make visual detection less reliable. Manual observation should be combined with automated tools and process controls rather than treated as a standalone defense.

What is out-of-band verification?

Out-of-band verification means confirming a request through a separate, pre-established channel rather than continuing on the channel where the suspicious request arrived. If a video call asks you to initiate a wire transfer, out-of-band verification means hanging up and calling the requester back using a number from your internal directory, not one provided during the call.

What should employees do if they suspect a deepfake?

Don't engage further with the suspicious request. Report it immediately through your company's incident response channel. If a financial transaction is already in motion, contact your financial institution as quickly as possible since speed is critical for reversing fraudulent transfers. Document what you observed, including the platform used, the nature of the request, and any anomalies you noticed.

Does cyber liability insurance cover deepfake fraud losses?

Coverage varies significantly by policy and insurer. Some cyber insurance policies cover social engineering fraud, which can include deepfake-enabled wire transfer fraud, while others exclude it or require a separate endorsement. Review your policy with your broker and confirm whether social engineering coverage applies and what documentation requirements you must provide to initiate a claim. A risk assessment can identify gaps in your coverage and controls.

Can Microsoft Teams, Zoom, or Google Meet calls be deepfaked?

Yes. Hackers can use AI-generated video and voice during live meetings to impersonate executives, vendors, coworkers, and clients. Some attacks use pre-rendered synthetic video, while more advanced attacks use real-time face and voice manipulation during active calls.

Video conferencing platforms themselves are not necessarily compromised. Instead, attackers abuse the trust people place in seeing and hearing familiar individuals during meetings. Businesses should treat video calls as one factor of identity verification, not proof of identity on their own.

Are deepfake attacks considered business email compromise (BEC)?

Often, yes. Many business email compromise (BEC) attacks now include AI-generated audio, video, or text impersonation as part of a broader campaign. Scammers may begin with phishing emails, then escalate to voice calls, messaging apps, or video meetings to pressure staff into approving payments or sharing sensitive information.

Security teams increasingly view deepfake fraud as an evolution of social engineering rather than a completely separate threat category.

Can AI-generated voices bypass MFA or identity verification?

In some cases, yes. AI-generated voices have been used to target call centers, password recovery workflows, and voice authentication systems. While many biometric platforms include liveness detection and anti-spoofing controls, no system is perfect.

Companies should avoid relying solely on voice recognition for high-risk account recovery or financial authorization processes.

How can businesses reduce deepfake risk?

The most effective defense combines employee training, identity verification procedures, financial approval controls, and detection technology. Key protections include multi-person approval for wire transfers, out-of-band verification for sensitive requests, phishing-resistant MFA, and regular social engineering awareness training.

Businesses should also establish incident response procedures specifically for impersonation attacks and synthetic media fraud scenarios.

Are deepfakes illegal?

Legality depends on how the deepfake is used. Some uses of synthetic media are lawful, including entertainment, parody, accessibility, and creative applications. However, deepfakes used for fraud, harassment, election interference, identity theft, extortion, or non-consensual intimate imagery may violate federal or state laws.

What is synthetic media?

Synthetic media refers to digital content generated or modified using artificial intelligence. This includes AI-generated images, video, audio, text, and avatars. Deepfakes are one category of synthetic media focused on realistic impersonation or manipulation of people.

Synthetic media can be used legitimately for entertainment, accessibility, marketing, and creative applications, but it can also be abused for fraud, misinformation, and impersonation attacks.

Can scammers clone a voice from social media videos?

Yes. Many modern voice-cloning tools can generate convincing synthetic speech using only short audio samples taken from social media videos, podcasts, webinars, interviews, or voicemail greetings. Public-facing executives and sales staff are especially exposed because hackers can often find hours of recorded speech online.

Businesses should assume publicly available audio can potentially be used for impersonation attempts and build verification controls accordingly.

Regulatory requirements are evolving rapidly. Businesses should monitor state disclosure laws, privacy regulations, and platform liability requirements related to AI-generated content.

What is a voice cloning scam?

A voice cloning scam uses AI-generated speech to impersonate a trusted individual such as an executive, employee, family member, vendor, or financial institution representative. Hackers use cloned voices during phone calls, voicemails, or video meetings to pressure victims into transferring money, revealing credentials, or bypassing security procedures.

These scams often rely on urgency, secrecy, and emotional pressure rather than technical sophistication alone.

Should businesses create a deepfake response policy?

Yes. Businesses should establish formal procedures for verifying sensitive requests, reporting suspected impersonation attempts, preserving evidence, and escalating potential fraud incidents. Policies should also define who is authorized to approve payments, change banking information, or release sensitive data.

Can deepfake scams target small businesses?

Yes. Small and midsize businesses are increasingly targeted because attackers often assume they have less formal approval processes and fewer dedicated security controls. A small finance team, limited segregation of duties, or informal communication culture can make impersonation attacks easier to execute successfully.

Deepfake fraud is no longer limited to large enterprises or public companies.

Can deepfakes bypass video identity verification systems?

Some deepfake systems are capable of challenging basic identity verification workflows, particularly those relying only on static facial matching or low-friction selfie checks. Many modern verification platforms now include liveness detection, device intelligence, and behavioral analysis to reduce spoofing risk.

Companies handling regulated data or financial transactions should evaluate whether their identity verification providers include anti-deepfake protections.

What are the warning signs of an AI impersonation attack?

Common warning signs include unusual urgency, requests for secrecy, pressure to bypass standard procedures, communication from unfamiliar numbers or accounts, requests to move conversations to personal platforms, and financial instructions that differ from normal workflows.

Technical anomalies such as unnatural speech rhythm, inconsistent lighting, lip-sync issues, or visual artifacts may also appear, but behavioral indicators are often more reliable than media quality alone.

Can attackers create real-time deepfakes during live calls?

Yes. Some advanced tools can manipulate facial appearance and voice output during live video or audio conversations in near real time. These systems are becoming more accessible as generative AI technology improves and hardware requirements decrease.

Businesses should assume that live communication channels can potentially be spoofed and should maintain verification procedures for high-risk requests.

Are executives at higher risk for deepfake impersonation?

Yes. Executives are common targets because their authority can override normal skepticism during financial or operational requests. Public appearances, conference presentations, interviews, earnings calls, podcasts, and social media videos also provide attackers with training material for voice and facial cloning systems.

CEO fraud and executive impersonation attacks increasingly incorporate AI-generated media to appear more convincing.

Can deepfakes be used in hiring scams?

Yes. Some attackers use AI-generated video or manipulated identities during remote job interviews to conceal their real identity, location, or qualifications. Organizations have also reported cases involving synthetic resumes, AI-assisted interview responses, and impersonated candidates attempting to gain access to corporate systems.

Businesses should strengthen remote hiring verification procedures, especially for sensitive technical or privileged-access roles.

A documented response process helps reduce confusion during high-pressure incidents and improves consistency across departments.

How do deepfake attacks usually begin?

Many deepfake attacks begin with traditional social engineering techniques such as phishing emails, credential theft, social media research, or business email compromise. Attackers gather information about organizational structure, communication habits, vendors, and executive behavior before launching impersonation attempts.

The AI-generated media is often only one part of a larger fraud campaign designed to build credibility and urgency.

How do deepfake attacks usually begin?

Many deepfake attacks begin with traditional social engineering techniques such as phishing emails, credential theft, social media research, or business email compromise. Attackers gather information about organizational structure, communication habits, vendors, and executive behavior before launching impersonation attempts.

The AI-generated media is often only one part of a larger fraud campaign designed to build credibility and urgency.

Can deepfake detection tools produce false positives?

Yes. Low-quality recordings, compression artifacts, poor lighting, unstable internet connections, and background noise can sometimes trigger false positives in automated detection systems. Human review and contextual verification remain important even when detection tools are deployed.

Organizations should treat detection scores as indicators of risk rather than definitive proof of manipulation.

How should finance teams respond to suspicious payment requests?

Finance teams should pause the transaction and verify the request using a separate trusted communication channel before proceeding. Employees should never rely solely on email, voice calls, or video meetings for high-risk financial approvals.

Businesses should document escalation procedures in advance so employees know exactly who to contact and what verification steps are required during suspected fraud attempts.

Can phishing-resistant MFA help reduce deepfake risk?

Yes. While phishing-resistant MFA does not directly detect deepfakes, it helps reduce account compromise that often supports impersonation campaigns. Attackers frequently combine deepfake tactics with stolen credentials, session hijacking, or business email compromise.

Hardware security keys, passkeys, and FIDO2-based authentication are generally stronger protections than SMS-based MFA for high-risk accounts. Learn more about passwordless authentication.

Why are deepfake attacks difficult to stop?

Deepfake attacks are difficult to stop because they exploit human trust rather than only technical vulnerabilities. Attackers combine realistic AI-generated media with urgency, authority, emotional pressure, and compromised communication channels to influence employee behavior.

Detection technology continues to improve, but organizational controls and verification culture remain essential because no single technical solution can fully eliminate impersonation risk. Companies should regularly test executive impersonation and wire fraud scenarios through cybersecurity tabletop exercises.

Can AI tools leak sensitive business data?

Yes. Employees may unintentionally submit confidential information, intellectual property, customer data, financial records, or regulated information into public AI platforms. Depending on the platform configuration and terms of service, submitted content may be retained, logged, or used for model improvement.

AI GOVERNANCE & COMPLIANCE

Are businesses required to comply with AI laws?

Increasingly, yes. Multiple states and international jurisdictions are introducing laws governing AI transparency, automated decision-making, privacy protections, synthetic media disclosures, and high-risk AI systems. Check out the STACK State AI Laws Guide for comprehensive details regarding AI legislation introduced and passed in all 50 states.

Should businesses create an AI usage policy?

Yes. Businesses should define which AI tools are approved, what data employees may submit, how outputs should be reviewed, and what security or compliance requirements apply to AI-assisted workflows.

AI policies should also address privacy, intellectual property, vendor risk, data retention, and employee accountability.

What is AI governance?

AI governance refers to the policies, controls, oversight processes, and risk management practices companies use to manage AI systems responsibly.

Effective AI governance typically includes security reviews, vendor assessments, employee training, compliance monitoring, incident response procedures, and executive oversight.

AI Readiness Survey

Should businesses assess AI readiness before deployment?

Yes. AI readiness assessments help companies evaluate licensing requirements, security controls, governance maturity, compliance obligations, identity protections, and operational risks before adopting AI platforms at scale.

Learn more through the STACK AI Hub.

Can AI improve cybersecurity?

Yes. AI is increasingly used in threat detection, behavioral analytics, phishing prevention, anomaly detection, endpoint monitoring, and security automation. Many modern security platforms rely on machine learning to identify suspicious activity more quickly than traditional rule-based systems alone.

However, scammers are also using AI offensively, creating an ongoing AI-versus-AI security environment.

Are attackers using AI for phishing attacks?

Yes. AI tools are increasingly used to generate realistic phishing emails, multilingual scams, social engineering scripts, fake login pages, and impersonation campaigns. AI can improve grammar, personalization, and scalability for attackers.

Learn more about phishing attacks.

AI STRATEGY & BUSINESS IMPACT

Will AI replace employees?

AI is more likely to change job functions than eliminate all jobs entirely. Many businesses are using AI to automate repetitive tasks, assist decision-making, improve productivity, and augment employee workflows rather than fully replace human workers.

Businesses should focus on governance, training, and responsible adoption to maximize benefits while reducing operational risk.

What industries are most affected by AI regulation and risk?

Health care, financial services, manufacturing, education, government contractors, legal services, and companies handling sensitive personal data face elevated AI governance and compliance obligations.

High-risk sectors should pay close attention to evolving privacy laws, cybersecurity requirements, and automated decision-making regulations.

Businesses should monitor evolving requirements including the EU AI Act, Colorado AI laws, and broader state AI regulations.

Companies should establish approved AI usage policies and review vendor data handling practices before deploying generative AI tools.

Learn more in our complete Deepfake Detection Guide.

MICROSOFT COPILOT AI FAQs

The questions in this section are lifted from our companion page, Microsoft AI Decision Brief.

Is Microsoft Copilot secure for business?

Microsoft Copilot includes enterprise security and compliance controls, but companies still must configure permissions, data access, retention policies, and governance procedures.

Misconfigured access controls can expose sensitive data through AI-generated responses.

Is Microsoft Copilot a separate tool?

No. Copilot is embedded inside M365 applications such as Outlook, Teams, Word, Excel, and PowerPoint. It operates within your existing tools.

How does Copilot help with SharePoint and OneDrive?

Copilot allows you to search, summarize, and compare documents using natural language instead of manual navigation. It generates responses based on files you have existing permission to access.

What are Copilot agents?

Copilot agents are task-focused AI experiences that help retrieve and organize data from sources such as SharePoint or OneDrive.

Is Copilot secure?

Copilot follows existing Microsoft 365 permissions, but security depends on how access controls, data governance, and user behavior are managed within your company.

Can I turn off Copilot in my environment?

Yes. Copilot is controlled through Microsoft 365 licensing and administrative settings. Companies decide which users have access and can disable or limit it based on security, compliance, or rollout strategy.

Does it cost extra to get Copilot in M365?

Generally, yes. Copilot is licensed as an add-on to existing subscriptions and isn't included in standard business plans by default.

What are the Copilot AI usage limits?

Copilot doesn't use a daily limit for most enterprise users. Usage is governed by M365 service controls designed to maintain performance instead of limiting or restricting activity.

What are tokens?

Tokens are the small units of text AI tools process when generating responses. A token can be a word, part of a word, or even punctuation. AI systems use tokens to understand input and produce output. But in Copilot, this gets managed on the back end so it's not something users typically see.

Does Copilot use tokens like other AI platforms?

Copilot is built on large language models (LLMs) that process data as tokens, but this isn't exposed to end users. Businesses don't manage token counts. Usage is managed in M365.

Related AI & Cybersecurity Resources

• AI Security Checklist for Businesses
• What Is Shadow AI?
• How Phishing Attacks Work
• What Is MFA?
• Incident Response Best Practices
• State AI Laws Guide