Artificial intelligence can help accounting and tax firms work faster.
It can summarize documents, help draft emails, organize information, and make routine work easier.
But AI is also changing cybersecurity risk.
Cybercriminals can now create more convincing phishing emails, imitate voices, generate realistic video, and disguise familiar scams in ways that are much harder for employees to recognize.
For accounting and tax firms responsible for tax records, Social Security numbers, payroll data, financial information, and other sensitive client data, that creates more than a technology concern.
It creates cyber liability.
Cyber liability is the business, legal, regulatory, operational, and reputational exposure a firm carries when cybersecurity responsibilities are not properly understood or managed.
The good news is that your firm does not need every employee to become an AI expert.
You need clear rules, dependable verification, sensible safeguards, and a team that understands what to do before a suspicious request arrives.
Here’s what that looks like.
AI Shapeshifters: Deepfakes Make “It Sounded Like Them” Less Reliable
One of the biggest AI cybersecurity risks for accounting firms is impersonation.
AI tools can now create realistic voice recordings and video that imitate real people. A fraudulent phone call may sound like a managing partner. A video message may appear to come from a client. A voice message may seem to be from a vendor or employee.
That changes an important assumption.
Recognizing someone is not the same as verifying them.
For accounting and tax firms, this matters when a request involves:
- Money transfers
- Banking changes
- Password resets
- Tax documents
- Payroll information
- Client financial records
- Account access
- Changes to sensitive systems
The answer is not teaching every employee how to detect a deepfake.
Deepfake technology will continue to improve.
A stronger approach is to build verification into the process.
For example, a firm might require employees to verify sensitive requests using a known phone number rather than the contact information provided in the request.
Financial changes might require a second approval.
Account access can be protected with multifactor authentication.
High-risk requests can follow a documented approval process.
The goal is simple:
Make the process stronger than the impersonation.
AI may be able to imitate someone’s voice.
It cannot automatically bypass a verification process your team consistently follows.
That is why good cybersecurity depends less on perfect detection and more on dependable procedures.
AI Mummies: Phishing Emails Look Better Than They Used To
Phishing emails used to be easier to recognize.
Many contained obvious spelling mistakes, awkward sentences, strange greetings, or poor grammar.
Employees were often taught to look for those warning signs.
AI is making that advice less reliable.
A cybercriminal can now use artificial intelligence to create phishing messages that sound professional, use correct grammar, and closely resemble normal business communication.
The scam underneath may be old.
The wrapping is simply better.
That means employees should focus less on whether an email looks professional and more on what the message is asking them to do.
Questions employees should ask before acting on an email
Does the message ask you to:
- Change banking information?
- Reset a password?
- Share client data?
- Open an unexpected attachment?
- Download a file you were not expecting?
- Change payroll or payment instructions?
- Bypass an established process?
- Take immediate action because something is supposedly urgent?
Those requests deserve verification even when the email looks completely legitimate.
That becomes especially important during tax season.
Busy teams are processing returns, answering client questions, collecting documents, managing deadlines, and dealing with hundreds of messages.
When people are rushed, they have less time to study every email carefully.
That is why simply telling employees to “watch out for phishing” is not enough.
Give them a process.
Sensitive financial changes should require verification.
Unexpected requests involving client information should be confirmed through another trusted channel.
Requests to bypass normal procedures should raise a question.
Suspicious messages should have a clear reporting path.
Clear rules are easier to follow than vague warnings.
AI Vampires: The Risk of Putting Sensitive Client Data Into AI Tools
Another growing AI risk for accounting and tax firms is something that may not look like a cyberattack at all.
An employee may simply be trying to save time.
They might copy information from a tax document into an AI tool and ask for a summary.
They might upload a spreadsheet for analysis.
They might paste an email containing financial information into an AI assistant and ask it to write a response.
No hacker had to break into the firm.
The sensitive information was voluntarily placed into the tool.
This is sometimes part of a broader issue known as Shadow AI - employees using AI applications that have not been approved or reviewed by the organization.
The employee may have good intentions.
The cyber liability remains.
What should accounting firms know before employees use AI?
Before sensitive information is entered into an AI platform, leadership should understand:
- Which AI tools are approved?
- What information can employees enter?
- What information is prohibited?
- Where does information entered into the tool go?
- How long is that information stored?
- Can the AI provider use or retain the information?
- Who reviews new AI applications?
- What should employees do when they are unsure?
These questions do not require every employee to understand how artificial intelligence works.
They require the firm to establish boundaries.
A practical AI-use policy should be easy enough for an employee to understand during a busy workday.
If employees have to read a 50-page document to figure out whether client tax information belongs in an AI tool, the policy probably will not help when it matters.
Education should make the safe choice easier.
Why AI Cybersecurity Is a Cyber Liability Issue for Accounting Firms
AI cybersecurity is not only an IT issue.
For an accounting or tax firm, a cybersecurity event can affect far more than computers.
It can disrupt operations.
It can expose confidential client information.
It can create legal or regulatory questions.
It can trigger cyber insurance issues.
It can cause clients to question whether their information is being protected.
And it can damage the professional reputation the firm has spent years building.
That broader exposure is why cyber liability is more useful than thinking only about whether a firm has “checked the compliance box.”
Compliance may tell you that a requirement exists.
Cyber liability asks a larger question:
What could happen to the firm, its clients, and its ability to operate if the responsibility behind that requirement is not properly managed?
That is the whole risk.
And it is why AI use belongs in leadership conversations, not only technical ones.
The Best Defense Against AI-Powered Cyber Threats? Better Rules
Artificial intelligence is making some cyber threats faster, cheaper, and more convincing.
But that does not mean your accounting firm is powerless.
It means some older assumptions need to change.
You can no longer depend on bad grammar to identify phishing.
You cannot assume a familiar voice proves someone’s identity.
You cannot assume a popular AI tool is automatically appropriate for sensitive client information.
And you cannot assume employees understand the rules unless those rules have been explained clearly.
A stronger approach starts with a few practical safeguards.
1. Verify sensitive requests
Create an established process for financial changes, password resets, account access, banking instructions, and other high-risk requests.
Do not let urgency replace verification.
2. Use multifactor authentication
MFA creates another barrier when usernames or passwords are compromised.
It also makes account access less dependent on a password alone.
3. Establish clear AI-use rules
Employees should know which AI tools are approved and what information may or may not be entered into them.
4. Teach employees what the rules mean
Do not simply send a policy and assume people understand it.
Explain the reason behind the rule.
Give examples.
Show employees what to do when they are unsure.
5. Protect sensitive client information
Know where sensitive data is stored, who can access it, and which applications interact with it.
6. Test your backups
Having a backup and being able to restore your firm are not always the same thing.
A backup should be tested before the day you actually need it.
7. Document your safeguards
Good cybersecurity should produce evidence.
You should be able to explain what protections are in place, how they are being used, and what has been reviewed.
That proof becomes valuable when a client, insurer, auditor, or other stakeholder asks how your firm is managing risk.
What Should an Accounting Firm Do About AI Cybersecurity?
Start by understanding what is already happening inside your firm.
You may discover that employees are already using AI.
That is not automatically a problem.
The important questions are whether leadership knows how AI is being used, whether sensitive information is being protected, and whether clear rules exist.
Ask your team:
What AI applications are you using?
What are you using them for?
Are you entering client information?
Are there tasks where you are unsure whether AI use is appropriate?
You may learn more from those conversations than you expect.
From there, you can begin identifying where clearer rules, additional safeguards, or better education may be needed.
You do not need to fix everything in one day.
You need to understand where you stand and make informed decisions about what comes next.
AI Cybersecurity FAQ for Accounting and Tax Firms
What is the biggest AI cybersecurity risk for accounting firms?
There is no single AI risk that applies equally to every firm. Common concerns include AI-powered phishing, voice and video impersonation, employees placing sensitive information into unapproved AI applications, and relying on outdated methods to identify scams. The right priority depends on how the firm operates and where sensitive information is handled.
Can AI make phishing attacks harder to detect?
Yes. AI can help attackers write polished, natural-looking messages without the spelling and grammar mistakes that traditionally made phishing easier to recognize. Employees should evaluate the request itself and follow verification procedures rather than relying only on how professional an email looks.
What is Shadow AI?
Shadow AI is the use of artificial intelligence tools inside an organization without formal approval, review, or oversight. It can create risk when employees enter confidential, financial, tax, personal, or other sensitive information into tools the firm has not evaluated.
Should accounting firms ban employees from using AI?
A complete ban is not necessarily the right answer for every firm. AI can provide real productivity benefits. The more useful approach is to understand how employees are using AI, decide which tools and uses are acceptable, establish boundaries for sensitive information, and educate employees on the rules.
Why is multifactor authentication important when dealing with AI-powered threats?
AI can make social engineering more convincing, but MFA adds another barrier to account access even if a password is exposed or an employee is deceived. It is one safeguard within a broader verification and access-control process.
Is AI cybersecurity a compliance issue?
It can involve regulatory and contractual requirements, but the risk is broader than compliance alone. AI-related cybersecurity can create business, legal, regulatory, operational, insurance, and reputational exposure. That broader exposure is cyber liability.
How can an accounting firm reduce cyber liability from AI?
Begin by understanding how AI is being used, create clear rules for sensitive information, verify high-risk requests, use multifactor authentication, educate employees, review data access, test backups, and document the safeguards in place. The goal is not zero risk. The goal is informed risk management supported by evidence.
You Don’t Need to Become an AI Expert
That may be the most important point.
You do not need to understand every new AI application.
You do not need to become an expert at spotting deepfakes.
And you do not need to predict every new cybersecurity threat that may appear next year.
You do need to understand the risks you are responsible for.
You need a process for evaluating them.
You need safeguards your employees can follow.
And you need evidence that your protections are doing what you believe they are doing.
That matters when your cyber insurance renewal arrives.
It matters when a client asks about your security program.
It matters when someone asks about your WISP.
And it matters when a convincing request reaches an employee during the busiest week of tax season.
Cyber liability is not about panic.
It is about clarity, preparation, and proof.
Halloween monsters disappear when the decorations come down.
AI-powered cyber risk will continue to change.
The best response is not fear.
It is knowing where you stand, understanding what matters, and making informed decisions before the difficult moment arrives.
Not Sure What AI Risk Looks Like Inside Your Firm?
If you are unsure how AI is already being used, whether sensitive client information may be reaching unapproved tools, or whether your current safeguards are enough, start with a conversation.
Schedule a Discovery Call with MTS.
We’ll help you understand the cyber liability questions worth asking, identify areas that may deserve a closer look, and clarify the information you need to make an informed decision about what comes next.
