The question we're answering
“Where are staff using unsanctioned AI, and what data is exposed?” Shadow AI adoption almost always outpaces official policy: employees paste sensitive data into consumer AI tools, or adopt browser extensions and integrations nobody reviewed, long before any governance conversation happens.
Who this is for
Organizations that suspect, or know, employees are using AI tools outside any approved list, and need to find out the real scope before writing policy in a vacuum.
What this covers
A Shadow AI review answers the questions governance can't start without:
- Discovery: which AI tools are actually in use across the organization, sanctioned or not
- Data classification: what sensitivity of data has been exposed through unsanctioned tools
- Policy gap identification: where the current policy (if any) fails to address real behavior
- Remediation path: sanctioned alternatives and a realistic adoption plan, not just a ban
Outcomes & deliverables
- A real inventory of unsanctioned AI tool use, not a guess
- A data-exposure assessment for what's already happened
- A remediation plan that accounts for why employees reached for these tools in the first place
- A direct feed into your broader AI Governance policy
How we approach it
Identify unsanctioned AI tool use across the organization.
Assess what data has been exposed, and how sensitive it is.
Sanctioned alternatives, policy update, and ongoing monitoring.
Supporting technology
Where the gap is a lack of any sanctioned alternative, we can point to Bonfy.AI, an affiliated technology, as one option, referenced only where it genuinely supports the outcome.
Regulatory readiness
Governance work here feeds directly into regulatory evidence, not just internal policy.
Industries & use cases
Proof
50 active enterprise clients, 100+ SMB clients, and 1,000+ assessments delivered per year: this isn't our first engagement like yours.
Expert reviewer
