Enterprise AI
Enterprise AI
What is enterprise AI?
- AI services built to meet enterprise requirements for security, administration, and contracts
- The key difference: input data is not used to train the model
- Provides admin features such as account management, usage controls, and audit logs
What changes when you adopt enterprise AI is not the screen but who owns the account. The moment employees move from accounts they created with personal email to accounts under a company-signed contract, who entered what and when comes under the company’s control. You can shut off a departed employee’s account the same day, and when something goes wrong you can trace what happened from the logs. Under a personal-account setup, by contrast, the most a company can do is announce “Do not upload work materials,” and it has no way to verify which files were actually uploaded.
The options generally fall into three tiers. Personal paid plans give you more capability but no admin features, so they are not suited to company-wide adoption. Team plans run about KRW 30,000 (≈ US$22)–40,000 per person per month and offer an admin console and a no-training clause, though they often come with a minimum seat count. Enterprise contracts are where SSO, automatic account provisioning and deprovisioning, audit logs, data retention settings, and data residency options become available. Heavily regulated industries such as finance and healthcare may even consider private deployments that host the model inside their own cloud, but you should budget up front for the fact that build and operations staffing costs can run several times the per-seat price. This is why you should not choose a plan based on a single clause saying your data is 'not used for training'.
The most common mistake in practice is believing security is done once the contract is signed. An enterprise contract protects against training of external models; it does not replace internal access management. Tools that search internal documents inherit the existing shared-folder permissions, so at a company that hasn’t cleaned up its permissions, an employee in their third month can end up getting a summary of executive salary files. The second misconception is that buying seats will bring adoption with it. Unless you reclaim and reassign unused seats every quarter, the budget gets cut at the renewal meeting a year later with the remark that “only the same few people use it.”
John KimInstructor John Kim, author of B2B Marketing Design and CEO of Nanum Consulting
Ara LimExpert in global leadership, AI, and business communicationStarting with the launch of ChatGPT Enterprise in 2023, major AI companies built out enterprise lineups, which became the market standard.
Consider a hypothetical case. Company A is a manufacturer of consumer-goods components with 380 employees and annual revenue of around KRW 120 billion (≈ US$89,780,000). During a first-half review, the information security team found that employees were using AI through personal accounts, which kicked off a four-month adoption project.
- When the head of information security pulled the proxy logs, 210 company PCs had accessed AI sites in the past three months, and 14 of those cases showed traces of cost sheets and drawing files being uploaded.
- The CFO balked at “KRW 130 million (≈ US$97,300) a year to buy seats for all 380 people,” so the plan was reworked: contract only 120 seats for the three highest-usage departments first and run a 6-week pilot.
- An IT manager added SSO and audit logs and set data retention to 30 days, but by week 4 of the pilot, only 46 of 120 people were using it twice a week or more.
- The training team ran 2-hour hands-on sessions for sales, purchasing, and development. Then a prompt for drafting emails to overseas suppliers, built by Kim in purchasing, was posted to the internal board, and requests from other departments came pouring in.
- Six months later, users working with it twice a week or more had grown to 101 of 120 (84%), PCs accessing personal accounts fell from 210 to 18, and the average time to draft a reply to an overseas quote request dropped from 40 minutes to 12.