Convertr today added a governance module to its portfolio of data management tools that promises to make it simpler to ensure customer contacts and sales leads meet compliance requirements before being entered into a customer relationship management (CRM) application or another type of system of record.
Greg Jordan, chief product officer at Convertr, said Convertr Govern makes it possible to ensure organizations comply with data rules and regulations that are becoming more stringent in the age of artificial intelligence (AI).
Convertr Govern now makes it possible to enforce policies across campaigns, sources, suppliers, markets and use cases down to the account level, with evidence behind each policy applied preserved in a way that is easily auditable, noted Jordan.
If a record falls outside policy, it does not just move through a workflow. A named approver, a recorded decision and a reason are required before the record can proceed. Output is generated in the form of an Evidence Pack that identifies for any customer record its source, supplier, the campaign that generated it, the policy and controls applied, what failed, who approved an exception, why the decision was made and where the record went. That capability is critical because many organizations today are unsure they can pass a compliance audit, noted Jordan.
While the number of compliance mandates that apply to customer data is expanding, it’s not clear how aggressively they might be enforced. However, before too long auditors will be applying AI agents to surface violations. As such, organizations should expect the amount of the fines being assessed for failing to comply with a mandate to increase. The only way to forestall those levies is to have a governance framework in place that prevents those issues from ever arising in the first place, said Jordan. It’s now more a question of when, not if, many organizations will need to revisit how they manage data in the AI era. More issues will arise as AI agents that are accessing data at machine speed are deployed in ways that expose weaknesses in existing controls. It’s already been shown that AI agents will explore any and every means available to access data regardless of what guardrails may have been applied to them. The challenge now is to make sure controls are consistently applied long before any data might ever be exposed to an AI agent, noted Jordan. In effect, organizations are now at an inflection point that will require a different approach to managing data as risk levels continue to rise, he added.
Less clear is how proactively organizations will be when it comes to rising to the challenge. There may need to be a few examples of costly fines being levied before organizations allocate the resources required to apply policies and controls before data is entered into a system of record. Regardless of how organizations come to terms with those requirements, the days when employees could be allowed to be cavalier about how data is collected, stored and used are coming to a close.