The concept of automation, including the adoption of Machine Learning and Natural Language Processing tools, has many benefits for business enterprises. But it presents many challenges like regulation, social responsibility or reputation. Many international organisations call for robust internal governance while using automation tools, like the Data Governance Act and Artificial Intelligence Regulation proposed by the European Union.
Internal governance defines the organisational and technical solutions within the company. It includes the fashion and rules used for reports, audit, control and data governance. The level of complexity of these rules depends on the size and the scope of activity of the company. It is the "proportionality rule".
Every institution using data as a source of information for its services and products need to report its operations. Reports will ensure you address every potential problem. It will also be necessary for implementing the automation tools. Feedback is a critical factor of success in AI.
Companies that wish to adopt automating tools should have at least:
A risk management system aligned to the profile of their business.
Record-keeping policies and procedures – for own purpose and external controls and audits.
Human oversight procedures ensure the identification and removal of any potential error.
Processes for creating and archiving documentation.
Specific guidelines for incident reporting and security breaches.
Strategy for the adoption of ICT tools.
Why is it important?
We live in a digital world with many incentives for fraud. Many cyber-fraudsters are looking for opportunities and easy profit. Using models and algorithms may put your organisation at risk for security breaches or data poisoning. Regulators and supervisors pay particular attention to robustness and cybersecurity. Responsible CEOs will think about internal governance as extra insurance, not cost. Effective internal management should give you more comfort and save you time, money and stress.