Automation is a hot topic across industries today, and incorporating automation into your business’s best practices can be tempting. But before you dive head-first into the world of automation, generative AI, and the like, there are significant potential risks to be aware of. In this blog, we will explore 3 important risks to consider before implementing automation into your business.
1. Data protection
This one might seem like an obvious risk, but there's more to it than you think.
Automation systems often handle large volumes of sensitive information, private personal information (PPI), protected personal information (PII), consumer data, financial records, etc. If this data is not properly managed and controlled, these automated systems can become highly coveted targets for cyber-attacks or data breaches.
When using automation to improve your processes, it's important to ensure that your systems are equipped with strong security measures to protect your data from unauthorized access. Some examples of robust data protection include:
Be sure to have a crystal-clear data protection policy in practice and train your employees on best practices for handling highly sensitive data. There can be severe consequences at stake if this is not properly executed, including legal penalties, loss of data, reputational damage, and more. It's imperative to take the proper precautions to safeguard your data before adding automation to your repertoire.
2. Ethical and legal implications
Automation in the business world often raises ethical and legal concerns. As generative AI and other forms of automation are evolving to take on more decision-making roles, it's essential to consider how these decisions align with your company's legal requirements and ethical standards.
From a legal perspective, you must ensure that your automation practices comply with the relevant regulations. This includes data protection laws like GDPR or CCPA, which mandate specific requirements for handling personal data. Failing to comply with these regulations can result in significant fines and legal repercussions.
Ethically, your business should be transparent about how adding automation into the mix may impact its stakeholders. This includes informing employees about potential job expectations and ensuring that automated decisions are fair and just. Balancing efficiency with ethical considerations is the key to maintaining trust and upholding your business's integrity.
3. Operational changes
Integrating automation into your business can also present several operational challenges. First, there's the risk of system integration issues. Automation often involves connecting various systems and software, which can sometimes lead to incompatibility, or problems with technical glitches. These issues can disrupt your operations and potentially affect your company's productivity.
With the added challenge of increased complexity in your internal processes, there is more room for error. While automation attempts to simplify tasks, the technology itself can pose different, more complex technical challenges. You'll need to be prepared to spend a significant amount of time and allocate the proper resources to set up and maintain your automation software. Ensure your employees receive proper training and documentation to help them operate as efficiently as possible with your new processes.
Moreover, the over-reliance on automation technologies can sometimes result in a loss of human oversight. It's essential to strike a balance between automated processes and human intervention to ensure that systems function correctly and adapt to any unforeseen challenges.
Mitigating risks of automation with data governance
While the risks of automation are real, they are not completely insurmountable. By proactively addressing data protection, ethical and legal concerns, and operation challenges, your business can navigate the complexities of automation more effectively. One way to mitigate these risks is by investing in robust data quality and data governance products. These tools can help ensure the accuracy and security of the data processed by your automation systems, providing an added layer of protection and reliability.
