In the ever-evolving landscape of finance, the integration of Artificial Intelligence (AI) is rapidly becoming a game-changer. Businesses are leveraging AI technologies to streamline processes, enhance accuracy, and provide more valuable insights. However, amid this high-speed journey, it's crucial to recognise the cybersecurity risks associated with handling sensitive client information through AI systems.
Traditionally, AI has been associated with automating mundane tasks such as data entry and transaction categorisation. Although the speed and efficiency of these tasks can be greatly improved using AI, the potential application reaches far beyond. For example, businesses will have the ability to apply AI-powered algorithms to develop real-time predictive analytics. This will allow businesses a complete understanding of the qualitative and quantitative characteristics of the business and could promote timely, well-informed decision making from management.
Consider a scenario where a retail business is struggling to understand the strategies of their competitors. Management may implement an AI competitor analysis system to continuously monitor competitors' online activities, pricing strategies and customer reviews. This information could then be considered during decision making processes and help strengthen the business’ competitive position.
What is the risk of using AI?
The advantages of AI do come with a warning. Machine learning, a fundamental aspect of AI, relies on the accumulation of user-input data to train and improve models. While this data recycling is essential for the development of AI models, it also presents a key information risk when dealing with sensitive business data. AI can’t ‘unlearn’ information, after all.
Some of the potential risks and downsides businesses using AI face include:
- Data Security and Privacy Concerns
One of the foremost risks associated with AI implementation is the vulnerability of sensitive data. As AI systems rely heavily on vast datasets, businesses need to ensure they have robust data security measures. The potential for data breaches, unauthorised access, and misuse poses a significant threat.
Some platforms store all your conversations on their servers, creating a risk that sensitive data is exposed if the servers are hacked, or potentially used to generate answers for other users. Other AI models such as ChatGPT 4 (paid version) and Bing Enterprise Chat only temporarily store your data and delete it after the chat is finished. Despite this being safer, cybersecurity is still a concern.
To safely use AI in business, users must understand how any data is being used and stored, and steer away from including sensitive information and data in their use.
AI algorithms are only as unbiased as the data they are trained on. If the training data is skewed, the AI system can perpetuate and even exacerbate existing biases. This can lead to discriminatory outcomes, damaging the reputation of the business and undermining trust.
AI models, especially deep learning algorithms, are often considered black boxes. The lack of transparency can make it challenging for businesses to understand how decisions are reached, hindering trust among stakeholders.
The integration of AI into business processes may lead to operational disruptions if not executed properly. This can include technical glitches, system failures and even employee resistance to change.
The regulatory landscape surrounding AI is continuously evolving. Non-compliance with existing and emerging regulations can result in legal consequences and reputational damage.
- Cultural context and language adaptation
Many marketing and communications practitioners already make wide use of AI tools to assist in the generation of content. When using AI generated content it is important to remember that the language has not been adapted to your organisation’s tone or culture. Equally, often the language used or provided by AI is not inclusive or accessible.
While the benefits of integrating AI into business operations are undeniable, it is crucial for organisations to approach this technological evolution with a keen awareness of the associated risks.
How can we help mitigate the risk of using AI?
AI is developing rapidly and providing many opportunities to improve existing business processes and analytics for informed strategic decision making. AI-powered algorithms will not only allow for the automation of mundane, repetitive tasks, they will be able to provide management with detailed business analysis in real-time. However, users must be mindful of entering sensitive information and be aware of the risks associated with machine learning and the storing of their data.
A business or risk advisor can help guide businesses through the complex terrain of AI implementation, offering expertise in data security, operational efficiency and regulatory compliance.
Moore Australia’s advisors have extensive experience in assisting clients with innovation, future proofing and change management projects. Contact us today to discuss this further.