While Artificial Intelligence (AI) offers numerous advantages, its implementation is not without risks.
Businesses must navigate these challenges carefully to fully leverage AI while mitigating potential pitfalls.
Below, we explore some of the key risks AI can expose businesses to and how organisations can prepare.
Ethical considerations of AI
As AI becomes more integral to business operations, ethical concerns around its use are growing.
- Bias in algorithms: AI systems learn from data, and if that data contains biases, AI can unintentionally replicate and amplify them. For example, recruitment algorithms may inadvertently discriminate if trained on biased hiring data.
- Privacy concerns: AI systems often rely on vast amounts of data, raising questions about how that data is collected, stored, and used. Businesses must ensure compliance with data protection regulations like GDPR to maintain customer trust. Some platforms promise to ringfence data that is used, but a cautious approach should be taken.
- Transparency: AI decisions can sometimes appear as a “black box,” making it difficult to explain or justify the rationale behind certain actions. This lack of transparency can erode stakeholder confidence.
Deepfake frauds
AI’s ability to create realistic but fake content – commonly known as deepfakes – poses a significant risk to businesses and their financial safeguards.
There have already been several high-profile cases in which this technology has been used to scam businesses out of millions of pounds.
- Identity fraud: Deepfake technology can mimic voices and appearances, enabling fraudsters to impersonate executives or employees. This can be used to authorise fraudulent payments or manipulate sensitive information.
- Brand damage: Fraudulent use of a company’s brand or leadership image through deepfakes can tarnish reputation and reduce customer trust.
- Increased threat of scams: Sophisticated phishing attacks using deepfake audio or video can deceive employees and customers, leading to financial loss and data breaches.
Lack of AI regulation
AI technologies are advancing faster than national and global regulatory frameworks can adapt, creating a grey area for businesses using AI.
- Regulatory uncertainty: The absence of clear regulations around AI use can leave businesses exposed to legal risks if they inadvertently misuse the technology.
- Liability concerns: Without clear accountability standards, businesses may face challenges determining who is responsible for errors or unintended consequences of AI systems.
- Cross-border challenges: AI regulations vary by country, complicating compliance for multinational organisations using AI across jurisdictions.
Dependency on AI systems
Over-reliance on AI can make businesses vulnerable if systems fail or produce inaccurate outputs.
- System failures: AI tools are not infallible and may malfunction due to coding errors, lack of updates, or cyberattacks. A breakdown in critical AI systems could disrupt business operations.
- Human oversight: Some businesses may overestimate AI’s capabilities and fail to provide adequate human oversight, leading to poor decisions or overlooked risks.
- Skill shortages: As AI adoption grows, the demand for AI-literate professionals increases. Businesses may struggle to find or retain the talent needed to manage and monitor AI systems effectively.
Cybersecurity risks
AI introduces new vulnerabilities that cybercriminals can exploit.
- AI-powered attacks: Just as businesses use AI to enhance security, cybercriminals use AI to launch more sophisticated attacks, such as adaptive malware or automated phishing campaigns. At the moment, the number of AI-powered attacks launched has been quite small, but the risk is still very real.
- Data breaches: AI systems that handle sensitive data are prime targets for hackers. A breach could lead to significant financial and reputational damage.
- Supply chain risks: Businesses that rely on third-party AI providers are exposed to potential risks from vulnerabilities in the provider’s systems.
Resistance to change
The introduction of AI can sometimes face pushback from employees and stakeholders who fear its implications.
- Job displacement concerns: Employees may worry about AI replacing their roles, leading to resistance or disengagement.
- Adoption barriers: Stakeholders may hesitate to invest in AI due to its perceived risks or high upfront costs.
- Cultural misalignment: If AI adoption is not aligned with a company’s culture or adequately communicated, it can create friction within teams.
This is the latest article in a series of articles that we are preparing on AI and its impact on business and finance. You can find the previous parts below:
If you would like guidance on the adoption of AI, please get in touch with our Business Innovation team.