AI is revolutionising industries, but it comes with its own set of challenges. Navigating the evolving landscape of AI can be complex, with rapid technology updates and legal changes. As a result, some companies are uncertain about adopting AI and concerned about how to approach it. Others fear being left behind and feel pressured to act quickly.
However, rushing into adopting AI without planning use cases, and assessing potential hazards, is risky.
The Hidden Risks of AI
From bias and discrimination to privacy and security concerns, and lack of transparency, AI requires careful risk management. This is especially true for sectors like healthcare, finance, or transportation, where the impact of failures can be severe. In addition, AI tools are now more accessible to the public. These tools can produce very convincing content, which may not be accurate or good quality.
Responsible AI, combined with a clear AI strategy, is crucial to address these challenges. It takes a holistic approach, tackling social, ethical, compliance, and governance risks for organisations.
Organisations must have a robust AI Governance framework in place, including policies and risk management processes. These measures ensure that Responsible AI principles are effectively implemented, and supported by the necessary structure. It’s also crucial that they align with the company’s AI strategy, values, and goals.
Building a Strong Governance Framework
AI Governance should tie in with existing company governance structures and programmes. Aligning with international standards, such as ISO 42001, ensures that key elements of AI risk management are covered. Another important step is employee training in the benefits and risks of AI. This builds awareness in the organisation to increase effectiveness and reduce risks. In addition, it complies with The EU AI Act AI literacy requirement to train employees using or building AI systems. Together, these measures increase transparency, define accountability, and mitigate risks in business operations.
It’s essential to understand the unique AI challenges for each company and the sector in which it’s based. For example, in healthcare, it is critical to make sure patient privacy, quality of care, and data security are protected. Responsible AI policies need to be tailored to these, to make sure they are adequate and effective for the company. This bespoke approach is essential to develop guidelines and governance that work in practice.
Keeping Up with AI Laws
Staying ahead of legal changes in the AI world is vital. Global updates on AI laws and regulations are now released at a similar pace to technical news on the latest models. Companies need to make sure their AI strategies and policies are aligned with the latest legal developments. This is especially important when working across several regions, with differing legal obligations. A proactive approach is essential to navigate this changing landscape and ensure compliance. This is key in safeguarding the company’s reputation and legal standing.
A Catalyst for Innovation
When implemented correctly, AI can deliver positive benefits for organisations.
Project SEEKER is one example of this. It was developed by BJSS, in collaboration with Heathrow Airport, Microsoft, UK Border Force, and Smiths Detection. The AI system automatically detects illegal wildlife in luggage and cargo at borders. This alerts enforcement agencies. The project has aided in the fight against illegal wildlife trafficking with over 70% accuracy.
AI Governance plays a key part in project success and can be a powerful driver of business innovation and growth. It provides a secure and compliant environment for AI adoption and development.
The Future of AI
Addressing bias, privacy, and regulatory standards means companies can mitigate legal and reputational risks.Responsible AI is more crucial than ever. AI is now being used in many different contexts, and tools are more widely accessible to the public. Companies must carefully assess use cases and manage risks to make the most of the technology. Responsible practices, clear AI governance, and regulatory compliance are vital for sustainable success with AI. By focusing on these, businesses can ensure that AI continues to benefit both their operations and society at large.
- Data & AI