Is AI a Hero or a Villain? These 4 Rules Will Decide AI can be a powerful business ally or a risky liability — these four ethical principles determine which.

AI is forging a new era for business innovation. Over 50% of US companies with more than 5,000 employees use artificial intelligence on a daily basis, a figure that climbs to 60% for those exceeding 10,000 employees.

However, such a quick spread of AI comes with a set of ethical considerations. On average, 40% of employees find that AI use has resulted in diverse ethical dilemmas, defined by the Capgemini Research Institute as outcomes that are non-transparent, unfair or biased. The question is how we can boost efficiency and make AI work for the best interests of society. Let's explore four key principles that will turn AI into your business hero.

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1. Prioritizing transparency

According to the CX Trends Report, 65% of customer experience leaders now see AI as a strategic necessity. Meanwhile, businesses need to move beyond the 'black box' approach and show how they work with AI systems — clear explanations of how algorithms function, the data they utilise, decision-making processes and any potential biases. This fosters trust and ensures that all parties (customers, partners, other stakeholders) can confidently engage with AI-driven technologies.

Cosmetic retailer Lush publicly champions ethical AI usage, engaging in open dialogue and communicating its ethical AI position through various channels, including social media. The company is committed to transparency: it's clear through its refusal to employ social scoring systems or technologies that could compromise customer privacy or autonomy.

Similarly, Adobe, when releasing its Firefly generative AI toolset, provided clear information about the data used for model training, including details on all utilised images, confirming ownership or public domain status. These measures empower users to make informed decisions regarding copyright compliance.

2. Ensuring privacy

While employees increasingly start to use AI on a daily basis, often without explicit employer knowledge, this trend can come with potential privacy concerns. A recent study by CybSafe and The National Cybersecurity Alliance highlights that 52% of individuals who use AI for work have not received training on safe AI usage.

At the same time, 38% of employees admitted they shared sensitive information without getting the permission of their employer, potentially exposing confidential data, intellectual property or customer details. Furthermore, 65% of respondents said they do not feel secure in the means of AI-related cybercrime, underscoring the growing recognition of associated threats.

Professionals must attentively review the privacy policies and terms of service of AI solutions, focusing on data collection, usage, storage and third-party sharing to ensure security and maintain customer trust. This understanding is a strong foundation for informed communication with clients regarding the risks and benefits of AI.

Consequently, organisations must create clear guidelines and instructions for protecting employee and organisational data. Ethical AI implementation begins with developing comprehensive policies addressing accountability, explainability, fairness, privacy and transparency.

Chinese chatbot DeepSeek R1 is a great example of the consequences of neglecting security measures. Security testing conducted by researchers from Cisco and the University of Pennsylvania revealed that the system failed to block any of 50 potentially harmful commands. In contrast, other leading AI models proved to show higher security levels, with vulnerabilities ranging from 26% to 96%.

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3. Eliminating bias

Research, recently published in JAMA Network Open, indicates that 83.1% of AI models carry a high risk of bias, with common issues as inadequate sample sizes and insufficient handling of data complexity. AI is learning from the prompts created by people, so it can reflect preconceived notions from the data they are trained on, underscoring the necessity of serious fairness testing and fact-checking.

Striving for equity when developing algorithms is a very important yet complex task, as data often mirrors existing social inequalities and developers may unintentionally introduce their own biases.

To mitigate this, it is essential to utilise data that accurately represents reality, rather than perpetuating existing disparities.

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4. Amplifying human potential

The true potential of AI lies not in replacing human efforts but in enhancing the overall performance, using it as a complement, not a substitute for human input. For instance, while humans alone may achieve an average accuracy of 81%, and AI alone 73%, their collaboration can reach 90% accuracy. AI can efficiently handle routine tasks, freeing up teams to focus on more strategic, empathetic and creative tasks.

A compelling example of this approach is my company's rebranding, where AI was employed to generate a special visual style. While AI excelled in providing a visual framework and idea generation, it also required the refining of skilled designers and illustrators to ensure quality and coherence. Zendesk's AI chatbots handle standard customer inquiries, reducing the workload on human operators. When complex issues arise, the chatbot seamlessly transfers the conversation to a real person to get a special touch of human empathy.

Integrating these four principles — transparency, privacy, bias elimination and collaboration — is a strong formula for bringing AI's benefits into your business while still harnessing its power ethically. The future of AI hinges on our commitment to responsible development and deployment, ensuring it serves as a hero in our increasingly digital world.