Generative AI: Ethics and growth are not opposing forces
From our blog / Article
Generative AI is revolutionising industries and reshaping how organisations innovate and grow. Its capabilities stretch far beyond efficiency, offering opportunities to reimagine collaboration, decision-making, and societal impact. However, with such transformative potential comes responsibility. Among the many ethical considerations, addressing bias is critical to avoid harm—not only because it affects fairness but because it directly impacts an organisation's ability to innovate and compete in an increasingly diverse and globalised market.
Bias in generative AI is not simply a technical issue; it mirrors the inequalities, prejudices, and systemic gaps embedded in the data it was trained on and processes. For instance, an AI model designed to analyse historical narratives might predominantly highlight male figures if trained on texts that historically excluded or minimised the contributions of women. Similarly, an AI focused on curating educational materials may fail to adequately represent diverse female achievements if its training data lacks inclusive perspectives. Such shortcomings not only diminish the richness of the historical record but also continue to present a one-sided view of history and potentially alienate audiences seeking a more comprehensive and representative business delivery.
Generative AI, when implemented with a strong ethical framework, can go beyond avoiding bias to actively address it and utilising it for the benefit of the business. For example, AI can identify patterns of exclusion in historical or organisational data, offering actionable insights to improve inclusivity.
This not only enhances fairness but also taps into the business advantages of diversity. Research consistently shows that organisations with diverse teams and inclusive cultures outperform their less diverse counterparts, generating higher revenues, greater innovation, and stronger employee satisfaction.
With this vision in mind, my question for every forward-thinking leader is:
“How can we utilise generative AI to tackle deep-rooted diversity challenges in organisations, transforming them into opportunities for innovation and growth, while reimagining solutions that create ripple effects—improving culture, driving inclusion, and unlocking untapped markets for sustainable success?”
Diversity as a catalyst for growth
A growing body of research highlights the business case for diversity. For instance, McKinsey’s studies reveal that companies in the top quartile for gender and ethnic diversity are more likely to achieve above-average profitability, stats state ethnic and cultural diversity on executive teams are 36% more likely to outperform their peers financially and companies in the top quartile for gender diversity on executive teams are 25% more likely to have above-average profitability. (Ref: Diversity wins; Delivering through diversity)
Logical as diverse teams bring varied perspectives, enabling them to tackle problems creatively and design products or services that resonate with broader markets due to better understanding of customer needs. When generative AI is applied to support such teams—acting as a neutral facilitator, a data-driven advisor—I would argue it increases these advantages, perhaps helping organisations innovate faster and connect with diverse customer bases by enabling true AI + Human collaboration that combines the logical and the emotional in a balanced way. I find this thought fascinating!
Consider the example of “Herstory Reimagined,” a project aimed at uncovering and highlighting women’s overlooked contributions to history. Generative AI could analyse historical texts to highlight patterns and gaps and provide a richer, more inclusive storyline that give arguments for customer solutions that otherwise would remain hidden. The educational materials produced would not only enhance public understanding but also demonstrate the potential of AI to positively influence cultural and social norms.
In a business context, similar principles apply. AI can assist organisations in identifying underrepresented customer segments or addressing systemic gaps in their operations, ultimately driving growth and market expansion.
Ethics and growth are not opposing forces
Ethical considerations around generative AI, including bias, are often framed as challenges to overcome. Yet, these considerations are also opportunities for growth. Addressing bias not only mitigates risks but positions organisations as leaders in responsible innovation. Customers and stakeholders are increasingly drawn to companies that demonstrate social responsibility and inclusivity, seeing these values as markers of trustworthiness and vision.
For example, organisations that prioritise ethical AI usage can unlock new markets by designing products and services that appeal to underrepresented demographics. AI tools that reduce biases in hiring or customer service can enable a more inclusive workplace culture, leading to higher employee retention and satisfaction, which in turn according to research usually correlates with growth. Transparency in how AI is deployed can strengthen stakeholder relationships, turning ethical practices into a competitive advantage.
The role of research and ethical implementation
Recent research underscores the importance of integrating ethical practices into AI development. Studies also highlight that diverse teams are better equipped to identify and mitigate biases in AI models, as they bring unique insights into how different communities might be affected.
“Organisations such as OpenAI, Google DeepMind, and others have begun increasingly investing in AI ethics research, creating frameworks that guide how these technologies should be developed and deployed responsibly.”
Moreover, industry collaborations, such as the “Partnership on AI”, provide avenues for organisations to share best practices, address common challenges, and develop standards that ensure generative AI benefits society at large. Businesses that actively engage in such research and collaboration demonstrate a commitment to ethics that resonates with employees, partners, and customers alike.
Business growth through responsible AI
The potential for generative AI to drive business growth lies not just in its technological capabilities but in how thoughtfully it is applied. For example:
- Innovation and market expansion: AI can analyse diverse customer data to uncover untapped markets and design products tailored to their needs with help of identity-specific LLMs.
- Efficient decision-making: By reducing bias, AI helps organisations make fairer, data-driven decisions that improve outcomes for all stakeholders creating not only better places for work but also possibilities in developing new markets and gaining market share through new customer share.
- Stronger team collaboration: AI can facilitate balanced discussions, ensuring all voices are heard and bringing fore a culture of inclusion that boosts employee engagement and via that finding suitable solutions.
“At its best, generative AI is a tool for progress—one that aligns ethical considerations with the pursuit of excellence and growth.”
Leader, don't leave growth opportunities on the table!
Approach Generative AI as more than just a tool—it has the potential to be a transformative partner in shaping the future and unlocking new possibilities with agility and precision. By prioritising ethics and addressing challenges like bias in LLMs, organisations can turn potential risks into opportunities, into new business growth.
Imagine a future where AI agents, each representing diverse viewpoints, engage in logical conversations to explore solutions that might elude human teams, often constrained by emotional or cognitive overload. This collaborative approach between humans and AI could guide the way for businesses to not only innovate but also create a future that is inclusive, impactful, and truly sustainable. Lets make the best out of AI!
