Regardless of any regulation, it makes sense to change the way people drive more ethical and inclusive behavior, use data, and understand why the differences between people can make both business and broader society a better place. For sure, profit is still fundamental, but a better balance is needed to create real value, and, as society and business evolve, to ensure that organizations are more flexible and inclusive.
Having the organizational awareness and conscience around ethics and diversity encourages managers to do this. Developing risk frameworks gives people the principles, policies, and standards that are expected. Regular audits and monitoring offer teams the tools needed to ensure compliance and course-correct challenges.
In an interview, diversity advocate and thought leader Kim Gray summarizes this nicely:
“Diversity, equity and inclusion should be an important strategic consideration for talent acquisition, management, and building a positive culture. This isn’t a nice to have but a critical component that builds a real sense of belonging for staff within the organization. It’s key to building a great place to work and a driving force behind joint collaboration and stronger relationships across teams. Never has this been a more important topic than in the building of products and services, AI driven or otherwise, that represent organizations’ diverse customer base.”
Turning Insight Into Impact
To move from good intentions to meaningful change, organizations must take action. Here are three essential steps to ensure that data and AI strategies are not only effective and responsive, but also ethically grounded, inclusive by design, and aligned with the wider organizational culture:
1. Build a culture that embeds diversity and ethics: Rather than simply being “add-ons,” these elements should be at the heart of company culture in order to promote responsible data and AI practices.
2. Design AI and data strategies with diverse inputs: Avoiding bias is key to achieving equitable outcomes. Actively seeking inclusive, representative data helps to reduce organizational blind spots.
3. Establish governance to support ongoing accountability: It’s essential to set up frameworks to ensure ongoing monitoring and, as the organization continues to evolve and scale, to allow for course corrections where necessary.
To truly unlock the business growth capabilities of data and AI, strategy must be grounded in diversity and aligned with an organization’s values. When inclusive data is supported by ethical, diverse teams and a culture of accountability, the result is not just smarter business, but also meaningful impact for society as a whole.
Adapted from Data Means Business: Level Up Your Organisation to Adapt, Evolve and Scale in an Ever-Changing World (Rethink Press, 2nd edition, 2025)