Customer-Centric AI: Major Paradigm Shift in AI Governance (Part 4)
Three reasons why customer-centric AI is a major paradigm shift in AI Governance
After I’ve discussed
WHY to be a customer-centric AI company (part1),
HOW to be a customer-centric AI company (part 2) and,
WHAT actions to take to be a customer-centric AI company (part 3),
I’ll move on to explaining
Why customer-centric AI is a major paradigm shift in AI Governance (part 4).
Read all the previous parts here:
Technological innovation has been driven primarily by private companies in recent decades, with the majority of research and development now carried out by the corporate sector in developed countries. This is a logical development as private firms are more forward-thinking and innovative than government entities due to market pressures and the need to stay competitive. Most likely private companies will continue to play a significant role in driving technological innovation including Artificial Intelligence. While the AI Governance field in a broader sense covers government regulations and corporate policies, standards, or codes of conduct, we should strive to make the AI Governance field as business-friendly as possible.
Working with businesses in the last several years, I’ve seen how alienated most of the companies have been from current AI Governance approaches and concepts - ‘Ethical AI’, ‘responsible AI’, or ‘trustworthy AI’ struggles to provide tangible tools that resonate with companies. Those who innovate and drive technological revolutions need rather pragmatic guidance which is at the same time underpinned by ethics, responsibility, or trust.
The Major Paradigm Shift in AI Governance, Customer-Centric AI:
1. Is tangible and realistic for businesses
When we talk about "human-centric AI," "responsible AI," or "trustworthy AI," the concepts often feel abstract and theoretical - Responsible to whom? Trustworthy for whom? They are noble goals but can be difficult to translate into actionable business strategies. Customer-centric AI, on the other hand, is grounded in something every business understands — making customers happy. It's a tangible and realistic objective that aligns directly with business goals. By focusing on customer satisfaction, companies can develop AI technologies that are immediately relevant and beneficial to their core operations, making the concept easier to grasp and implement. Customer-centricity focuses on improving the lives of customers through specific products and services rather than attempting to address broader societal issues or making sweeping changes aimed at benefiting humanity as a whole.
Governments and international organizations can focus on broader human-centric AI policies, while businesses concentrate on customer-centric solutions. This separation of responsibilities ensures that businesses can effectively contribute to AI governance without being overwhelmed by broader societal goals (however, this does not exclude businesses from considering societal implications, see part 3 where I explain the ‘societal layer’ of AI Governance).
Edit: more detailed explanation of this in part 5: “Human-Centric AI vs Customer-Centric AI.” Read here
2. Encourages genuine (customer) care
A customer-centric approach inherently involves caring about what truly matters to your customers. This naturally leads businesses to ask important ethical questions: Are we respecting our customers' privacy? Are we using AI to enhance their experience in meaningful ways? This shift makes ethical considerations a natural part of the business process rather than an obligatory checkbox. Moreover, this perspective transforms regulations from burdensome restrictions into helpful guides. Regulations are typically designed to protect fundamental human rights, and when businesses are genuinely focused on customer-centricity, these regulations help ensure that companies meet basic ethical standards.
When you truly care about your customers, you learn to ask better questions, make more informed decisions, and learn from your mistakes. This care is reflected in every decision you make, every line of algorithmic code you write, every compliance box you tick, and every piece of feedback you respond to. Customer-centricity fosters a cultural shift within an organization, encouraging employees at all levels to prioritize customer welfare. This mindset leads to more cohesive, mission-driven teams and promotes a holistic approach to decision-making that considers the broader impact on customers. This, in turn, can lead to more balanced and thoughtful business strategies that prioritize long-term benefits over short-term gains both for businesses and for customers.
3. Improves decision-making
Traditionally, businesses have relied heavily on internal expertise and complex algorithms to drive decision-making. While these methods are valuable, they often lack the nuanced understanding that comes from direct customer interactions. A customer-centric AI approach revolutionizes this by integrating the collective wisdom and insights of the customers themselves.
As AI is a powerful technology unlike any other, making life-altering decisions for others—such as those involving career, diet, finance, or health—can be incredibly challenging. Internal governance structures and algorithms, no matter how advanced, can struggle to address the diverse and dynamic needs of a broad customer base.
By actively involving customers in the development and refinement of AI technologies, businesses not only enhance their decision-making processes but also build stronger, more trust-based relationships. Customers feel valued and heard, which increases their engagement and loyalty. This collaborative process encourages continuous improvement and innovation, as businesses stay attuned to evolving customer needs and preferences. True innovation arises when companies combine their internal expertise with the lived experiences of their customers, leading to products and services that are not only advanced but also deeply relevant and impactful.
Conclusion
The shift to customer-centric AI represents a significant paradigm change in AI governance. It’s a practical, ethical, and empowering approach that aligns directly with business objectives and customer needs. Focusing on customer well-being allows businesses to more effectively navigate the complexities of AI governance, turning potential regulatory burdens into opportunities for growth and innovation. This customer-first mindset not only drives business success but also fosters a more responsible and participatory AI ecosystem.
Stay tuned for part 5!
Ana Chubinidze is the founder/CEO of AdalanAI, building a novel approach to AI Governance.
email: ana.chubinidze@adalanai.com