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Artificial intelligence (AI) is revolutionising retail, impacting everything from customer service to supply chain management. Yet, as outlined in our recent IADS Exclusive titled "AI in retail: why culture, values, and strategic goals matter more than tech," successful AI adoption involves more than simply implementing new tools. It requires deep alignment with an organisation's broader mission, culture, and values. This exclusive further addresses one of the most critical challenges in AI deployment—the "black box" problem, which refers to the challenge of interpreting or explaining how complex AI models arrive at their decisions. This piece explores how retail leaders can ensure transparency, accountability, and ethical use. Retailers can fully harness AI's potential by focusing on governance, explainability, and innovation while avoiding the risks of opaque decision-making systems. A lack of clarity can impact both customers and employees, undermining trust and creating potential issues with compliance and fairness. Our focus here is on bridging AI's capabilities with clear, human-centred governance by prioritising transparency and informed oversight to channel AI’s potential for people-first innovation.

Beyond the “black box”: accountability, explainability, and transparency

Cracking open the black box 

AI’s promise lies in its ability to make decisions faster and more efficiently than humans. However, many AI systems operate in ways that even their developers cannot fully explain, creating what is known as the "black box" problem. AI algorithms work by analysing vast amounts of data through multiple layers of complex calculations, where each layer transforms the data in ways that are difficult to track. Although developers set the initial parameters, the system's learning process often results in decision paths that are nearly impossible to map or interpret in clear, human-understandable terms. This issue becomes especially risky in retail, where decisions like product recommendations, dynamic pricing, or hiring must be accurate and fair. Unlike industries where AI operates behind the scenes, retail relies on customer- and employee-facing decisions that are immediately visible, impacting trust, satisfaction, and loyalty among both groups. As a result, explainability and fairness in AI outcomes are fundamental concerns, they are vital to maintaining competitive advantage and retention.

Retail leaders must prioritise transparency at every stage of AI development and implementation to overcome this. Documenting data sources, algorithmic logic, and decision-making processes allows businesses to provide clear explanations when needed.1 Unlike in traditional systems, where a clear set of rules may guide a process, AI often uses complex, data-driven models that can be harder to interpret. This opacity raises concerns not only for internal governance but also for customer trust and regulatory compliance.

Retailers must ensure their AI systems are explainable to stakeholders at all levels, from customers and employees to regulators and internal governance teams. By documenting and understanding each decision made by AI systems, companies can avoid the risks of operating in the dark.

Human oversight in AI 

As discussed in "AI in retail: why culture, values, and strategic goals matter more than tech," AI is not a stand-alone solution. Its success hinges on alignment with human oversight and strategic goals. AI-driven systems require ongoing human accountability to ensure they function as intended.

Leaders in retail need to establish clear governance structures for AI deployment, designating dedicated teams to oversee AI systems and address potential issues, safeguarding the interests of both employees and customers2. This was seen in Tesco's pilot program for AI-driven dynamic pricing, where IT teams and department heads collaborated closely to integrate AI without compromising existing business processes. Such coordinated efforts are critical for ensuring that AI-driven decisions align with operational goals and ethical considerations.

Keeping in mind that AI cannot operate effectively without human oversight, retail leaders should set up dedicated governance teams to monitor decisions made with the use of AI, ensuring they are both accurate and ethical.

Building trust through transparency 

Retailers can no longer rely on opaque AI systems, especially as customers, employees and regulators demand greater transparency. In today's marketplace, trust is currency and ensuring that AI tools operate transparently is vital to maintaining it. Regular audits and assessments, such as Data Protection Impact Assessments (DPIAs) and conformity assessments, can ensure that AI systems meet legal requirements and uphold responsible practices throughout their lifecycle.

Marks & Spencer, for instance, conducts ongoing assessments of its AI systems to ensure they align with both customer expectations and ethical standards. These practices help maintain transparency and foster trust across stakeholders.

Regular, transparent assessments of AI systems, paired with continuous monitoring, ensure that AI tools remain aligned with business goals, legal standards, and customer expectations.

Positioning AI as a creative partner in personalisation and innovation

While AI has traditionally been associated with operational efficiency, its potential as a creative and inclusive tool is equally significant. AI agents have revolutionised customer interactions, offering personalised product recommendations and real-time customer support through chatbots and virtual assistants3. Retailers have the opportunity to use AI not just to improve processes but to drive innovation in areas like product design and customer engagement, fostering a more inclusive and sustainable future for retail. For example, some AI-powered digital labs are demonstrating innovative uses of AI creatively to generate custom visuals and personalised content, offering valuable strategies to amplify brand identity and foster impactful customer engagement. Additionally, AI platforms in custom jewellery create unique pieces tailored to individual specifications, blending luxury with personalisation on a scalable level. There is also untapped potential in applying AI to refine employee experiences, aligning training and support with personal strengths and brand values.

AI for inclusive fashion design 

Fashion has historically struggled to cater to all body types and physical needs, but AI offers a pathway to change that. By analysing consumer data such as body measurements, feedback, and preferences, AI can help create clothing with a more inclusive fit. In the bra industry, for example, AI-driven platforms are transforming design by offering custom-made options tailored to each individual's unique measurements, promising a "perfect fit" that addresses both comfort and support. This technology not only enhances comfort but also addresses long-standing challenges in fit, design, and accessibility. As previously mentioned, parallel advancements in AI-driven customisation tools for jewellery mirror this trend, allowing customers to design pieces that reflect their personal style and requirements. Moreover, AI empowers designers to balance aesthetics with accessibility, supporting the creation of inclusive pieces that retain quality and appeal. This approach can be transformative, ensuring that new products meet functional needs and offer greater comfort and accessibility.

AI as a catalyst for sustainability 

Sustainability is an area where AI can make a profound impact. Beyond optimising supply chains, AI can help discover new eco-friendly materials, minimise waste, and predict customer demand more accurately to prevent overproduction. IKEA, for instance, uses AI to track real-time customer preferences, allowing it to fine-tune inventory and reduce excess stock, thereby cutting waste. Additionally, some digital content labs employ sustainable practices by reducing waste in production, and AI-powered augmented reality (AR) shopping solutions help consumers make more precise purchase decisions through virtual try-ons, which decreases returns and supports more sustainable consumption.4

Moreover, AI can simulate the environmental impact of materials and operational decisions, guiding retailers toward more sustainable practices. By integrating sustainability into AI-driven innovation, retailers can meet both customer demands and environmental goals, positioning themselves as leaders in responsible technology use. Overall, AI remains a powerful tool for driving sustainability in retail, from optimising supply chains to minimising waste and promoting eco-friendly choices.

The future of retail spaces: creating the "third place” 

AI can help retailers move beyond traditional shopping experiences by designing spaces that function as "third places"—spaces where customers can shop, relax, and engage with their community. AI tools that analyse foot traffic and customer behaviour enable retailers to create environments that cater to families, young professionals, and other demographics. For example, Nordstrom uses AI to enhance customer service and design spaces that foster interaction and loyalty. Retailers can use similar insights to create experiences that go beyond transactions and resonate emotionally with customers.

Increasingly, retailers are integrating extended reality (XR) technologies—comprising augmented reality (AR), virtual reality (VR), and mixed reality (MR)—to transform in-store experiences further. Each of these technologies provides unique enhancements: augmented reality overlays digital elements onto the real world, virtual reality immerses customers in fully digital environments, and mixed reality combines the two, allowing for real-time interaction between physical and virtual elements. With these tools, customers can try on products virtually, explore gamified store layouts, or engage with product details in 3D, adding new layers of interaction that make shopping both dynamic and memorable.

Moreover, gamification strategies supported by AI and XR deepen these connections by transforming shopping into an interactive journey. AI-driven rewards, achievements, and challenges motivate customers to engage more fully, creating a dynamic and memorable in-store experience. This gamified approach not only draws customers back but also shifts the retail experience from a routine task to an enjoyable, impactful activity. Together, these innovations create an atmosphere where shopping is functional, immersive, and personally engaging.

Multigenerational workforce: Millennials, Gen Z, and Gen Alpha bridging the AI gap

The rise of AI in retail is not happening in isolation. It is unfolding in an era where the workforce is becoming more multigenerational than ever before, spanning Boomers, Gen X, Millennials, Gen Z, and, in the coming years, Gen Alpha. The younger generations—Millennials, Gen Z, and soon Gen Alpha—are not only shaping consumer trends but are also at the forefront of AI adoption in the workforce. Their digital fluency allows them to bridge the gap between traditional retail practices and AI-driven innovations.

Millennials and Gen Z: leading the charge

Millennials and Gen Z employees bring a unique set of skills to the table, particularly in understanding how AI can enhance customer and employee experiences.5 These generations are digital natives, comfortable with using AI tools to create more personalised and efficient shopping experiences, ranging from tailored customer interactions to streamlined employee training and support systems. Their affinity for innovation makes them ideal candidates for roles that involve AI governance, strategy, and implementation. In many organisations, these generations are the bridge between leadership’s vision and the practical application of AI solutions on the ground. In some organisations, interns play a crucial role in advancing AI initiatives by experimenting with AI tools innovatively. This open approach allows retailers to test and refine straightforward, adaptable solutions, often achieving quick wins and practical insights into AI’s application in retail environments.

Gen Alpha: the future of AI in retail

Looking ahead, Gen Alpha—those born after 2010—will be the most AI-native generation yet. As they enter the workforce in the coming years, their expectations for seamless, tech-driven environments will push retailers even further toward AI adoption. Retailers must prepare now by fostering a culture of continuous learning and adaptability.  Unlike previous generations, Gen Alpha is growing up in an environment where AI, XR, and interactive digital interfaces are the norm. This digital immersion will likely lead them to prioritise seamless, personalised, and ethically aligned AI applications as they enter professional roles.

Gen Alpha’s digital-native perspective positions them to lead retail innovations, especially in personalisation, transparency, and sustainability. As this generation enters retail roles, their advanced tech skills and commitment to socially conscious, transparent practices will further push the industry toward robust AI adoption and integration. Preparing for this workforce shift involves fostering a culture of continuous learning, with Gen Z and Millennials guiding Gen Alpha as they begin taking on leadership roles.

Governance done right: legal and ethical compliance

AI in retail must adhere not only to business goals but also to legal and ethical frameworks. Retailers need to recognise that while AI can enhance operations, it must operate within the confines of privacy laws, consumer protection standards, and intellectual property rights. Effective AI governance requires a solid grasp of multiple disciplines, including AI, data science, law, risk management, and ethical standards. Given the rapid evolution of this field, governance frameworks and policies developed today will likely require updates and adaptations in the near future. Pragmatism is essential, as well as understanding that not using AI can pose greater risks than using it responsibly.

Staying ahead of the regulatory curve

As AI evolves faster than the law, retailers must be proactive in understanding and complying with existing legal frameworks. For instance, AI systems used for hiring or pricing must adhere to anti-discrimination laws and consumer protection standards. The U.S. Federal Trade Commission (FTC) has made it clear that AI tools cannot violate existing regulations, and failure to comply can result in significant penalties. Implementing governance frameworks like the EU AI Act or ISO 42001 can provide structure, but governance professionals must remain adaptable to navigate the changing legal landscape effectively.

Successful AI governance is not limited to enforcing rules but involves fostering a culture of ethical responsibility. This requires a mindset that balances risk with opportunity. Companies must work closely with legal teams to ensure that AI systems do not inadvertently breach regulations. This requires continuous legal oversight, particularly as AI evolves and new use cases emerge. Being proportionate in AI governance, focusing on high-risk areas and scalable oversight, is critical to effectively balancing AI’s benefits against potential risks. Retailers need to ensure that AI systems comply with existing laws and regulations, working closely with legal departments to mitigate potential risks, protecting both customer data and employee rights in the process.6

Navigating intellectual property challenges

As AI supports the creation of new designs, marketing strategies, and other innovations, intellectual property (IP) issues will become increasingly important. For example, recent rulings on AI-generated content raise questions about ownership rights. Retailers need clear policies regarding IP ownership for AI-driven innovations, ensuring they are legally protected while avoiding conflicts with third-party rights. This challenge requires AI governance professionals to understand not only the technology but also the intersections of IP law, ethical standards, and commercial pressures. A perceptive approach to AI governance (building a shared language around AI and data science) facilitates mutual understanding and credibility, strengthening governance practices across the organisation.

Continuous governance for continuous innovation

AI governance is not a one-time effort but a continuous process that requires regular updates and audits, as well as alignment with organisational values. This is particularly important when addressing dimensions such as bias, data privacy, and fairness. Retailers must adopt governance frameworks like ISO 31000:2018 Risk Management Guidelines or the NIST AI Risk Management Framework to ensure AI systems comply with legal and ethical standards. Regular audits will help navigate the complexities of AI and maintain responsible use.7

As retailers face the complexities of AI deployment, they must prioritise thoughtful planning, structured governance, and continuous adaptation to ensure successful outcomes. Here are the key practical steps for integrating AI, which serve as essential takeaways:

• Conduct a formal needs assessment: Start by understanding where AI can add the most value, ensuring alignment with both operational challenges and broader business objectives.
• Align AI with organisational goals: AI must not operate in isolation. Leadership should set a clear vision and develop a roadmap with prioritised use cases that target strategic impact.
• Develop proof of concept and pilot programmes: Test AI through controlled pilots, refine based on real-world data, and involve key stakeholders across departments to ensure AI integrates smoothly with existing systems.
• Iterate and improve before full-scale deployment: Do not rush into full implementation. Learn from pilot results, iterate, and document decisions to create a responsible and transparent AI framework.
• Plan thoroughly for full-scale deployment: Ensure detailed planning, resource allocation, and ongoing performance monitoring to mitigate risks and avoid AI becoming a “black box.”

Beyond technical steps, continuous adaptation and monitoring are necessary to keep AI systems aligned with business objectives and ethical guidelines. By continuously evaluating and refining AI systems, retailers can unlock AI’s potential as a strategic asset that drives innovation, inclusivity, and sustainability. At its best, AI governance becomes a key enabler of long-term value. Retailers who embrace governance frameworks and standards, coupled with transparent, accountable practices, will be well-positioned to succeed and thrive in a future shaped by AI, ultimately benefiting both employees and customers with a responsible, human-centred approach.

The "black box" challenge highlights the dual impact of AI in retail: AI systems shape customer experiences in areas like personalised shopping and dynamic pricing, and they influence employee-related decisions, such as hiring and resource allocation. Yet, these systems must themselves be shaped and guided by human oversight. This interdependence calls for transparency and accountability, ensuring that AI-driven decisions are effective and aligned with the core values and needs of employees and customers. AI operates as a "socio-technical system"—meaning it blends both technical processes and human influence. This requires a strong foundation of ethical, human-centred governance where AI complements company culture by prioritising people and data integrity over purely algorithmic outcomes.

AI is best used as a tool to support, rather than replace, human judgment, helping decision-makers make informed choices through simulated insights. Such a foundation ensures that AI complements organisational culture, expanding possibilities while adhering to human-centred values. A purpose-driven approach to AI integration paves the way for sustainable growth and innovation, allowing technology to amplify human values and propel the retail industry toward a future rich with meaning and resilience.

Credits: IADS (Maya Sankoh)