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Every IADS event is designed to allow the Association members to learn from each other, and the General Assembly is no exception. This is why the 2024 edition took place in Türkiye. It was the perfect opportunity for one of the IADS’ newest members, Boyner Grup, to showcase the progress made since the COVID-19 pandemic and how it radically reinvented itself to adapt to the new market conditions.

The text below is a synthesis of a presentation by Cihan Yildiz, Boyner's CTO, describing the company’s journey into this field. Today, Boyner Grup uses AI in various use cases after taking the necessary steps to ensure the company structure was adapted.

It has been stripped of confidential information, including the Q&A section, which IADS members can find in the meeting recap related to the 2024 General Assembly on the IADS Website

Introduction: how AI is a game-changer for all industries

Artificial Intelligence (AI) has traditionally been defined as replicating human intelligence using machine algorithms. Over time, research and technological advancements in machine learning and deep learning have substantially expanded the scope of AI. These developments enabled computers to recognise images, understand speech, and perform tasks like facial recognition, which once seemed futuristic. The arrival of Generative AI, propelled into the mainstream by solutions such as ChatGPT, represents a particularly significant milestone. Some commentators describe the launch of ChatGPT as an “iPhone moment,” meaning it heralds a new phase of AI maturity where advanced language capabilities become available to a broad audience.

Yildiz attributes this accelerated growth in AI partly to the near ubiquity of smartphones, which now serve as vast data generators. This surge in data, coupled with more sophisticated algorithms, has opened the door to various innovative solutions that were almost unimaginable a few years ago. Generative AI exemplifies these advancements by using large datasets and specialised learning techniques to produce new content, drive complex analysis, and engage in nuanced conversations in efficient and highly adaptable ways. It is this aspect of AI—its agility and creativity—that many experts believe will shape the next wave of business and consumer applications.

Business perspectives

Boyner regards Artificial Intelligence (AI) as a powerful catalyst for transformation across numerous industries, especially retail, where data-driven decision-making can dramatically improve efficiency and spark innovation. According to Yildiz, who has led several AI initiatives at Boyner, businesses should adopt a systematic approach to AI implementation to leverage its full potential. During his presentation, he underscored the importance of understanding AI’s evolving capabilities, its immediate applications, and its expected long-term impact on operations and customer engagement. His perspective highlights that AI can remarkably quickly reshape an organisation’s strategies, processes, and culture when introduced through carefully chosen projects.

Current forecasts suggest that Generative AI will attract around three trillion US dollars in investment between 2023 and 2027 globally, indicating the extent to which companies believe in its transformative capacity. Nearly half of all technology companies are expected to embed Generative AI into their offerings, a sign that AI is becoming not just a technical addition but a foundational element of future products and services. Enterprises typically move through three distinct phases when they adopt AI: first comes the learning phase, during which teams become familiar with AI tools and concepts; second is the testing phase, which involves running small pilots to validate new ideas; and finally, the investing phase, where proven AI models are scaled to the enterprise level.

Even though only a fraction of AI use cases today explicitly involve Generative AI, results show that those use cases alone can drive notable increases in efficiency and customer satisfaction. Studies indicate a nearly thirty per cent improvement in operational efficiency, matched by a thirty per cent uplift in customer experience measures. Projections for the future amplify this trend. By 2028, a third of enterprise software is expected to include agentic AI features, compared to a negligible portion in 2024. Similar shifts are anticipated in digital storefronts, where a significant share of interactions could be managed by AI tools rather than human agents, and in daily work decisions, an increasing number of which will be delegated to AI systems that can analyse data and deliver real-time recommendations.

How Boyner crafted its vision and roadmap

In its approach to AI, Boyner has closely followed Gartner’s strategic guidelines, focusing on high-impact opportunities, including price promotion strategies, optimisation of markdown processes, and improvements in in-store product availability. The company also prioritises personalisation, social media monitoring, and demand forecasting. Leveraging these focus areas, Boyner articulated five central pillars that define its AI roadmap: personalisation, data-driven insights, efficiency, innovation and creativity, and continuous improvements.

The company’s priority is personalisation, which aligns with the ongoing Boyner Now initiative and other efforts to tailor experiences for individual customers. Boyner also intends to develop a platform that generates data-driven insights, allowing it to consolidate all relevant data and transform it into accessible, actionable information.

Furthermore, Boyner remains committed to operational efficiency, building upon Gartner’s assessment that AI could help address nearly a quarter of retail's overall costs. Alongside these goals, the organisation embraces creativity and innovation as essential catalysts for new AI-driven solutions, ensuring that experimentation is encouraged at all levels.

The final pillar is the cultivation of a Kaizen-style system of continuous improvement, a principle that guides Boyner in regularly assessing and refining its AI applications to keep pace with rapidly evolving technologies and market demands.

Using partnerships to become AI-ready

To put these ideas into practice, Boyner devised a strategy it calls “AI readiness,” designed to ensure that every relevant stakeholder, from data scientists to C-level executives, understands AI's value proposition and is equipped to manage its risks and benefits. This process begins by defining a clear vision and identifying what AI can accomplish for the organisation. Boyner also articulates key performance indicators that guide measuring success, highlighting aspects such as revenue impact, customer satisfaction, and risk mitigation.

Collaborations with key partners like Gartner and Microsoft form another critical dimension of this readiness strategy. While Boyner maintains in-house development capabilities, it also relies on external expertise to stay aligned with cutting-edge advancements. Aligning AI with Boyner’s broader organisational strategy is a critical first step, ensuring that all departments recognise how AI projects serve shared corporate objectives. Boyner invests in awareness programs, teaching employees about Generative AI and providing them with tools built on Microsoft’s OpenAI services. The company encourages grassroots innovation by offering workshops and safe sandbox environments and ensures that the best ideas are brought to light. Following these initial learning and testing stages, Boyner evaluates all AI use cases and solutions based on ethical principles and data privacy standards and ultimately presents a tactical roadmap backed by executive sponsorship.

Current AI use cases

Boyner’s commitment to AI is exemplified by the fact that every new or experimental AI solution it develops moves swiftly into production, where it can deliver real value.

One such example is the automation of order and product sorting, allowing the logistics team to handle items more efficiently across the supply chain. In addition, Boyner has introduced an AI-based product import tool that extracts attributes from product images and retrieves any missing details through web scraping, significantly reducing the time and manual effort required to add items to its e-commerce catalogue.

Personalisation efforts take shape through micro-segmentation, allowing Boyner to offer tailored promotions, such as raincoat discounts only in regions experiencing adverse weather conditions. The marketing team has also implemented sophisticated in-house Marketing Mix Models to allocate budgets strategically, incorporating profitability targets and, in the future, data from CRM systems and omnichannel sources.

Another key innovation involves a Semantic AI Assistant that improves the e-commerce platform’s user experience through content summarisation and intelligent responses to customer inquiries. Moreover, Call Center voice-to-text transcription has been introduced to capture and analyse customer conversations, further enhancing service quality.

While these AI solutions bolster operational efficiency and customer satisfaction, Boyner has also championed Generative AI-driven chatbots. These include tools that assist customers in choosing gifts, manage stock levels in real time, and even handle internal human resources inquiries, as evidenced by the success of the People Chat application.

To unify these efforts, Boyner consolidated four disparate data warehouses into a single AI-ready platform, making it easier to draw connections between different data points and support informed, evidence-based decision-making.

Boyner’s journey with AI offers a compelling example of how an organisation can systematically integrate data-driven solutions into its operations and thereby reshape its future. By paying close attention to the learning, testing, and investing cycle, and by forming strategic alliances with prominent technology partners, Boyner has managed to introduce AI solutions that deliver tangible benefits. These benefits range from logistical efficiencies and robust customer experiences to increased creative capacity and a forward-looking corporate culture.

Yildiz concluded that Boyner’s focus on empowering all employees to experiment with AI tools—while maintaining strict safety and privacy protocols—goes a long way toward embedding AI in the company’s DNA. This approach secures buy-in from both leadership and frontline staff. As Generative AI continues to mature, Boyner looks to deepen its expertise, exploring new frontiers in retail automation, customer personalisation, and knowledge management, all while keeping an eye on responsible practices. In doing so, Boyner serves as an illustrative case study for other organisations: the potential of AI to drive meaningful change is substantial, but realising that potential requires consistent engagement, thorough preparation of data, and a measured, adaptable roadmap.

Credits: IADS (Selvane Mohandas du Ménil)