Find the original article published by AiThority here.
Lori Schafer, CEO of Digital Wave Technology, chats about the impact of AI on the retail industry, the pivotal role of Master Data Management (MDM), and shares valuable tips and strategies for successful digital transformation in this catch-up
Hi Lori, tell us about the key lessons in your Tech leadership role at Digital Wave.
Invest in top technical talent—it’s essential for success. We build innovative scalable, secure cloud-native systems, natively integrating AI and Generative AI. To differentiate, we hire leading talent in architecture, technology, and data science alongside strong executive leadership. Our CIO ensures delivery of secure, high-quality solutions, while our CTO and Chief Data Science Officer focus on optimal architecture and effective use of data science for critical business challenges.
Align technology with customer and industry goals, ensuring investments are strategic, scalable, and drive growth. Prioritize top talent in product marketing and management.
Empower teams with clear purpose and autonomy to foster creativity, ownership, and accountability. A collaborative, agile environment accelerates innovation and project timelines.
How do you see AI transforming the retail industry, particularly in customer engagement and supply chain management?
Customer Engagement to drive increased sales and profitability.
Product Copy & Attributes at Scale: AI generates personalized, optimized product descriptions and enriches attributes for better search and discovery.
Recommendations: AI tailors product suggestions based on browsing and purchase history, increasing satisfaction and conversions.
Chatbots & Virtual Assistants: AI-driven chatbots offer 24/7 support, improving customer service while cutting costs.
Loyalty Programs: AI predicts buying behavior to create more personalized and effective loyalty programs.
AR & Virtual Try-ons: AI enables customers to preview products in real-time before purchase, boosting confidence and reducing returns.
Supply Chain Management to improve efficiency, accuracy, and responsiveness:k[]\
Demand Forecasting: AI analyzes data to improve inventory optimization, reducing stock issues and boosting cost-efficiency.
Warehouse Automation: AI and robotics streamline operations, lowering costs and accelerating fulfillment.
Real-Time Inventory: AI tracks stock levels across channels, improving accuracy and efficiency.
Supply Chain Resilience: AI identifies potential disruptions and suggests alternatives, enhancing continuity and responsiveness.
What are the biggest hurdles you see for brands adopting AI, and how does Digital Wave’s solution help overcome them?
The biggest hurdles companies face when adopting AI and Generative AI include data quality and availability, a shortage of specialized skills like AI engineering and data science, the need for costly upgrades to legacy systems, uncertainty around ROI and costs, ethical and regulatory concerns (such as bias, privacy, and compliance), security and privacy risks, and cultural resistance.
Digital Wave Technology addresses these challenges with a modern, unified data platform, deep expertise in data science software, and personalized customer service to apply AI to real-world business problems. Future-ready, highly secure software is crucial for improving data quality and replacing outdated systems. Equally important is a team that bridges the talent gap, educates teams, and is skilled in security, ethics, regulatory requirements, business processes, and change management.
Talk about how AI is being used to improve advertising campaigns. What benefits does it offer to retailers?
AI-driven advertising enables rapid, accurate, and high-quality ad generation, including both ad text, taglines, and associated lifestyle images. For example, a consumer-packaged goods (CPG) company can use AI to send personalized ads to retail partners, tailored to specific customer demographics across global regions, while supporting multiple languages and automating lifestyle images and marketing content.
The benefits are significant, reducing costs associated with traditional ad creation methods like photo shoots, models, and stylists, while also speeding up the ad creation process. This allows marketing assets to be quickly shared across various channels—digital, social media, email, direct mail, and streaming platforms—for cohesive campaigns. By decreasing the time and expense involved, companies can run more ads than they currently do, significantly boosting content production. Additionally, AI-generated ads can be customized to match regional, seasonal, holiday, and event-specific needs, enhancing relevance and engagement. Companies can produce more ads independently, fostering AI-driven brainstorming sessions, diverse marketing strategies, and tailored content creation.
What role does Master Data Management play in ensuring accurate, consistent data across brands, and how does your ONE™ Platform integrate this?
Master Data Management (MDM) forms the foundation of Digital Wave Technology’s ONE™ Platform, providing a single, trusted source of truth by unifying product, customer, and supplier data across systems and channels. Historically, MDM was often confined to IT departments and not fully integrated with other essential software solutions. However, a modern MDM platform can handle big data, ensuring a single version of truth across the organization. This empowers companies to maintain data integrity while leveraging AI to drive growth and innovation. MDM centralizes data governance and accuracy, ensuring consistency across channels and brands. It serves as the critical foundation for all Digital Wave’s software solutions, as well as others within the enterprise. Clean and accurate data is vital for AI, Generative AI, and all types of data-driven decision-making. With full integration across business process-oriented software, this platform ensures that all critical decisions are based on the same reliable, accurate data.
Having worked globally, how do AI adoption strategies differ across regions like North America, Europe, and APAC?
AI adoption strategies differ across North America, Europe, and APAC due to varying regulatory environments, market dynamics, and cultural attitudes. While more established AI technologies like machine learning, demand forecasting and numerical mathematical models have been used similarly in these regions, Generative AI adoption is seeing divergent approaches.
North America: Prioritizes speed and innovation, focusing on gaining competitive advantage. AI adoption is driven by a strong startup ecosystem and less restrictive regulations, enabling faster deployment across industries like healthcare, finance, and retail.
Europe: AI strategies are shaped by stringent regulations, such as GDPR, leading to a more cautious approach. The focus is on responsible AI, fairness, and transparency, particularly in public sector applications, resulting in slower but ethically grounded adoption.
APAC: AI adoption varies widely. In countries like China, strong government backing, and large-scale investments drive rapid adoption for economic growth and surveillance. In other countries, adoption may be slower due to infrastructure or economic constraints, but the focus is on AI for manufacturing, smart cities, and telecommunications, with fewer regulatory hurdles compared to Europe.
Share five tips for companies working on their digital transformation strategy today.
Based on extensive experience in digital transformations, I recommend the following:
Start with a Clear Vision and Executive Support: Align digital initiatives with business goals to ensure technology investments drive long-term objectives. Strong C-level sponsorship across the company is essential, as successful digital transformation requires significant change management and a comprehensive review of processes, systems, and infrastructure.
Start Small with Clear ROI Objectives: Don’t attempt to tackle everything at once. Focus on manageable, measurable steps. Start with areas that have clear, tangible ROI that can be easily tracked to build confidence and momentum within the organization.
Foster a Digital-First Culture: Encourage employees to embrace digital tools and innovation. A company-wide culture that supports digital transformation will lead to smoother transitions and more successful outcomes.
Invest in Scalable Technology, a Unified Data Model, and Future-Ready Solutions: Choose flexible, scalable technologies that can grow with your business and adapt to future demands. A unified data model will ensure consistency and adaptability.
Measure and Iterate: Continuously track key performance metrics and refine strategies based on data-driven insights. This iterative approach will enable your organization to optimize its digital transformation efforts over time.
Thank you, Lori, for sharing your insights with us.