Embedding intelligence at the coalface of work

Angela Colantuono, president and managing director of SAP Australia and New Zealand (ANZ), highlights that creating value is the defining business issue today. Six months ago, the focus was on how many hours AI could save, but now the question is about the value AI can create. Colantuono emphasizes that AI must be strategically embedded across end-to-end business processes rather than being treated as a standalone application. She notes that the gap between organizations that have successfully integrated AI and those still in pilot phases is widening, and leaders are increasingly aware of this disparity. Data quality and process simplification remain significant barriers to improving business performance. Colantuono explains that organizations struggle with accessing accurate data, which impacts AI and other business operations. Many companies have accumulated complex technology environments over time, making it difficult to connect information across various departments like finance, human resources, procurement, and operations. Instead of adding more technology layers, businesses are simplifying their processes before embedding AI. Simplifying processes enables technology to deliver better results, enhancing an organization’s capability to achieve meaningful outcomes. The shift in technology investment is also changing. Organizations are moving away from the traditional 80/20 technology burden, where most effort and funding are spent maintaining fragmented systems, toward improving business outcomes. Colantuono points out that a best-of-breed approach in technology decisions has led to significant integration costs. Simplifying technology environments creates a stronger foundation for trusted data, allowing AI to integrate seamlessly into existing workflows rather than becoming a disconnected tool. The transition from experimentation to embedded AI is already visible in customer-facing organizations. Freedom, a furniture retailer, expanded its online product range from around 15,000 to over 70,000 products to offer an 'endless aisle' experience. This expansion created a challenge in identifying the right product for customers. Freedom integrated AI-driven search and personalization directly into the customer journey, analyzing customer intent through various interactions. The results showed a measurable shift in customer behavior, including increased search bar usage and higher conversion rates. Federico Jalil, digital product manager at Freedom, stresses the importance of reliable data for effective AI. He notes that poor-quality data leads to poor outcomes, regardless of AI model sophistication. Success depends on ensuring data is accurate, properly indexed, and structured appropriately. Jalil also highlights that data volume alone is not sufficient; the right data must be properly managed to enable accurate and meaningful outputs from large language models (LLMs). AI is increasingly becoming a boardroom issue rather than an IT initiative. Colantuono says business leaders are asking how AI can create competitive advantage while maintaining trust, ethics, compliance, and security. She emphasizes the need for balanced investment decisions, risk frameworks, and governance structures to keep pace with AI advancements. SAP approaches AI through three principles: responsibility, reliability, and relevance. These principles align with discussions with chief executives and chief information officers, who are shifting focus from rapid AI deployment to responsible integration within core business operations. Government agencies are also facing similar challenges. Organizations are seeking productivity improvements that enhance frontline service delivery while maintaining governance and accountability. The evolution of AI capabilities is leading to a consensus that lasting value comes from integrating AI into core business activities rather than treating it as a separate project. Jalil suggests starting with a genuine business problem, identifying a clear challenge, and focusing on opportunities that can be automated and scaled. Organizations across government, retail, and enterprise are confronting questions about value, service delivery, and responsible AI adoption while working with limited resources. The next frontier involves redesigning work to enable organizations to combine trusted data, simplified processes, and governed AI to create new levels of speed, agility, and value. Organizations that achieve this will build the foundations of the autonomous enterprise, where trusted data, intelligent applications, and AI agents work together to help organizations anticipate, decide, and act with confidence under human oversight.