The rise of AI assistants such as ChatGPT have made AI a more visible and prominent tool for everyday users. On a daily basis, millions of people input prompts into chat windows to explore what AI can do.
AI continues to make headlines, sparking heated debates about ethics, sustainability and governance, and organizations are now rushing to adopt policies for AI use.
Currently, the conversation around AI is focused on the interface itself: which chatbot is best, how to write better prompts and how AI can improve the way we work. However, the hype around prompts and chatbots will eventually pass. History shows that the most transformative technologies eventually fall out of our conscious awareness.
The new normal
When we turn on a light switch, we don’t consider the complex processes that enable us to use electricity or the electrical grid and power infrastructure behind it. Similarly, when we buy a product online, we are only concerned with the website and the Checkout button.
Hidden behind that simple transaction are dozens of systems working together to coordinate inventory, payments, warehousing, fulfillment and customer communications. As customers, we only care about how simple the buying experience is, not the underlying technology that makes it happen.
History shows that the most transformative technologies eventually fall out of our conscious awareness.
AI is following a similar path. While the first phase of generative AI focused on helping individuals complete tasks, the next phase will focus on orchestration. Instead of enhancing productivity tools, AI will coordinate activity across people, systems and processes.
Over time, it will become more of a background facilitator. This will represent a fundamental shift in how organizations think about AI. While the first wave of adoption focused on productivity, such as drafting documents or summarizing information, these uses remained largely isolated, individual activities. The real competitive advantage of AI can be realized by shifting from individual productivity gains to organization-wide coordination.
The next phase of AI will center around connecting workflows across departments and business functions. Information will move automatically between systems, enabling routine decisions to be made in real time. Processes that previously required manual coordination will be managed dynamically in response to changing business conditions.
This is where enterprise platforms become increasingly important. Most businesses already have enterprise resource planning (ERP) systems that hold finance, inventory, procurement, staffing and operations information. But as AI becomes embedded in these platforms, information across different parts of the business can begin to connect, helping coordinate what needs to happen next.
Instead of simply recording information, AI-enabled ERP systems will help organizations respond more quickly to what is happening now, in real time.
From prediction to insight
AI integrations across organizations are enabling much more powerful automation. For decades, retailers used predictive analytics to forecast what might happen. Today, AI-driven retail platforms can detect disruptions, make informed decisions and initiate operational actions in real time. These include dynamic pricing adjustments, inventory reallocation, fulfillment rerouting and hyper-personalized customer engagement.
This is particularly significant in the Asia–Pacific region, where retailers operate in a highly fragmented and volatile environment. Supply chains often span local, national and international networks, with rapidly shifting consumer behavior and geopolitical tensions influencing sourcing and logistics.
The next phase of AI will center around connecting workflows across departments and business functions.
But orchestration extends beyond operational workflows. AI is also transforming how organizations capture and apply knowledge. For example, the hospitality industry traditionally generates huge volumes of data, which can actually make it harder to access clear, meaningful insights. Managers often spend more time sorting through inputs than acting on them.
This challenge is further complicated by high staff turnover. When workers leave, they take specialist knowledge with them and new employees typically start with little to no training or knowledge of the systems and processes used by their predecessors.
This is where AI can serve as an ‘institutional brain’, retaining knowledge through staff changes and translating complex performance metrics into simple briefings. Embedded within an organization and working in the background, staff do not need to be trained on multiple tools or spreadsheets; they can simply interact in natural language.
AI becomes more like a team member than an application, capable of instantly answering questions such as “How do I process a refund for this reservation?” or “What dates do we have available for a large conference booking?” without needing to check with other departments or managers.
The rise of ambient AI
This emerging model is often described as ambient AI. Instead of requiring employees to pause work and use a separate tool, AI is embedded in everyday processes. It continuously monitors, analyzes, recommends and coordinates activities in the background.
Much like cloud computing, AI will create the greatest value when it seamlessly integrates how organizations operate. This is all the more critical considering the skilled worker shortage organizations around the world are currently facing.
AI is also transforming how organizations capture and apply knowledge.
A phrase often heard in the technology space is that the most successful technologies eventually become ‘boring’. Once a technology becomes essential infrastructure, the focus is no longer on the technology itself, but on what it actually enables.
Compared to decades ago, no-one is impressed by a smartphone with a camera, nor would they even mention it. Yet we frequently use them to take photos or scan QR codes without thinking about the complex layers behind the technology.
Eventually, employees will no longer think of themselves as using AI. They will simply perform their jobs while AI helps coordinate the work around them. The most successful enterprise AI will be invisible, operating silently in the background.
