AI will drive the next wave of business process transformation

Back in 2019, while publicizing a book I had written, I blogged about the future of business process best practices and how “new” technologies would mean less work, more automation, and better outcomes. At the time, I noted that technology was changing faster than ever before and that artificial intelligence/machine learning and other emerging technologies would further accelerate business change.

In my book, I explained, “Why many new jobs will be created, some old jobs will become irrelevant—but every job will change at the task level.” What occurred over the next five years was a fundamental evolution of business processes in every industry, creating new opportunities for transformation and reinvention. Consider the following examples:

• Collaboration technologies enabled remote working and learning to become the norm in almost every industry during the pandemic and afterward.
• Healthcare in many of the world’s developed countries has been revolutionized by giving patients access to their own health data and enabling remote consultations.
• Auto manufacturers, never laggards in adopting new technologies, are using automated vision systems to improve defect detection by as much as 90%.

Power of embedded features

In 2024, traditional AI and generative AI features are starting to be embedded into the enterprise applications that manage most business processes, magnifying and multiplying industry transformation and reinvention opportunities. The embedded features make it easier for organizations to adopt AI capabilities, helping them increase productivity, automate even more end-to-end business processes, and reduce the costs of doing business.

One way to put this into context is to explore a business process that, for almost every organization, is the very core of their purchasing activities: sourcing. This process affects almost every part of the organization and always begins with identifying what’s meaningful through the use of data analytics.

Imagine that, as the director responsible for indirect purchases, you’ve been challenged by the executive team to seek further reductions in that spending. Using your procurement application's dashboard, your in-depth analysis indicates an opportunity for major cost savings in a forthcoming purchasing project. Digging further, you find that your organization has just two qualified suppliers.

The AI embedded in the application offers an option to discover new suppliers that meet your criteria for sustainability, technology requirements, competitive prici¬ng, and delivery. Investigating further, you identify six additional potential suppliers and add them to your purchasing project. Now you have to draft the cover page to go with your RFQ.

GenAI embedded in the procurement application presents an AI assist feature, letting you reduce the time and effort you’d normally need to tailor a cover page. GenAI takes into account that new suppliers are unfamiliar with your organization, the purchasing order specifications, and how your organization works. AI assist provides several suggestions for the text of the cover page, letting you quickly select, edit, and publish the RFQ.

In just this one use case on insight-to-sourcing, you can see the powerful impact of traditional AI and generative AI on a key Oracle Modern Best Practice business process. And this is just the beginning.

Steve Cox is chief architect of Oracle Modern Best Practice and the author of several books on the subject.

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