Jenevieve King is a Sales Director at Tonkean and a member of the Forbes Business Council. This article originally appeared on Forbes. To see the original version, click here.
AI—and specifically generative AI—has proven to be the most breathlessly hyped technology ever to hit the procurement function. When it burst onto the scene, it was trumpeted less as a technology and more as something like magic. Well, the hype hasn’t died down. Through my work at Tonkean, which builds process orchestration tools for internal service teams like procurement and which puts me in touch with CPOs and heads of procurement every day, I recently spoke with leaders who report they’ve been fielding mandates from the C-suite to invest in certain new procurement tools simply because they include “AI” in their name.
Generative AI’s potential is meaningful, of course. Deployed strategically, it can help repurpose procurement teams from transactional silos to strategic business partners, engaged by employees early on in buying cycles and valued by company leadership for the unique skills and perspectives only procurement teams can bring to bear.
But heralding AI as salvific unto itself almost guaranteed procurement wouldn’t be able to harness the technology effectively, at least not right away. So, I believe a correction is due. Based on my experience helping to build Tonkean and the many different conversations I've had with procurement leaders about what they need, here's the truth about AI-powered tools and what we should demand from them.
These technologies are not meant to be magical substitutes for your people or even your existing technology investments—least of all the ERP (enterprise resource planning) and P2P (procure-to-pay) platforms on which procurement depends. Rather, their true promise resides in their ability to empower organizations to get more out of those existing investments—to leverage them more seamlessly and effectively in concert with one another.
The key is implementing AI at the process level via process orchestration, where your organization coordinates automated business processes across teams and existing, integrated systems. In my view, this is the essential infrastructure for getting real, at-scale business value out of innovative technology, AI included. (Think of process orchestration as your organization’s piping for better technology use: for automating tasks, collecting better data and, eventually, leveraging AI.)
I’ve seen that organizations that embrace such a tempered expectation of AI—and utilize orchestration as a delivery mechanism for it—can produce incredible results: cutting cycle times in half, facilitating a nearly 100% internal process adoption, growing proactive procurement engagement and aiding in more strategic respect for procurement as a business partner in the organization.
A common challenge among internal service teams in process design is compensating for the fragmentation of systems across organizations. Likewise, this is an issue in getting business value out of AI at scale.
In most organizations, disparate platforms like ERP systems, Supplier Relationship Management (SRM) tools and Contract Management systems (CMS) operate in silos. Such fragmentation inculcates inefficiency, hinders performance and creates damaging employee experiences—the types of experiences we’ve all seen in our day-to-day: employees not knowing where or how to kick off even simple intake requests, employees having to log into complicated ERP systems that weren’t designed for them, procurement having to manually triage half a dozen different intake channels, employees not knowing where to go for help, procurement having to manually pester managers for follow-ups, nobody knowing the status of anything, etc.
You need, in effect, better piping through which data and work can be effortlessly passed, collaboration more seamlessly facilitated and innovative capabilities more intelligently surfaced—and that’s where process orchestration comes into play.
The best and most enterprise-grade process orchestration technology will:
• Seamlessly wrap around and accommodate your organization’s existing databases, policies, people and systems.
• Create processes that meet every individual employee in accordance with their differing needs, contexts and technological preferences, wherever they already are. (The days of relying on employee knowledge or willingness to comply with your policies and strategies to improve results are over.)
• Integrate your organization’s many different teams and systems—including ERP and P2P platforms and all the various messaging apps and tools employees like spending time in—such that processes can be more seamlessly weaved in and out of them, data passed automatically back and forth and innovative, powerful technologies, such as AI in its various forms, can be surfaced for employees most strategically.
Introducing AI into an organization is not just about giving employees access to the technology; it's about making that technology accessible to employees when they need it most.
What does that look like? It looks like identifying those areas where there has traditionally been friction, confusion or difficulty, and leveraging AI to remove those barriers.
There exist a few internal AIs on the market today that enable you to do as much—that empower process designers to extend to employees different intelligent functionalities throughout process lifecycles. The best will consist of a few key components:
• An "AI Front Door": AI-powered "front doors" can field plain-language inquiries over email, Microsoft Teams, Slack and/or custom portals. They can answer common questions, autonomously resolve simple requests, route users to the proper form sequences for more complex items and deflect out-of-policy requests. Think of it as an AI-powered starting point for employees to use when kicking off internal requests that they can “open” from anywhere.
• AI-Enhanced Forms: This is another in-workflow form of AI that should be surfaced for employees when appropriate. Think of AI-enhanced forms as personalized form sequences that’ll take user roles and situational signals into account to radically simplify processes like intake, pre-populating fields with data from connected systems across the enterprise tech stack and eliminating steps with dynamic conditional logic.
• In-Line AI Q&A: At any given point in a process, stakeholders might have questions. They should be able to ask an AI chatbot for answers directly within form sequences when those questions arise.
These are all just starting points, but processes that provide access to such AI capabilities can quickly lead to huge results. Eliminating the need for context-switching and change management will delight employees and boost process adoption, which will have crucial downstream impacts on compliance, performance and efficiency. Increased efficiency and improved performance—resolving internal requests faster and more effectively with in-workflow AI and cross-system orchestration—translates into more consistent business value.
By embracing orchestration, organizations can not only achieve greater operational efficiency but also create resilient, adaptable workflows that can evolve alongside market demands.
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