You can’t prompt your way out of complexity: Why enterprise AI is turning to process intelligence

As enterprises navigate the complexities of scaling AI initiatives, the agentic AI blueprint for success lies in combining deep process intelligence with powerful cloud platforms, enabling organizations such as Genpact Ltd. to transform finance and operations workflows through reimagined processes and effective partner ecosystems.

That convergence defines the moment the industry finds itself in as a wave of agentic AI announcements proliferates. The technology is maturing quickly; the partner relationships that determine who actually captures value are maturing too, according to Nidhi Srivastava (pictured, right), senior vice president and head of digital and cloud at Genpact.

“The partner ecosystem is now the new village wherein we work with the vision of the client,” Srivastava said. “We’ve been working with business processes for our clients for many, many years. We have a very deep understanding of what the last mile looks like for our clients. When you combine that with the power of a platform like Google Cloud, it becomes a motif for success.”

Srivastava and Pallab Deb (left), managing director of global partner go-to-market practice and product engagement at Google Cloud, spoke with theCUBE’s John Furrier and co-host Alison Kosik at Google Cloud Next, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the agentic AI blueprint for success and why process intelligence is surging as the decisive enterprise advantage. (* Disclosure below.)

Process intelligence and the agentic AI blueprint for enterprise scale

One of the clearest signals of agentic AI’s maturity is where early enterprise momentum is concentrating. Finance transformation — long considered a back-office function — has emerged as a primary beachhead for agentic deployments, driven by its deterministic nature and clear return on investment. Genpact moved early on this signal, launching its agentic AP Suite to automate accounts payable workflows end to end as part of its broader Service-as-Agentic-Solutions portfolio, Srivastava noted.

“I think we are clearly at the point where we should solve the real problems,” Srivastava said. “Playing at the edge and getting used to it and feeling comfortable — we are past that point. Finance transformation has kind of bubbled up to the top.”

The return of process expertise as a first-class discipline echoes a pattern traceable back to the ERP era, according to Deb. AI is bringing functional depth back to the foreground after two decades in which pure technology focus — mobile, data lakes, cloud — dominated enterprise investment, he explained. The engineering gap that separates a polished demo from a production deployment on a mission-critical SAP environment is where that expertise now earns its keep.

“You think you can prompt your way out of complexity? Don’t even try,” Deb said. “The demos are going to show you that you can prompt and get wonderful things [to] happen. Try doing that on top of a fairly custom SAP installation that manages your supply chain, where things are mission-critical. You’re probably going to need hard engineering work. I think that’s the gap between what’s promised versus what it takes to get through the journey.”

Google Cloud’s $750 million investment in its partner ecosystem underlines the strategic weight both companies are placing on the agentic AI blueprint for success. But throwing AI at an unreformed process yields only marginal gains — the prerequisite is reimagining workflows for AI from the ground up, including value stream mapping and building agents that mirror the personas of the people they are designed to support, according to Srivastava.

“It’s super important to reimagine the process for AI, because throwing AI on an old process only gives you marginal improvement,” she said. “That’s also where the business case of AI sometimes suffers, because people are just instrumenting AI into an existing process which was not designed for AI. Spending enough time reimagining the process is critical to the scale when you’re looking for success at scale.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Google Cloud Next:

(* Disclosure: Genpact sponsored this segment of theCUBE. Neither Genpact nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE