4 days ago
AI Agents Make End-To-End Process Integration More Than A Pipe Dream
Is 2025 the year of agentic AI? KPMG thinks so; the advisory firm's AI Pulse Survey for Q4 2024 found that 51% of organizations are exploring the use of AI agents and another 37% are piloting the technology, which comprises intelligent, often autonomous agents that can understand natural language, bridge information gaps, integrate across systems, and even take action.
While near-term targets for automation include administrative duties and call center tasks, what gets people most excited is how agents can integrate into existing applications and end-to-end business processes, because it provides a much clearer path to ROI than early iterations of generative AI (GenAI) technologies.
Given the embedded nature of AI agents in business workflows, it will be important for technologists to gain a deeper understanding of processes across finance, HR, procurement, supply chain, sales and marketing, and other functional areas. CIOs wary of disrupting business with AI pilots that target some of these vital operational areas are getting an assist from software vendors that have been integrating AI agents into their enterprise applications. It's a good place to start testing agentic AI's capabilities.
'Look at your core applications first, because they hold the data and the processes where agents can provide the most value,' says Isaac Sacolick, president and founder of StarCIO, a digital transformation consultancy. 'Ultimately it comes down to where the user is.'
This focus on where 'work gets done' is the key to an organization's ability to shift from capturing incremental productivity gains, where much of the early GenAI experiments have focused, to improving business performance by rethinking and transforming end-to-end processes, says Francesco Brenna, VP & Senior Partner for AI Integration Services with IBM Consulting.
'Many businesses are still far from seeing value at scale from AI implementations,' says Brenna. 'The first generation of AI assistants are good at helping you find the information you need to do your job, but they're not really focused on helping you actually get the job done. This is where agentic AI can really have an impact.'
Agents that are embedded into existing applications will make it easier to implement the technology across the business, says Timo Elliott, VP of Marketing and Global Innovation Evangelist with SAP. 'Building AI agent proofs of concept is surprisingly easy,' he says. 'Making them ready for real-world production environments is surprisingly hard.'
From application vendors to hyperscale cloud providers, the tech industry is working hard to help ease that process. For example, agents embedded in SAP's financial management products can help an accounts receivable clerk quickly settle a disputed invoice from a customer. Here's how it works:
An AI agent tasked with monitoring an inbox that houses customer inquiries would identify the dispute and alert the accounts receivable team, generating a case number and a summary of the issue. Next, the agent interacts with a help desk agent to review previous cases and the customer knowledge base to identify possible solutions. It then proposes a few suggestions to resolve the dispute—all in a matter of minutes.
A member of the accounts receivable team is then prompted to review the case, including the original customer e-mail and the proposed solutions. The clerk also can review the agent's reasoning and actions before making an informed decision on which solution to offer the customer. Based on the solution, the agent can then draft an e-mail for the clerk to approve and send.
'Application vendors know where to get the right data and understand the goals and context of the action being taken,' says Elliott. 'And they have the economies of scale to figure out how to set up these agents for each business decision or automation opportunity across all their customers.'
Push-button innovation
As agents gather more and more feedback, they will add more value through their ability to analyze existing processes and workflows and suggest changes to improve performance. That's when the concept of 'push-button innovation' becomes very plausible, says Elliott.
'Innovation becomes less like a staircase where you manually have to go up each step, and more like an escalator where the system takes you automatically to the next levels without you having to intervene, with each process constantly learning and improving and upgrading itself,' he says.
For example, a CIO, working with the CFO or the head of supply chain operations, could deploy a set of agents to scour industry news for hints on what could be done better or how other organizations or industries respond to sudden disruptions such as an unexpected trade war among several nations.
'These agents work with your organization's 'innovation agent' to suggest changes to ERP workflows, work with the 'strategic SI [system integrator] agent' to implement the changes, which would in turn work with the 'human organization and change management' teams of agents,' to ensure adoption and compliance, Elliott explains.
The CIO's role in change management also will escalate as these scenarios play out.
'We always talk about the importance of change management,' says Brenna. 'But in this case, it's even more critical to ensure adoption of any of the solutions you're implementing.'
Learn more on how agentic AI is transforming the role of the CIO here.
