Infosys BPM is rapidly transitioning from traditional ‘AI-augmented operations’ with AI in the loop to ‘AI-first operations’ with humans in the loop, embracing all aspects of people, process, and technology that need to evolve for this transition. In particular:

• People: will need to develop AI-first and transaction elimination mindsets and increasingly become process influencers
• Process: domain and context knowledge will be complemented by an emphasis on responsible AI, leading to the introduction of new metrics such as process resiliency and trust indices. The nature of process design will change to include exception support by design, since AI inherently generates exceptions, and decisions will be AI-led and data-driven
• Technology: will increasingly involve purpose-built co-pilots and autonomous agents.

In line with the increased client requirement to demonstrate the responsible use of AI, Infosys BPM ensures that each AI agent developed for a client undergoes DPO, information security, and RAI approval. The company has developed a Responsible AI (RAI) framework, which is used to ensure that every AI use case is validated, with any risks identified as part of the implementation cycle.

Infosys BPM’s RAI engine is integrated into each of the company’s AI platforms, so that every request is filtered through the RAI engine to eliminate factors such as racial bias from both input and output perspectives.

Getting AI-ready

Infosys BPM is getting its own organization AI-ready by:

• Getting the workforce AI-ready, with initial AI training rolled out to 46K personnel
• Creating new AI roles, redefining some of the old roles through an AI lens
• Redefining the AI-First vision for each Infosys BPM practice
• Developing new domain-focused solutions to complement the AI-first vision of each practice
• Creation of playbooks; for example, for identifying use cases, delivering them, and taking AI to market.

It has developed ~10 in-house AI solutions and platforms. These include the development of agentic AI platforms and solutions such as Agentic APOC, Agentic AR, and data profiling assistants for master data management.

Overall, Infosys BPM has 26 clients where agentic AI has already been implemented, with 30-40 AI agents involved, and another 25 where implementation or discussions are underway. Prominent examples are covered below.

Agentic AI in Accounts Payable for Americana

Infosys BPM has deployed eight AI agents to support accounts payable for Americana, a restaurant chain with ~2,600 restaurants in the Middle East and Northern Africa, handling around 400,000 invoices per annum across five languages, including Kazakh and Russian. The service went into production in February 2025.

The documents received from the restaurant chain are complex and include a mixture of invoices, purchase orders, and goods received notes, all in various formats, typically dependent on the expense type. Each expense type also requires a potentially unique set of values to be captured for the ERP system.

Infosys BPM has developed two sets of AI agents to support processing these documents. Firstly, ambient agents process documents in the background, identifying the expense type and the required values, and categorizing each invoice as green, amber, and red. Secondly, assistant agents guide human agents in processing.

“Green” invoices are ready for posting. “Amber” invoices require a human in the loop to validate the processing that has been done. In this case, all invoices with values exceeding $5K are required to be manually checked. “Red” invoices are typically those where some processing has taken place but, for example, the purchase order number was incorrect or particular information could not be found.

Infosys BPM is finding traction for agentic AI in accounts payable, with five implementations underway since May 2025.

Agentic AI for Collections

Infosys BPM has developed AI agents for AR collections and applied them internally within Infosys BPM’s operations. The AI agents monitor multiple client payment portals, read email messages, and create follow-up emails for agents. Here, Infosys BPM has seven AI agents in production, resulting in faster cash collection and a 40%-50% reduction in subprocess effort. Infosys BPM’s wider agentic AI for Bill to Cash (collections) solution combines AI agents and RPA agents, which are autonomously integrated to achieve their goal.

Agentic AI to Drive Autonomous Sourcing

Infosys BPM has also implemented AI agents for spend data cleansing for a client, classifying and enriching 700K MRO data records. If the part number is available, browser-based agents with multilingual capability find the relevant information, curate it, and enhance the product descriptions.

This downstream data cleansing is facilitated by Infosys BPM’s sourcing team’s ongoing identification and uploading of relevant catalogs into a catalog repository within the sourcing solution.

Infosys BPM has further automated the sourcing process, with every purchase requisition going through the sourcing solution. This includes generating the product code, performing first-level negotiation, and contract negotiation. The results of this process are summarized by an AI agent to enable the selection of the most appropriate supplier. This process has now been further enhanced to include spend aggregation, enabling the achievement of additional savings.

Agentic AI Supporting Data Acquisition for Investment Firm

Infosys BPM has deployed six AI agents in support of data acquisition for an investment firm. Infosys BPM was previously capturing information from a limited number of websites, all in the English language, and now utilizes AI agents to create new customer contacts, update existing contacts, and maintain the client database. These AI agents can handle a fivefold increase in the number of websites and process multilingual information. The speed of information capture has also improved, enhancing the client’s time-to-market by 35%.

In the future, F&A will continue to be a key area for the further development of agentic AI at Infosys BPM. For example, in R2R, Infosys BPM is looking to create AI agents to interface with Blackline in areas such as journal entry uploads.

Infosys BPM also recognizes that, in much the same way AI agents combine multiple task skills, so agent orchestration platforms will increase in importance. Infosys BPM will utilize multiple AI agent orchestration platforms, including in-house platforms such as the EdgeVerve AI Next orchestration platform, leading third-party platforms, and solutions from new start-ups, depending on the client’s situation.

Moving Rapidly Ahead with A New Mindset

Infosys BPM is rapidly identifying use cases and building platforms to support client requirements for AI-first operations, developing new domain-specific AI-first solutions at pace. Much of its initial activity has been around Infosys BPM’s traditional focus areas of finance & accounting, sourcing and procurement, and order management, where the company has already developed and implemented end-to-end AI-first offerings.

Infosys BPM also recognizes that implementing AI-first operations requires a fundamentally different mindset and approach from more traditional AI-in-the-loop operations. Two key developments here are a greater emphasis on building exception support into the initial design and the integration of the company’s Responsible AI (RAI) engine into each use case to identify risks and eliminate bias in both inputs and outputs.

Summary

Infosys BPM is moving from ‘AI-augmented operations’ with AI in the loop to ‘AI-First operations’ with humans in the loop. In doing so, it:

• Is preparing its workforce by creating new AI roles and redefining existing ones
• Has developed ~10 AI platforms, including agentic AI solutions for APOC and AR, with 30-40 AI agents deployed
• Deployed its Responsible AI (RAI) framework in every agentic AI use case for risk identification and to eliminate biases in inputs and outputs
• Will leverage multiple AI orchestration platforms, and further embed exception handling and Responsible AI in all AI-first operations.