From manual processes to intelligent procurement: How are enterprises embracing AI and automation

Enterprises are moving from paper-based and spreadsheet-heavy purchasing to intelligent procurement, empowered by growing technology, including artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA), in order to transform the entire source-to-pay (S2P) lifecycle.

Several firms have shifted from using AI merely to analyse and spend toward deploying it as an operator, as agents now create purchase orders, route multi-level approvals, and flag supplier anomalies before any involvement of humans. Interestingly, teams in the firms deploying AI typically cut cycle times by 40 to 60 per cent and improve productivity and efficiency of the result more precisely without consuming extra effort and time.

While AI, automation and cloud platforms are becoming increasingly accessible, many organisations continue to operate with legacy systems, fragmented data and processes that were not designed for today’s pace of business. For large enterprises, the challenge is no longer simply about investing in newer technology. It is about connecting existing systems, improving the quality of data and redesigning workflows so that technology can deliver measurable improvements in productivity, efficiency and decision-making.

This shift is particularly visible in functions such as procurement, where organisations are looking to move beyond manual processes and disconnected systems towards more intelligent, integrated and user-friendly experiences. At the same time, the growing use of AI is raising new questions around governance, security, human oversight and how businesses can translate experimentation into tangible operational value.

In a conversation with WION, Trishna Patel, Head, Ewiz Procure, Powerweave, and Reena Ravindran, VP – Delivery, Powerweave, discuss the major challenges enterprises experience in modernising legacy environments and the changing expectations around procurement. They also focused on how AI can deliver measurable business outcomes, and the importance of balancing automation with human judgement and responsible technology adoption.

1. Many enterprises continue to operate with legacy systems and fragmented data. What are the biggest challenges they face when modernising their technology infrastructure?

Trishna Patel, Head- Ewiz Procureat Powerweave: One of the biggest misconceptions is that modernisation means replacing legacy technology. In reality, the bigger issue is often the fragmentation of data, processes and workflows around it. Large enterprises have invested heavily in ERP and other core platforms, but many still operate with disconnected systems, inconsistent master data and manual processes outside those platforms. Modernisation is therefore as much a data and operating-model challenge as a technology one.

The starting point should be the business problem: where is the process breaking down, where is data unreliable, and where are manual interventions limiting visibility or efficiency?

"We see this often in procurement. With ewiz procure, we work alongside systems such as SAP, Oracle and Coupa. We first understand the business objective and process gaps, then fix the underlying data and governance, automate the right workflows, and introduce AI where it can add meaningful value. That is where enterprise modernisation is heading: not replacement for replacement’s sake, but making existing investments work harder through cleaner data, better-connected processes and more intelligent automation," Trishna said.

2. With AI becoming more accessible, how can businesses move beyond experimentation and translate AI investments into measurable operational outcomes?

Reena Ravindran, VP-Delivery at Powerweave: AI will create real value when businesses stop treating it as a standalone technology experiment and start embedding it into the way work actually gets done. The right question is not how many AI pilots an organisation has launched, but which business metric has improved because of them. To get there, AI needs to sit inside a defined workflow where it can influence decisions, automate repetitive steps and improve cycle times.

That also requires the right foundation: reliable data, clear process ownership, team training, change management and controlled evaluation. Without those elements, even a strong AI capability can struggle to deliver sustained operational value. We have seen this in practice. In one chemical manufacturing deployment, the results came not from AI alone, but from redesigning the procurement workflow around structured data, automation, system integration and digital decision support. PR-to-PO processing time was reduced by 87%, while supplier onboarding time dropped by 95%. I think that is the real shift enterprises need to make. AI should not sit beside the process as another tool. It needs to be embedded into the workflow, supported by good data, governance and adoption. That is what turns experimentation into measurable business outcomes.

3. How are customer expectations evolving in procurement, particularly among manufacturers, distributors and wholesalers?

Trishna Patel, Head- Ewiz Procure at Powerweave: Procurement users are no longer comparing their experience only with other B2B systems. They are comparing it with the best digital experiences they use every day, raising expectations around speed, visibility, self-service and ease of use. They expect every interaction with a procurement tool to feel seamless and intuitive, whether they are searching for a product, raising a request, approving a purchase or onboarding a supplier.

With tools like ChatGPT shaping user behaviour, that experience is also becoming more conversational. Users increasingly expect to describe what they need in natural language and be guided to the right action without navigating complex menus. For manufacturers, distributors and wholesalers, the challenge is to hide complexity rather than expose it. Data, workflows, approvals and intelligence need to work together behind the scenes while the user gets a simple, connected experience. The competitive advantage will increasingly come from removing friction across the procurement journey while improving control, visibility and compliance.

4. How does Powerweave measure the impact of its solutions for customers? Could you share examples of business challenges addressed and outcomes achieved?

Reena Ravindran, VP-Delivery at Powerweave: Technology should never be the outcome. The outcome is the only reason to deploy technology in the first place. We therefore establish a baseline before measuring impact. In ewiz procure, customers have seen 8–12% savings on indirect procurement, sourcing cycles around 30% faster and 27% lower process costs. In one procurement data cleaning project, we helped uncover €40M vendor-consolidation opportunity for a global manufacturer. The opportunity was already there. We just helped them uncover it.

In awspromostack, AI has reduced order-entry effort by 40% and art and booking effort by 60%, while storefront and product-listing creation is 80% faster. Our operations process more than 40,000 orders a day at over 98% accuracy. Across these examples, the principle is consistent: we measure what changed in the business, not how much technology was deployed

5. With customers across multiple geographies, how does Powerweave adapt its solutions to different markets, regulatory environments and business requirements?

Trishna Patel, Head- Ewiz Procure, Powerweave: Global technology does not mean identical technology everywhere. The foundation can be common, but the context cannot. Regulations, workflows, data structures and customer expectations vary significantly by market. The real capability lies in knowing what should be standardised and what must remain local. Snowkap is a good example. An Indian business may operate under BRSR and BRSR Core while also responding to frameworks such as CSRD, GRI, TCFD or IFRS when serving global markets.

The same principle applies to procurement. ewiz procure works with the customer’s existing ERP, S2P and supplier landscape, while adapting workflows, data structures, approvals and governance to local business requirements rather than forcing a single operating model everywhere. Our approach is therefore to build adaptable technology around the customer’s reality. Scale comes from a strong common foundation; relevance comes from understanding the market, regulations and operating model in which that foundation has to work.

6. As AI becomes more deeply integrated into business operations, what responsibilities do technology leaders have in ensuring its adoption is practical, secure and aligned with business objectives?

Reena Ravindran, VP-Delivery, Powerweave: The responsibility of a technology leader is no longer simply to ask whether AI can be deployed. It is to decide where AI can create measurable business value, how it should fit into existing workflows, and where human judgement must remain. AI is highly effective at processing information, identifying patterns and automating repetitive work. But relationships, commercial judgement, risk and strategic decisions often depend on context that cannot be captured in data alone. That is why we believe in progressive adoption: automate administrative work first, augment human decision-making next, and introduce greater autonomy only where the controls, data and context support it.

Security and governance are equally fundamental. That means clear access controls, data governance, auditability, defined decision rights and human oversight, alongside strong enterprise security standards. Powerweave's platforms and operations are ISO 27001 certified and SOC 2 Type II audited. Responsible AI ultimately comes down to four things: a clear business purpose, reliable data, appropriate controls and clear accountability for the outcome.