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Highlights
- GenAI’s ability to generate actionable insights from large data sets can help procurement organizations mitigate risk and optimize cost in highly volatile market conditions.
- GenAI can add significant value in key procurement functions such as supplier strategies, predictive demand forecasting, spend analytics, supplier relationship management, and contract management.
- CPOs can transform the procurement function by focusing on use cases that deliver maximum business value with least investment risk.
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GenAI’s growing role
The importance of artificial intelligence (AI), specifically generative AI (GenAI), in the re-imagination of operations is only growing.
GenAI excels in a wide range of diverse tasks, such as extracting, analyzing, and summarizing insights from multiple data sources, automating complex tasks, and analyzing historical and current market trends to identify potential risks and opportunities.
It is finding increasing acceptance among CPOs as this cutting-edge technology boosts efficiencies, unlocks new sources of value, and provides a competitive edge in the market.
Building value
Sourcing and procurement operations have historically been swift to adopt technological disruptions.
From leveraging automation for operational efficiencies to analytics for spend categorization or deploying conversational AI for guided buying, procurement functions have continuously innovated to reduce costs and gain more control with better visibility and compliance.
Highly volatile market conditions have put additional pressure on procurement organizations to mitigate risk and optimize costs. This is where GenAI can come to the rescue with its ability to generate actionable insights and create new content by emulating large data sets.
Let’s look at the key areas where GenAI can add value to the procurement function:
- Supplier strategies: GenAI powered tools can quickly scan vast databases of potential suppliers and shortlist those who meet specific criteria such as location, industry, product offerings, and sustainability guidelines. AI algorithms also analyze supplier performance data to assess their reliability, financial status, and compliance with regulatory frameworks and quality standards. Using historical data, GenAI can also predict which suppliers may increase prices in the future, allowing the organization to act pre-emptively.
- Predictive demand forecasting: GenAI-powered software analyzes historical sales data, market trends, and external factors to accurately predict future demand for goods and services. This enables procurement teams to optimize inventory levels, avoid stockouts, and negotiate better terms with vendors.
- Spend analytics: AI can analyze vast amounts of procurement data to provide key insights into spending patterns, cost-saving opportunities, maverick spending, and potential risks. The information helps optimize sourcing strategies, negotiate better commercial terms, and improve overall procurement efficiency.
- Contract management: AI automates creating, reviewing, summarizing, and negotiating contracts. By analyzing legal documents based on pre-defined criteria and legal requirements, AI-powered systems ensure that contracts are legally compliant and aligned with business objectives and sustainability regulations.
- Conversational bots: GenAI powers virtual assistants that can answer questions, provide recommendations, and automate routine procurement tasks. These chatbots act as personal buying assistants, allowing users to identify the right products, create or auto-fill purchase requisitions, seek approvals, and provide status information based on pre-defined guidelines. This frees up employees of procurement organizations to focus on more strategic tasks.
- Data analytics: Textual analysis with GenAI can be used to analyze unstructured data such as supplier reviews, social media posts, and news articles to gain insights into price trends, supplier sentiment, and geo-political risks. This will help with vendor evaluation, compliance monitoring, market intelligence, and contractual risk management.
- Supplier relationship management (SRM): GenAI can create personalized communication templates for suppliers based on their performance and relationship history. This helps to strengthen supplier relationships and improve collaboration.
Ambition into action
To extract the maximum value out of GenAI, procurement functions need to outline a clear strategy aligned with their long-term business goals.
GenAI adoption is a continuous journey, and organizations need to put an ecosystem in place to ensure its successful integration into existing processes.
Some key factors for procurement organizations to consider before embarking on their GenAI adoption journey are:
- Data quality: AI and GenAI rely on high-quality data to be effective. Organizations must ensure that their data is accurate, complete, and up to date. Organizations need to regularly cleanse their master data from time to time and streamline their data pipelines to achieve this.
- Talent: A robust talent strategy that addresses digital upskilling and is prepared to pivot talent to other strategic areas where GenAI significantly changes job definitions is critical.
- Ethical considerations: The use of AI raises ethical concerns such as bias, privacy, and job displacement. Organizations need to appropriately address these concerns and take steps to mitigate them.
AI and GenAI are poised to play a key role and bring in a disruptive change in procurement strategy, governance, and innovation.
CPOs need to take a pragmatic approach to GenAI, focusing on tackling the ‘low-hanging fruits’ such as the AI use cases that deliver maximum business value with the least investment risk—like those mentioned in this article. Through this measured and gradual approach, CPOs can leverage AI and GenAI to revolutionize the procurement function.
A large entity’s procurement process transformed
TCS supercharged the procurement process for a global steel major with GenAI.
This steel manufacturer’s procurement process was largely manual, effort-intensive, and iterative. It used to take almost 30 days to release a purchase order (PO) after the indent was raised by a user. The process was streamlined using various TCS Cognix™ powered AI and GenAI interventions.
GenAI is used to prescribe vendors based on evaluation criteria, generate customized communication for suppliers, and suggest the recommended price of items by analyzing several internal and external factors.
As an outcome, the cycle time has now reduced to 10 days (from 30 days), and the on-time in full (OTIF) improved from 70 to 90%, leading to a positive impact on user experience and cash flow.
