March 24, 2026

Potential Obstacles to Effective Cognitive Procurement

In our last blog, we discussed cognitive procurement’s impact on enterprises and today we’ll explore the potential roadblocks for designing/developing an effective cognitive procurement system.

The scope for development is massive when it comes to building an effective cognitive procurement system but there are various obstacles which can hinder the development and it is crucial to successfully overcome obstacles in order to achieve desired results. The elation surrounding cognitive procurement and various associated new-age techs is deemed to be palpable as the future endeavors planned for cognitive procurement to be an industry disruptor completely relies on present-age developments. To actually achieve what we expect, the groundwork needs to be gradually laid and implemented. The route to success for cognitive procurement stems from these below-mentioned points -

First and foremost requirement is an adequate IT infrastructure support and a unified data-sphere. Technological infrastructure is viewed as a base for future developments and innovation. Without proper infrastructure, the data collection, data management, and data analysis are deeply affected. This generally happens due to lack of interconnectedness of data-sharing between various procurement operations. The analysis conducted based on incomplete data can potentially put the value-chain function in jeopardy.

Along with appropriate IT infrastructure, it’s crucial to have an understanding of business and corporate mechanics to interpret insights and take strategic decisions based on the analysis. Analysis-centric decision making needs to be prioritized to avoid any cultural war between previous practices and the strategic suggestions made by AI.

The requirement for well-qualified human capital is a necessity for expectations to turn into reality for cognitive procurement. A dedicated and talented team who are exceptionally conversant with new-age technologies are required in order to design, develop, implement and integrate cognitive solutions. The counter problem in creating and integrating cognitive solutions can be faced with resistance to change from internal (employees/workforce) and external (clients) sources, especially by people who are new to cognitive technologies and to its application-based solutions (for example, AI chatbots and self-service portals). Therefore, it becomes extremely important to build solutions customer-friendly and easy to operate to curb resistance to change.

Cognitive technologies today already influence areas of procurement and value-chain along with opening new opportunities for automation. As per the current scenario of development of cognitive procurement solutions, the area of analytics and reporting has already begun integrating big data and predictive analytics which are being tackled heavily with AI systems. The help desk and support is another area which has started using AI and chatbot solutions to automate user inquiry responses and support services.

Despite recent technological innovations in the procurement domain, the development in the area of predictive analytics and process optimizations is not yet fully illustrated. It is due to the higher complexities prevailing in procurement processes and the unstructured data entry types, which makes algorithm creation and automation of processes difficult. A general view denotes that the higher the complexity of process coupled with unstructured data entry types, the more complex is the use of solutions.

To put in perspective, if one drafts a chart of cognitive procurement technologies in terms of processing complexity against data input type to determine the scope of automation and complexity to develop, then the following picture emerges: No alt text provided for this image The above chart indicates that there is an ample amount of technological developments to take place and only with time the true potential of these cognitive techs can be experienced and leveraged. These thinking techs have a potential of replicating human-like behavior and strategic decision-making skills, which only grows over time with self-learning capabilities.

Lastly, to conclude, the best way to ensure that your organization is ready for cognitive procurement is to invest in digital transformation and new-age technologies. The following are some concrete recommendations for effective cognitive procurement establishment –

• Take the digital leap and start with automation of simple, repetitive, and time-bevvy tasks, using RPA solutions as they are already developed/matured and are being used heavily in the procurement-related operations (for example, data management, source-to-pay, reporting and analytics).

• Invest in building a centralized and unified data sphere, which connects all the procurement operations to communicate and share data. A cloud-based solution is an effective way of creating a centralized data repository for facilitating communication and to avail added security benefits.

• As you progress and integrate the more complex cognitive technologies such as AI, ML, and blockchain, it is advisable to be extremely cautious and keep patience. Even if you outsource or integrate solutions via a partnership deal, start with small pilot projects to observe and study the outcomes generated, before department-wide rollout. Being skeptical and prudent is normal, therefore indulge in educating and training your procurement team/organization as you design and implement cognitive solutions to curb any type of resistance to change.