TLDR: Gartner’s latest analysis reveals that while generative AI (GenAI) adoption is increasing within procurement, the technology has entered the ‘trough of disillusionment.’ This phase signifies a period where initial excitement gives way to more realistic expectations, as organizations grapple with significant challenges related to data quality, system integration, and regulatory uncertainties, despite the clear benefits of efficiency and cost savings. Gartner projects GenAI for procurement will achieve full productivity within five years.
Generative AI (GenAI) is experiencing a surge in adoption across procurement functions, yet it has simultaneously entered a critical phase known as the ‘trough of disillusionment,’ according to a recent report from research and consultancy firm Gartner. This stage, part of Gartner’s Hype Cycle for Procurement and Sourcing Solutions, indicates that while early adopters have seen benefits, many organizations are struggling to achieve consistent returns on their investments, leading to a cooling of initial enthusiasm.
Kaitlynn Sommers, Senior Director Analyst in Gartner’s Supply Chain practice, highlighted the dual nature of GenAI’s impact. “GenAI is proving to deliver process efficiency, better data insights, and cost savings for procurement organizations,” Sommers stated. The technology’s applications are diverse, focusing on automating time-consuming, repetitive tasks such as knowledge discovery, summarization, contextualization, workflow, and execution. This automation is expected to boost productivity, reduce operational costs, and allow staff to focus on higher-value activities like strategic decision-making and supplier management.
However, the path to widespread success is fraught with obstacles. A primary challenge identified by Gartner is the prevalence of fragmented and low-quality data across existing procurement systems, which can significantly hinder the accuracy and reliability of GenAI outputs. Furthermore, integrating stand-alone GenAI solutions with established platforms often proves complex due to differing technical specifications. Beyond technical hurdles, organizations face difficulties in changing long-standing processes, and there are considerable uncertainties surrounding new regulations, raising concerns about privacy, intellectual property, and trust. Employee resistance, job security fears, and skepticism regarding AI-driven insights also contribute to adoption challenges, alongside high and unpredictable costs.
Despite these hurdles, the applicability of GenAI across the entire source-to-pay spectrum continues to drive strong interest and adoption. Sommers cautioned that “Organizations that delay action on integrating GenAI into procurement processes risk falling behind as early adopters overcome these challenges and realize tangible benefits.”
Gartner projects that GenAI for procurement will mature and become a fully productive technology within the next five years. To navigate the current ‘trough of disillusionment’ and achieve long-term success, Gartner advises chief procurement officers (CPOs) and organizations to take several strategic steps. These include investing in robust data infrastructure to standardize and integrate information, carefully selecting AI solutions that align with specific business goals, adapting procurement processes to effectively incorporate new technologies, closely monitoring legal and regulatory developments to ensure compliance, and upskilling procurement teams to foster trust and improve human-AI collaboration.
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This trend aligns with broader forecasts for GenAI spending, with worldwide end-user spending on GenAI models projected to reach $14.2 billion in 2025. Spending on foundational GenAI models, including large language models (LLMs), is expected to remain the largest segment, growing from $5.4 billion in 2024 to $13.1 billion in 2025, underscoring the significant investment and transformative potential of this technology across various sectors, including procurement.
