Artificial intelligence has quickly moved to the center of procurement strategy. By now, most organizations have moved past the question of whether AI has a role to play in the function. The more pressing issue is whether procurement leaders can show where it creates measurable business value.
For the past several years, procurement teams have been under pressure to modernize, automate and digitize. AI has emerged as the centerpiece of that transformation. Yet as adoption accelerates, many organizations are discovering that implementation alone does not guarantee results.
Research from the 2026 Economist Enterprise Report — titled Procurement at a crossroads: from optimism to realism and sponsored by SAP — highlights how the next phase of procurement transformation will be shaped by a more practical question: Can AI investments deliver measurable impact?
Procurement’s Top Transformation Priorities
The latest Economist Enterprise research reveals just how quickly AI has moved to the center of procurement strategy. More than half of executives surveyed (56%) identify AI adoption as the leading driver of digital transformation in procurement.
At the same time, digital transformation has become procurement’s most urgent strategic objective, with 60% of respondents ranking it as their top priority over the next 12 to 18 months, up from 38% a year ago.
These findings show how much executive expectations have shifted. Not long ago, spend visibility, sourcing automation or process efficiency were the headliners in procurement technology discussions. Today, AI is increasingly the lens through which leaders view those priorities and, ultimately, the future of the function.
The opportunity is significant. AI can help procurement teams process supplier, contract, spend and market data faster than ever before. It can surface patterns that humans might miss, and help teams respond more quickly to changing business conditions.
But enthusiasm alone does not return results. As organizations move beyond experimentation, expectations are changing.
Adoption Is No Longer Enough
Many organizations assume technology limitations remain the biggest obstacle to AI deployment. Economist Enterprise findings suggest the bigger issue is proving value. Nearly one-third of executives (32%) identify unclear return on investment as the biggest barrier to AI adoption in procurement, nearly double the number who cite integration challenges.
That finding signals a shift in executive scrutiny. Procurement leaders are no longer being asked whether they have an AI strategy. They are being asked what that strategy delivers.
As investments grow, so do business leaders’ appetite for outcomes. Procurement teams must increasingly answer questions such as:
- How will AI improve sourcing performance?
- Where will it reduce cycle times?
- What financial value will it create?
- How will success be measured?
Without clear answers, AI initiatives risk becoming disconnected from business priorities.
The organizations best positioned to make progress are identifying specific challenges and connecting AI capabilities to clear business outcomes.
One reason ROI remains difficult to demonstrate is that many organizations are still applying AI to isolated tasks rather than end-to-end business processes.
The research shows that AI is producing gains in automation, productivity and operational efficiency. Yet its impact becomes far less clear when organizations attempt to move beyond process improvements and into more strategic tasks. More than half (56%) of executives report no improvement in procurement decision-making from AI over the past 12 to 18 months.
This is an important distinction.
Automating routine activities can create immediate value. Improving decision quality requires something more complex: trusted data, integrated systems, governance frameworks and clear accountability. When faced with fragmented supplier information, disconnected contract repositories or inconsistent spend data, even sophisticated AI models struggle to generate insights that business leaders trust enough to act upon.
That is why the next wave of AI adoption will likely focus less on experimentation and more on operational discipline. Organizations need frameworks that connect AI recommendations directly to business outcomes and provide visibility into how decisions are made.
Governance Is Now a Competitive Advantage
As executive expectations rise, governance is becoming just as important as technology.
Procurement leaders need clear ownership for AI initiatives, success metrics defined upfront, and deployment plans aligned to specific procurement objectives.
Those objectives may vary by organization. Some teams may prioritize sourcing efficiency. Others may focus on contract compliance, supplier performance, category management or risk mitigation.
This is particularly important because procurement’s influence over enterprise technology decisions appears to be under pressure. Economist Enterprise research found that executive confidence in procurement’s role shaping digital transformation strategy declined from 91% in 2025 to 68% in 2026.
If procurement leaders cannot demonstrate value, ownership of AI strategy may increasingly shift toward centralized technology functions. Conversely, procurement teams that establish clear governance and measurable outcomes will be better positioned to shape how AI evolves across the enterprise.
The differentiator is execution.
Procurement leaders who connect AI investments to sourcing performance, contract outcomes, supplier collaboration and measurable financial results will create lasting competitive advantage. Those who focus solely on adoption risk becoming trapped in an endless cycle of pilots and proof-of-concept projects.
The next challenge for procurement is accountability. The organizations that can prove where AI creates value — and demonstrate that value consistently — will define the next chapter of procurement transformation.
Gordon Donovan is global vice president of research, procurement, and external workforce at SAP.