Enterprise AI is having a moment. As Nvidia CEO Jensen Huang said recently, “AI agents represent the new digital workforce. The IT department in every organization will evolve into the HR department for AI agents in the future. This multi-trillion-dollar opportunity will fundamentally change how we work and create value.”
Is it hype or the future? It is likely the latter, as enterprise AI applications are finding new fans in the C-suite. That comes thanks in part to AI’s role in enterprise procurement. GenAI, in particular, has significantly impacted enterprise procurement, yet adoption remains divided. While 8 in 10 CFOs report using AI in procure-to-pay cycles, just 25% specifically leverage GenAI. A key reason for this divide is undefined operating standards, particularly regarding data privacy, accountability and traceability.
More than one-third of CFOs see this lack of clarity as a moderate or significant barrier to investment. Meanwhile, 42% of CFOs already using AI tools have no plans to adopt GenAI, citing governance concerns. CFOs leveraging GenAI for high-impact tasks worry about data privacy risks (91%) and deepfakes (57%). Likewise, 67% of those using it for medium-impact tasks cite job displacement as a primary concern.
Despite these hurdles, nearly 3 in 4 enterprises now use or are considering using GenAI to enhance procurement efficiency. Addressing privacy and sustainability safeguards could help bridge the confidence gap, especially among firms reluctant to expand GenAI adoption.
These findings come from “The Investment Impact of GenAI Operating Standards on Enterprise Adoption,” a PYMNTS Intelligence study produced in collaboration with Coupa. This report examines how CFOs navigate GenAI investment decisions and is based on insights from 60 CFOs at U.S. firms generating at least $1 billion in revenue, surveyed from Jan. 8 to Jan. 16.
Lack of GenAI Operating Standards Slows Investment
Operating frameworks are a critical barrier to GenAI expansion.
Thirty-eight percent of enterprise CFOs see unclear GenAI operating standards as at least a moderate barrier to investment, with the impact varying by use case complexity. For this study, we use a proprietary scoring system to group firms into low-, medium-, or high-impact personas based on how they use GenAI. Low-impact firms use routine, low-risk applications for individual tasks, like summarizing information or drafting emails. High-impact firms deploy complex, strategic applications that monitor processes, assess risks and generate content, directly influencing business outcomes — such as autonomous cybersecurity or real-time production monitoring.
Among high-impact users, 91% cite data privacy as a concern while 57% worry about misinformation and deepfakes. For medium-impact users, 67% identify job displacement as their primary concern — the highest level across all groups. These CFOs, who deploy GenAI for predictive analytics and customer service automation, view automation-driven workforce reductions as a more significant challenge than privacy risks.
Low-impact users remain the most skeptical. Every CFO in this category considers unclear standards a moderate or significant barrier. For 40%, this concern is substantial enough to stall investment. Concerns about bias and fairness also weigh more heavily in this group, with 40% seeing it as a key issue, compared to 28% of the total sample.
Hesitation extends beyond current users. More than half of skeptics — CFOs not considering GenAI — cite ethical concerns as a moderate or significant investment barrier. Even among those already using other AI tools, 42% say they are unwilling to adopt GenAI due to governance concerns.
Without stronger privacy, accountability and bias mitigation safeguards, GenAI adoption will remain fragmented. Enterprises that develop clear operating frameworks will be best positioned to scale GenAI use in procurement.
GenAI Operating Standards Could Drive Wider Adoption
CFOs see value, but uncertainty stalls expansion.
Seventy-three percent of enterprises are using or considering GenAI to improve procurement operations, but unclear operating standards slow expansion. While firms recognize GenAI’s efficiency potential, many hesitate to commit without stronger governance frameworks for privacy, security and compliance.
Adoption levels vary across firms based on revenue, industry and task complexity. Larger enterprises — particularly those generating $10 billion or more in revenue — show the highest exploration rates, with 71% considering GenAI. Smaller firms are more cautious, with just 39% of those in the $1 billion to $5 billion range evaluating its role. Likewise, more firms in this segment already use GenAI compared with larger enterprises, at 33% versus 14%.
- Adopters (25%) actively use GenAI in their procure-to-pay cycle. These firms likely see tangible benefits in operational efficiency but are also aware of challenges with data privacy and missing information.
- Explorers (48%) show interest in leveraging GenAI in their procure-to-pay cycle but likely need clearer frameworks before moving forward. They represent the most significant opportunity for future adoption.
- Skeptics (27%) do not leverage GenAI in their procure-to-pay cycle and remain hesitant to do so. These firms cite trust, reputation and uncertain ROI as primary barriers.
Use case complexity also affects willingness to adopt. Among firms deploying GenAI for high-impact automation, 30% have already adopted it for procure-to-pay processes, while 48% are still evaluating it. By contrast, firms using GenAI for low-impact tasks — such as email drafting and document summarization — are far less likely to have expanded their use to procurement processes.
A strategic shift is needed for GenAI adoption to scale. Rather than justifying AI’s usefulness, vendors must emphasize operating frameworks that ensure safety, reliability and compliance. As GenAI adoption increases, organizations that develop explicit governance models will gain a competitive edge.
Stronger GenAI Operating Standards Will Overcome Barriers
Leadership wants more straightforward safeguards before expanding GenAI usage.
CFOs recognize GenAI’s potential in procurement but hesitate to expand its use without clearer operating standards. Data privacy, bias and AI reliability remain the most significant concerns, limiting broader adoption. Establishing transparent governance frameworks could increase confidence and drive investment.
Ninety-one percent of CFOs using GenAI for impactful and complex tasks cite data security as a top concern. Many firms will not deploy GenAI at scale without strong data protection measures. Skeptics see human oversight as critical, with 56% believing AI still requires significant manual intervention. Bias and sustainability concerns further slow adoption. Half of skeptics worry about bias in AI-generated procurement data. Half of all skeptics say sustainability is key to GenAI’s ethical use. Firms demand clearer policies to mitigate unintended biases and environmental impacts.
Adopters see efficiency benefits, but many encounter missing or unreliable AI-generated data. Sixty percent of adopters report missing information in GenAI procurement outputs, and 69% of explorers cite accuracy issues as a reason to avoid adoption. These reliability concerns reinforce skepticism and slow GenAI investment decisions.
To bridge these gaps, firms must implement traceability measures, including audit trails, explainable AI models and human-in-the-loop oversight. Stronger governance will help address concerns and increase adoption. Organizations that develop clear AI operating standards will lead in adoption. Firms that ensure trust, security and regulatory compliance will gain a competitive edge in procurement optimization.
The future of GenAI in procurement depends on trust and standardization.
CFOs agree that GenAI’s potential is clear, but uncertainty around standards remains a critical barrier. Even among enterprises already using GenAI, concerns about output reliability, privacy risks and governance limit full-scale adoption.
- Sixty-nine percent of explorers worry GenAI outputs may contain errors, making them hesitant to integrate the technology into procurement workflows.
- Sixty percent of adopters have encountered missing or incomplete information in AI-generated procurement data.
- Fifty-six percent of skeptics believe GenAI still requires excessive human oversight, reducing confidence in its ability to automate procurement processes.
Despite these challenges, most enterprises see a path forward. CFOs believe stronger privacy protections, bias mitigation and explainability frameworks could drive broader adoption. Fifty-three percent of all adopters cite sustainability as key to GenAI’s ethical use, while 87% of CFOs rank user privacy protections as essential.
For GenAI to play a larger role in procurement, firms must establish clear accountability models, maintain audit trails and improve transparency. Enterprises prioritizing governance and security will now be positioned ahead of competitors as adoption accelerates.
Read More
PYMNTS Intelligence is the leading provider of information on the trends driving AI adoption across the C-Suite. To stay up to date, subscribe to our newsletters and read our in-depth reports.
Methodology
“The Investment Impact of GenAI Operating Standards on Enterprise Adoption” is based on a survey conducted from Jan. 8 to Jan. 16. The report examines how enterprise CFOs assess GenAI for procure-to-pay operations, focusing on adoption levels, key concerns, and governance challenges. Our sample included 60 CFOs from U.S. firms generating at least $1 billion in annual revenue. The findings reveal that while 73% of enterprises are using or considering GenAI in their procure-to-pay cycle, concerns over data privacy, missing information and bias slow investment. Stronger governance frameworks could drive confidence and accelerate enterprisewide implementation.
