B2B Suppliers Lag in AI Adoption as Digital Leaders Surge Ahead

A new study by Deloitte Digital has found that artificial intelligence adoption among B2B suppliers is moving more slowly than many business leaders expect, especially when it comes to advanced “agentic AI” systems.

The research, published on February 17, surveyed 530 U.S. B2B suppliers and 530 buyers. It found that only 45% of suppliers currently use AI in sales, and just 24% use agentic AI, which can act more independently in decision-making processes.

At the same time, companies classified as digitally “mature” are significantly outperforming their peers. According to the study, these firms exceeded their annual sales growth targets by 110% more than less digitally advanced competitors. They were also five times more likely to use AI extensively.

The gap becomes even clearer when compared to buyers. While 61% of B2B buyers reported using AI in purchasing decisions, and 38% said they are already using agentic AI, supplier adoption remains far behind.

The study suggests that limited IT capacity, ongoing ERP system upgrades, and budget constraints are slowing supplier adoption. In fact, 87% of suppliers said they are currently upgrading or planning to upgrade their ERP systems within the next year, which often absorbs key technology resources.

Budget pressure remains a major hurdle. About 62% of suppliers cited securing funds for technology investments as their top challenge, followed by rising customer expectations.

Deloitte also found that suppliers may be overestimating how automated their processes are. While 72% of suppliers believe their sales operations are highly automated, only 47% of buyers agree. Poor buying experiences are costing suppliers an estimated 13% of potential sales bids, while positive experiences are linked to a 36% increase in buyer spending.

The report concludes that AI alone will not close the performance gap. Companies that are seeing the strongest results are combining AI adoption with disciplined digital strategies and ERP modernization, while many others remain limited by time, budgets, and organizational capacity.