What impact, if any, is scaling your organization’s AI operating model having on vendor relations?

SaaS vendors are moving from user-based to outcome-based pricing, driven by anticipated lower organizational headcounts and increased backend costs (e.g., GPUs). This shift requires organizations to assess whether to leverage vendor-created agents or develop their own frameworks, balancing cost and value.

Vendor relations are impacted by shifting pricing models. Many vendors initially include AI features at no extra cost, but prices often increase once capabilities mature. Some vendors price themselves out of consideration by demanding more than the efficiency savings justify. The rapid pace of change leads to instability, with some startups failing before pilots conclude. We focus on selecting vendors likely to persist through multi-year transformation programs and remain cautious about claims of free or low-cost AI.

As a regulated company, we are audited annually on AI adoption, requiring detailed tracking of all AI-related tools. Our AI governance, led by the Chief Risk Officer and CISO, evaluates new and existing AI capabilities for real impact versus marketing claims. The workflow ensures proper vetting and documentation for compliance.

Scaling AI has not adversely affected vendor relationships, but the pace of change is rapid. Vendors frequently update their AI roadmaps, sometimes accelerating developments mid-cycle. We approach vendors cautiously, avoiding beta testing where possible. Some capabilities are over-marketed, with the final product not fully delivering value. Adoption rates and the speed of change often outpace our ability to roll out solutions. Many AI offerings are niche, targeting specific industries or functions rather than broad enterprise needs.