AI IS REWRITING TECHNOLOGY & SOFTWARE SPEND
AI is reshaping how enterprises buy, build, and pay for software. As investment accelerates, buyers and sellers are making decisions about where AI delivers value, which capabilities to purchase or develop, and how pricing models need to evolve.
We surveyed 316 U.S.-based executives directly involved in buying AI/enterprise software (buyers) or involved in or informed about pricing and/or product decisions at their company (sellers). Here’s what we found.
Build vs. buy: Software sellers overestimate how often buyers build AI solutions.
Buyers and sellers are operating in the same AI market, but they do not always see it the same way. Comparing how buyers describe their own approach with how sellers describe their customers reveals a meaningful gap in expectations around build versus buy.
West Monroe’s Advice on Build vs. Buy:
Define the job first
Identify the workflow, user, and measurable outcome you want to improve. Clear requirements make it easier to compare a vendor solution with an internal build.
Buy for proven needs
Choose a commercial tool for standard workflows. Test it with real users and account for its total cost and security integration before scaling.
Build for real differentiation
Build when proprietary data or strategic control create a meaningful advantage. Include the engineering, governance, and maintenance the solution will require over time.
AI capabilities: Sellers and buyers don’t fully agree on where AI investment is going.
Both buyers and sellers see AI investment concentrating in a handful of areas, but their priorities diverge beyond the top of the list. Those differences offer a view into where customer demand is clearest and where software providers may be getting ahead of, or lagging, buyer priorities.
West Monroe’s Advice on AI & Software Investments:
Connect spend to outcomes
Set a clear business goal for each investment and how you’ll measure progress. That gives teams a basis for comparing opportunities and deciding what to scale.
Fund the foundation
Plan for the data, infrastructure, integration, security, governance, and talent that make AI usable across the organization—not just the cost of the models or tools.
Scale with evidence
Start with focused use cases, track adoption, performance, and cost, then expand what delivers results. Revisit priorities as technology and business needs change.
Pricing: Software sellers are moving toward pricing models buyers don’t prefer.
AI is already changing how software is priced, but buyers and sellers are not aligned on where pricing is headed. Buyer preferences still favor enterprise subscriptions and usage-based models, while sellers expect hybrid pricing to become the leading approach over the next three years.
West Monroe’s Advice on AI & Software Pricing:
Anchor pricing in shared value
Buyers should look for clear links between price and outcomes. Sellers should make those outcomes measurable and show how their pricing reflects them.
Make costs transparent
Buyers need to understand and forecast total costs. Sellers should explain what drives the bill and provide clear usage limits or tiers.
Choose a model that fits
Buyers should assess whether the pricing fits how they use and budget for the software. Sellers should choose a clear model that reflects customer value and delivery costs, without adding unnecessary complexity.
Want A Deeper Dive?
Download the full research to see where technology and software buyers and sellers align, where expectations diverge, and how AI is reshaping budgets, pricing, vendor relationships, and value creation.
Methodology
The State of B2B Enterprise Software & AI Spend (2026) was fielded via online survey by Centiment in August 2026. Respondents included 156 U.S.-based executives directly involved in buying AI/enterprise software (buyers) and 160 U.S.-based executives involved in or informed about pricing and/or product decisions at their company (sellers).
