Every year, thousands of enterprise organizations walk into technology negotiations trapped by the same fundamental mistake: they negotiate a product instead of solving a problem.
Having advised over 2,000 enterprise customers annually on technology acquisition over two decades, I see this pattern play out daily. Purchasing committees meticulously list the specific features, software modules and server specs they think they need, converting their organizational requirements into a static shopping list. On paper, this strategy feels disciplined. It creates a standardized, predictable item that procurement can use to negotiate a line-item discount with providers.
When you buy a fixed product, you get the immediate, gratifying perception of a lower price. But that upfront discount can come at a hidden cost: you risk cutting yourself off from the disruptive innovation of emerging technologies like artificial intelligence (AI).
By prescribing the solution before the negotiation even begins, enterprises force vendors into the narrow role of commodity suppliers rather than strategic partners. You ask them, “How cheaply can you build what our internal committee specified six months ago?” instead of asking, “What is the most efficient way to achieve this outcome today using capabilities we might not even know exist?”
In an era where AI can reshape entire operational workflows, anchoring your procurement strategy to fixed product specifications means you may pay less for yesterday’s way of doing business while missing the value of new capabilities.
When procurement treats technology as fixed products, it tries to bundle mature products, such as software-as-a-service (SaaS) licenses, with rapidly evolving capabilities, such as AI services billed by token consumption, into one grand contract. You end up applying three-year static product licensing to AI capabilities that change on a monthly basis, locking your company into rigid pricing models and outdated technology.
A request for proposal (RFP) is the ultimate manifestation of product-first buying. It forces vendors to answer 200 static questions about prescribed features rather than offering alternative solutions. Procurement celebrates negotiating a 15% discount on a legacy customer service product, completely unaware that an outcomes-based AI approach could have eliminated 70% of the support tickets altogether. You win the unit-price battle, but lose the total cost of ownership (TCO) war.
Procurement departments use RFPs with the goal of driving down unit costs and reducing risk. But as behavioral expert Rory Sutherland has argued, corporate purchasing can prioritize blame avoidance over value creation. RFPs require the buying organization to specify the technical solution long before it enters a room with the experts who could help solve the original problem.
The RFP backfires in two distinct ways:
You force vendors to answer the wrong question
An RFP asks vendors: “How much will you charge to build what our internal committee decided we need six months ago?” It denies the seller the ability to say: “The problem you are trying to solve can now be eliminated using a new approach you haven’t considered.”
Shifting costs rather than reducing them
RFPs do not necessarily lower TCO; they can shift costs around while inflating administrative overhead. Software goes unused, becoming shelfware, because the focus was placed on winning the RFP pricing battle rather than user adoption and operational enablement. The company then has to spend more on adoption, while employees may turn to unsanctioned tools, known as shadow IT, duplicating costs and eroding the negotiated savings.
When enterprise buyers attempt to simplify procurement by bundling SaaS, infrastructure-as-a-service (IaaS) and AI into a single, multiyear contract with a hyperscaler, they can make switching providers harder. Research published by Harvard Business School on platform strategy explains how bundling can reinforce customer retention even when one component disappoints. Buyers need to evaluate the flexibility of each component, not just the combined discount.
A good example is what happened to one of my customers: an unmonitored script loop written by a developer unexpectedly burned through 18% of their annual infrastructure commitment in AI token consumption over a single weekend. By bundling emerging, unpredictable technology with stable infrastructure services, they exposed an otherwise predictable IT budget to financial volatility.
Buying technology correctly means matching the contract model to the technology’s maturity stage. Treating an emerging, fast-evolving space like AI with the same three-year static lock-in used for corporate email is a governance failure.
Another of my customers, a regional insurance company, issued a 200-question RFP to replace its customer service center software, seeking an AI-driven system to handle support tickets 20% faster.
Consider the limitations of that RFP: procurement issued a spreadsheet demanding details on call-center headcount, staff rotation rates and employee training certifications. An AI startup whose autonomous agent framework proactively fixes customer problems before a support ticket is even logged refused to participate because the questionnaire assumed a human workforce. The deal went to a legacy vendor that answered all 200 questions and offered a 15% discount. Procurement celebrated a price drop on seat licenses, even though it had just committed millions to perpetuating the existing operational model.
The buyer saved 15% on seat licenses, but spent $3 million over two years maintaining the call-center workflow. Had the company abandoned the rigid RFP, it could have eliminated 70% of its call volume entirely. Procurement successfully minimized the unit cost of the contract while missing the potential value of a different capability.
If we want to stop buying technology wrong, CIOs and purchasing committees must adopt three fundamental shifts:
- Decouple contracts by maturity stage: Keep mature SaaS, optimizable IaaS and emerging AI in independent contractual structures. This preserves the flexibility to swap out emerging tools as better models hit the market without triggering financial penalties on core systems.
- Replace rigid RFPs with proof-of-value (PoV) sandboxes: For disruptive technologies and services, replace prescriptive questionnaires with small, rapid experiments that allow vendors to prove outcomes. Define the business problem, success criteria, budget and security requirements before testing. Pay to solve the problem, not just to acquire the product.
- Prioritize local enablement and FinOps over direct discounts: A 10% direct manufacturer discount means little if 30% of your cloud infrastructure is overprovisioned or if your employees never adopt the software. FinOps aligns technology spending with business value through collaboration among engineering, finance and business teams. Evaluate what your internal team or a multicloud partner can deliver in user adoption, local-currency billing, support for local tax requirements and ongoing cost management. Compare the full cost and return on investment (ROI), rather than the discount alone.
It’s time for enterprise leaders to stop managing technology procurement like a commodity auction. The goal of buying technology isn’t to get the lowest price on yesterday’s specs; it is to secure the greatest speed, flexibility and business value.