The current IT procurement process delivers the speed, scale or results leaders expect. Meanwhile, traditional supplier models optimize for selection and price, not for business outcomes and impact.
Those current approaches waste time and money and stall momentum. The average global enterprise can throw away millions of dollars each year because it cannot get the technology it needs to compete. This waste will climb as AI becomes central to differentiation.
Enterprise AI initiatives benefit from Tier 1 provider relationships because AI does not behave like traditional IT. In IT, solutions typically automate tasks and remain static until someone changes them. In AI, solutions learn, adapt and improve in production. That shift carries three consequences:
Processes become dynamic. Models must reflect a changing environment. That requires rapid iteration, tight feedback loops and direct line of sight to business decisions, which is best provided in a Tier 1 setting.
Data becomes a durable asset. In IT, data is a byproduct. In AI, data is the raw material for new capabilities. Data is not limited to what the enterprise knows when Tier 1 providers extend the data involved in decisions.
Change becomes continuous. Value grows with usage and learning, rather than one-time IT purchases and project-based investments. Tier 1 relationships give providers and enterprises the means to continuously drive innovation and business impact.
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These differences demand relationships optimized for speed and compounding value, not for episodic selection events.
Tier 1 providers sit close to the enterprise's core value creation and its leaders. In manufacturing, these are the suppliers whose products feed directly into what customers buy. The same idea applies to AI. Tier 1 technology providers codevelop strategy, products and operating models with their clients. They bring essential assets to compete. Enterprises assess them by results delivered, not by the size of the purchase order.
Three practical changes define the model:
Measure value, not spend. Judge providers by the growth they enable, the cost they take out, the risks they mitigate or the learning they unlock. Track time to impact and the reuse of data and models across the business.
Mutually commit to business outcomes. Replace adversarial buying with joint planning and shared roadmaps. Incentivize providers on business results through consumption, milestones and value sharing. Avoid cost-plus structures that misalign incentives.
Adopt a promotional mindset. Treat the relationship as a competitive advantage. Share data, insights and risk with a small number of strategic partners to move faster together than either party could alone.
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A Tier 1 partnership becomes necessary when the organization pursues goals that exceed the limits of standard market-based technology solutions. Tier 1-based solutions drive AI transformation as enterprises modernize their business models with AI‑infused products or services.
Situations that benefit from a Tier 1-style relationship include altering the enterprise's competitive position, touching multiple profit-and-loss statements, or requiring new data foundations and operating rhythms.
To reach this level, enterprises must operate differently. A Tier 1 relationship cannot be bought; it must be earned through openness and shared accountability. That begins with creating a single, transparent view of plans, data and performance.
Both parties must agree on how value will be measured and commit to revisiting that value together. Pricing must reflect business outcomes rather than technology inputs, with incentives tied to speed, impact and reuse. A portion of gains should be reinvested into future work.
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These shifts give enterprises and their providers the alignment and momentum needed to turn AI ambitions into sustained competitive advantage.
Enterprise leaders can get started building Tier 1 relationships within their enterprises by taking the following steps over the next 90 days:
Pick one strategic domain. Customer service containment, next-best-action in sales or predictive maintenance are common candidates with measurable value.
Name the Tier 1 partner. Select the partner based on domain fit, capability, reusable assets, data posture and willingness to work on value terms.
Write a two-page outcome charter. Define the business issue and outcome, target metric, economic model, data scope, guardrails and governance.
Launch a value sprint. Working with the Tier 1 provider, deliver a production pilot in 10 to 12 weeks with clear acceptance criteria.
Publish the score. Compare the baseline to actuals, release value to both parties and expand the scope.
AI rewards focus, speed and compounded learning. The Tier 1 model aligns incentives to deliver all three. Enterprise CIOs who lead this change will convert AI from scattered experiments into durable advantage. Those who do not will continue to spend more, wait longer and watch the gap widen.
Gartner
Mark P. McDonald is a distinguished vice president and fellow at Gartner. He is chief of research for Gartner’s high-tech practice, where he focuses on the impact of AI and other technologies on enterprise and provider business models.
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