In today’s fast-evolving IT services landscape, managed service providers (MSPs) are at a crossroads where artificial intelligence (AI) is both a game-changer and a potential pitfall. With generative AI (genAI) driving unprecedented efficiencies in service delivery, MSPs have the chance to revolutionize how they operate—think faster resolutions, fewer errors, and streamlined operations. Yet, a hidden challenge looms large: many providers integrate AI without disclosing its role to clients, creating a trust gap that could unravel even the strongest partnerships. This lack of transparency, often dubbed “shadow AI gains,” means clients see better outcomes but remain unaware of the technology behind them, let alone how those gains are reflected in pricing. As clients grow savvier and more independent with their own AI tools, the pressure is on for MSPs to rethink their approach. Transparent AI pricing models aren’t just a nice-to-have—they’re becoming a critical lifeline to maintain relevance, build trust, and secure long-term profitability in a market that’s shifting beneath their feet. This discussion delves into why MSPs must act now to adapt, exploring the forces driving this urgency and the strategic steps needed to stay ahead.
The Rising Tide of Client Expectations
The adoption of AI in IT services has sparked a transformation in what clients expect from MSPs, and it’s happening at a breakneck pace. Businesses are waking up to the potential of AI to cut costs and boost outcomes, but they’re often left in the dark about how these improvements are achieved. When an MSP resolves issues faster or reduces errors using AI, clients notice the results without understanding the tech driving them. Worse, these “shadow gains” rarely translate into adjusted pricing or shared benefits, leaving clients feeling shortchanged. This opacity isn’t just a minor oversight—it’s a growing source of distrust that could fracture relationships if left unchecked. As more companies demand clarity on how AI shapes their services, MSPs face a stark choice: open up about their processes or risk alienating their client base with every undisclosed efficiency.
Moreover, clients aren’t sitting idle while MSPs navigate this shift. Many organizations are taking matters into their own hands, building in-house AI capabilities through dedicated centers of excellence. These internal tools allow them to automate routine tasks like incident triaging, slashing reliance on MSPs for low-value, effort-based work. This newfound independence flips the traditional dynamic, pushing MSPs to offer more strategic, high-impact services rather than transactional grunt work. Without transparent pricing that reflects AI’s role in driving value, MSPs risk being sidelined as clients question why they’re paying for services they could handle themselves. The message is clear: transparency isn’t just about ethics; it’s about survival in a landscape where clients are no longer passive recipients but active, empowered partners.
The Push Toward Outcome-Focused Pricing
Clinging to traditional pricing models like time-and-materials or fixed fees is becoming a losing battle for MSPs in an AI-driven era. These outdated structures, tied to effort rather than results, fail to account for the massive productivity boosts AI delivers. Instead, a shift to outcome-based pricing—models like transaction-based units or gain-share agreements—offers a way to align costs with the actual value provided. Imagine a scenario where an MSP charges based on resolved incidents rather than hours logged, directly reflecting AI’s efficiency. Such transparency not only bridges the trust gap but also positions MSPs as innovators, potentially unlocking new opportunities like cross-selling or early contract renewals. This pivot isn’t merely a trend; it’s a fundamental recalibration of how value is measured and communicated in IT services.
However, making this transition isn’t without hurdles. MSPs must first grapple with quantifying AI’s impact on their workflows, a task that demands rigorous tracking and clear metrics. Beyond that, they need to educate clients on why this shift benefits both sides, ensuring that pricing reflects shared gains rather than perceived exploitation. Gartner forecasts that by 2027, 60% of large IT services contracts will include “AI clawback clauses,” mandating providers to return a portion of efficiency gains to clients. This prediction underscores the urgency for MSPs to proactively adopt outcome-focused models before contractual obligations force their hand. Sticking to old-school pricing risks not only margin erosion but also losing the competitive edge to rivals who embrace transparency as a differentiator. The path forward demands boldness and clarity to redefine how value is priced and perceived.
Governance and Trust as Cornerstones of Success
Pricing isn’t the only area where MSPs need to evolve—AI governance is equally critical in this new landscape. Many providers dive headfirst into AI tools and partnerships, dazzled by the tech’s potential, but overlook the ethical and regulatory minefields. Clients are increasingly scrutinizing MSPs not just for technical prowess but for their ability to manage risks, ensure compliance, and safeguard data. Without robust governance frameworks—covering everything from usage logs to data lineage—AI innovations can quickly morph into liabilities. MSPs that neglect this aspect risk damaging their reputation, while those who prioritize it stand to gain a powerful asset: trust. As Gartner notes, trust is the “ultimate margin,” a currency that can outweigh even the slickest tech in securing client loyalty.
Building on this, transparency in AI deployment goes hand-in-hand with governance to cement that trust. Clients want assurance that AI is used responsibly, with clear accountability for its outputs and impacts. MSPs who openly disclose how AI operates within their services, while pairing it with strong risk management practices, can differentiate themselves in a crowded market. This approach isn’t just about avoiding pitfalls; it’s about turning governance into a strategic advantage. A provider that can demonstrate compliance with evolving regulations and ethical standards becomes a partner clients can rely on for more than just tech solutions. In contrast, ignoring these imperatives could lead to lost contracts or legal headaches, especially as scrutiny around AI intensifies. For MSPs, investing in governance isn’t a burden—it’s a gateway to deeper, more resilient client relationships.
Leveraging Key Moments for Contract Evolution
One often-overlooked opportunity for MSPs to address AI-driven changes lies in milestone events—those natural reset points in a client relationship. Think of moments like the successful rollout of a genAI pilot or a major platform go-live. These junctures offer a low-friction chance to renegotiate contracts, revisiting pricing, scope, and roles to reflect the realities of AI efficiencies. Yet, too many MSPs and procurement leaders let these windows slip by, missing out on aligning agreements with current needs. Failing to act at these pivotal times can perpetuate outdated terms that neither party finds satisfactory, sowing seeds of frustration. Proactively seizing these moments could redefine partnerships, ensuring they evolve with the tech landscape rather than lag behind.
Furthermore, using milestones for renegotiation isn’t just about fixing what’s broken—it’s about setting a forward-looking tone. MSPs can propose innovative pricing constructs or shared-savings models during these discussions, demonstrating a commitment to fairness and collaboration. This approach helps prevent abrupt rate shocks or disputes over undisclosed AI gains, fostering a dialogue where both sides feel heard. The inertia that often surrounds contract updates can be a silent killer of value, as outdated terms fail to capture the benefits AI brings to the table. By contrast, MSPs that treat milestones as strategic touchpoints can build momentum for long-term trust and alignment, turning potential friction into a foundation for stronger ties. The opportunity is there; it’s up to providers to act decisively when it counts most.
Charting a Path to Strategic Relevance
Ultimately, the stakes for MSPs extend far beyond pricing or governance—they’re about redefining their role in a competitive, AI-saturated market. Positioning as strategic partners rather than mere tactical vendors is the endgame, and transparency is the linchpin. By openly addressing AI’s role in service delivery, MSPs can lead the narrative with clients, preventing margin collapse and securing high-value engagements. This isn’t just about dodging risks like trust erosion or client independence; it’s about embracing a proactive stance that turns challenges into opportunities. As AI becomes a baseline expectation rather than a novelty, providers who adapt swiftly will shape the future of IT services, while those who hesitate may find themselves outpaced.
Looking back, the journey to this point revealed a landscape where MSPs grappled with balancing innovation against trust, often stumbling over opacity in AI gains. The solutions that emerged—outcome-based pricing, robust governance, and strategic use of contract milestones—offered a clear roadmap. Moving forward, the next steps involve deeper investments in reskilling teams for AI oversight roles and redesigning organizational focus toward domain expertise over rote tasks. MSPs should also explore joint reinvestment models with clients, turning efficiency savings into shared innovation funds. These actions, grounded in transparency, can transform yesterday’s challenges into tomorrow’s competitive strengths, ensuring MSPs remain indispensable in an ever-shifting industry.
