What is outcome as agentic solution (OaAS)?

AI adoption continues to reshape enterprise priorities and investment strategies, with Gartner predicting that 40% of enterprise apps will feature task-specific AI agents in 2026, up from less than five percent in 2025.

The analyst firm predicts that a new paradigm it’s named outcome as agentic solution (OaAS) will make some of the biggest waves, by replacing software as a service (SaaS). The new model will see enterprises contract for outcomes, instead of simply buying access to software tools.

Instead of SaaS, where the customer is responsible for purchasing a tool and using it to achieve results, with OaAS providers embed AI agents and orchestration so the work is performed for you. This leaves the vendor responsible for automating decisions and delivering outcomes, says Vuk Janosevic, senior director analyst at Gartner.

“OaAS shifts enterprise value from tool access or services contracted to guaranteed execution, blending software, services and AI agents into outcome-based delivery,” he says.

Take, as a practical example, invoice processing. Instead of licensing software, an OaAS provider will deploy AI agents to reconcile accounts payment and close the books, with the customer measuring success only by delivered outcomes such as invoices processed, reconciliations completed or months closed.

The evolution from tools to outcomes

The ‘outcome scenario’ has been developing in the market for several years, first through managed services then value-based delivery models. “OaAS simply formalizes it with modern IT buyers, who want results over tools,” notes Thomas Kraus, global head of AI at Onix.

OaAS providers are effectively transforming systems of record (SoR) into systems of action (SoA) by introducing orchestration control planes that bind execution directly to outcomes, says Janosevic. The struggles many enterprises face with agentic AI adoption, such as fragmented data, siloed apps and the absence of an assurance layer explain why they fail to scale. OaAS addresses this by delivering verticalized blueprints and governed execution, making outcomes auditable and dependable.

“Strategically, this marks a redefinition of enterprise software: not as a toolkit, but as an operating fabric where value is proven in execution, not just promised in capability,” he explains.

OaAS may be fundamentally redefining what software is and what customers can expect from it, but it’s still very early days for the technology, as few enterprises have operationalized OaAS at scale yet.

“We’re seeing early signs that agentic service models could reshape how value is delivered across IT services, but it’s essential to recognize that the terminology and frameworks are still evolving,” points out Lars Goransson, vice president of Research, Worldwide Services at IDC. “Much of the current discourse is exploratory, and clarity around definitions, governance and implementation models will be essential for broader adoption.”

Several factors are driving interest however, including time-to-value and closing the transactional value gap in AI adoption, where the use of AI doesn’t always translate into business results. This is something that can be achieved with OaAS while improving capital efficiency and reducing risk by shifting execution accountability to vendors, says Janosevic.

He adds that OaAS simplifies operations and enhances customer and employee experiences through fewer errors and faster service, “giving early adopters a competitive edge in markets undergoing rapid digital transformation”.

Which industries will benefit most?

While industries with high operational complexity – such as healthcare, logistics, and financial services – do face elevated risks due to regulatory scrutiny and intricate workflows, they also stand to gain the most from agentic service models when implemented thoughtfully, notes Goransson.

“These sectors often operate at scale, with well-defined governance structures and mature compliance frameworks that can support the oversight required for autonomous service delivery,” he says. “Moreover, larger organizations typically have the resources to invest in robust data infrastructure, AI readiness, and cross-functional alignment – critical enablers for agentic capabilities.”

That said, smaller firms with modern, cloud-native tech stacks may benefit from faster deployment cycles and greater agility, he notes. “Ultimately, the ability to capitalize on agentic models hinges less on size or sector and more on an organization’s maturity across technology, governance, and strategic alignment.”

Shared risk, shifting responsibility

Goransson, however, advises enterprises carefully evaluate several areas of risk before adopting an agentic service model, Accountability is paramount, he notes, as without clear ownership structures and performance metrics, organizations may struggle to assess whether outcomes are being delivered as intended.

Transparency in how agentic systems make decisions is equally critical, he adds, especially when those decisions impact customer experience or regulatory compliance. “Governance frameworks must evolve to oversee autonomous processes, ensuring they align with corporate policies, ethical standards, and legal obligations. Additionally, security becomes a central concern: agentic systems often operate across multiple data environments and decision layers, which can introduce new vulnerabilities if not properly managed. Enterprises must ensure robust controls are in place to safeguard sensitive data and prevent unintended actions or breaches.”

Usman Ikhlaw, programme manager for AI at techUK, says CIOs now have an increasingly pivotal role to play.

“They’re becoming the architects of the future workforce. By leading the charge in process reinvention, prioritizing governance and investing in new roles like agent orchestrators, they’re laying the groundwork for a more efficient, agile and strategically focused enterprise.”

Strategic urgency

Gartner predicts that vertical adoption of OaAS will continue but that broader mainstream adoption will take place after 2028, once enterprises standardize OaAS contracts and orchestration frameworks.

But whatever CIOs thoughts on OaAS and agentic AI adoption are right now, Gartner strongly recommends that CIOs define their overall agentic AI strategy in the next three to six months, as the industry is at an inflection point. Those organizations that delay adoption will spend more to operate the same workflows, says Janosevic, eroding capital efficiency and leaving fewer resources to innovate on core products and services.

“Over time, this compounds into lost market share and profit, particularly in attracting and retaining talent. Early adopters will be able to translate capital efficiency into reinvestment, innovation and talent advantage, creating a competitive gap that late movers will find nearly impossible to close.”