How SaaS companies can embrace the agentic AI future

As AI drives a market evolution, SaaS companies must reimagine business models that can drive significant reward but also increase risk.

In brief

• As SaaS companies are adding GenAI capabilities to their offerings, they can more directly and autonomously demonstrate customer value.
• The race to capitalize on this opportunity will increasingly require an evolution of pricing models that, in turn, will increase operational complexity.
• Successful software companies will use this opportunity to embrace a fundamentally different customer relationship — becoming partners rather than vendors.

Generative AI (GenAI) is transforming enterprise software. Thanks to artificial intelligence (AI), enterprise software solutions are being elevated beyond the invaluable tools on which enterprises run their businesses; they can now more directly — and autonomously — drive tangible value for customers, spanning the spectrum from copilots to fully autonomous agentic AI solutions.

The reward for software companies that get this product innovation right is a massive expansion in total addressable market (TAM). But to succeed, companies need to do more than just deliver product innovation; they must reimagine their relationships with customers, becoming more of a partner focused on service quality rather than a vendor.

More recently, the concept of a “seat” has been under pressure due to two major factors. First, seats haven’t been growing as corporate America has kept tighter cost controls. And second, customers have been looking to consolidate the number of SaaS vendors they utilize and scale back spending from 2021 through 2022 levels.

With those trends comes greater incentive to find a revenue model that better aligns customer and vendor interests. In fact, future success of AI-powered software will directly contribute to the erosion of the need for seats that SaaS providers historically relied on to expand and grow. 

SaaS transformation means moving to alternative pricing models and a more complex and hybrid pricing future

A flurry of recent GenAI product releases by software vendors has, so far, mostly been introduced as enhancements to existing products, largely packaged into, or as add-ons to, existing pricing and revenue models. As software companies continue to develop more agentic-like AI capabilities that can autonomously and directly deliver enhanced services and value to customers, both vendors and customers want to benefit. Aligning interests is vital, and alternate pricing models — including consumption-based models and in the case of more fully autonomous agentic AI-like capabilities, more outcome-based models — can better align interest among both vendors and customers.

While consumption-based models are already more common and understood, outcome-based models are still nascent. Identifying, quantifying and agreeing on the value or outcome created by more agentic and autonomous software can be complex. For example, software that can take on or augment the work of human agents will drive different levels of value depending on the use case (e.g., a credit lending originator vs. an IT help desk). That value can be in the form of requiring fewer human agents, resolving issues on a more consistent and/or timely basis, increasing sales volumes by suggesting better product alternatives or reducing customer churn. 

Agreeing on the unit of “outcome” and defining its successful resolution also adds challenges. Data, processes and systems likely need to be revamped to accurately track and report outcomes. Given the complexity of the above examples, it may be simpler and quicker to price on a consumption basis, such as per call to a contact center, rather than on successful outcomes. 

As the number of agents in use by a customer proliferates and becomes more autonomous, the agents will need to be orchestrated to increasingly interact with each other, often spanning agents from different software vendors — further adding pricing and operational complexity. 

Software companies therefore face a more complex future as pricing shifts from the traditional seat basis and enterprise license agreement (ELA) to a hybrid of seat, ELA consumption and outcome models. SaaS vendors will benefit from adopting more of a partnership mindset, with a focus on identifying pricing structures that work best for both the customer and the company.

How can SaaS companies effectively design a new business model to drive enterprise value? 

Successfully rising to this challenge will likely affect the way almost every part of the software enterprise operates. Numerous and important decisions that will rely on the answers to the following questions will have to be navigated:

• How should you price new offerings? How should they coexist with existing SaaS/seat-based and ELA pricing arrangements already in place?
• How do you successfully define, align and measure “outcome” or “consumption”? What’s the right balance of standardization vs. customization of terms? What’s the right trade-off between the complexity added by pricing outcome vs. more simply pricing on consumption (i.e., queries resolved vs. queries answered)? And can costs differ by outcome delivered depending on the customer type?
• Does a sale and subsequent success now require a broader set of stakeholders within the client organization? How do you best develop these relationships?
• How should you pivot the way sales teams are organized and incentivized?
• How should the customer success team be reimagined in a more outcomes-dependent relationship?
• What would you need to alter in underlying telemetry, IT and billing systems to support such revenue models?
• What new or augmented key performance indicators need to be tracked and financially reported?
• How do you financially plan a more variable revenue stream and successfully guide investors through this change?
• What are the tax consequences when selling through or delivering more services via an agentic platform?

Creating value is key

During the last major platform shift to the cloud and SaaS models, success depended on embracing change and guiding investors, while those that hesitated fell behind. Today, companies that stick with traditional subscription models risk losing to competitors that better align price to value received by software consumers.

Moving to a hybrid offering that includes traditional SaaS pricing and consumption- and outcome-based models requires not only the right product but also operational agility. As before, this is a critical moment where fortunes can quickly turn. Incumbents must be willing to disrupt themselves thoughtfully and quickly — or risk losing share.

As SaaS companies look for a new equation that can help increase sales, revenue and value in an AI-driven marketplace, they will need to adopt a more collaborative approach — both internally and with customers — to make sure their strategies, offerings and metrics align to deliver value and improve customer performance.

Nina Lapachet, EY-Parthenon, also contributed to this article.