How to rethink SaaS go-to-market strategy for an agentic AI world

Winners in the agentic AI race will be determined by their commercial models as much as by their technology.

In brief

• The advancement of agentic AI makes the go-to-market strategy for SaaS companies more complex. Relying on old operating models won’t work.
• The buying proposition is evolving quickly, shifting decision-making from IT buyers to business functions like finance and customer service.
• Agentic AI pushes SaaS firms to shift from vendor to partner, co-investing with clients to develop tailored solutions that yield measurable results.

As agentic artificial intelligence (AI) continues to change the software as a service (SaaS) industry in fundamental ways, it’s essential for leaders to rethink, and in some cases, radically refocus, major components of their business model – including their go-to-market (GTM) strategy. Companies that adopt agentic AI at scale can transform, and in all likelihood, disrupt their operations, raising the bar for trust and experience from their software solution partners. New industry entrants with nothing to lose will have an advantage compared to the larger SaaS players trying to protect their per seat pricing models and installed base subscription revenues.

Here are five significant shifts that agentic AI is driving in the SaaS GTM motion:

1. Customers’ buying criteria are changing.

Before, most SaaS software was sold on capabilities and price. Today, customers want to see agentic AI in action – for example:

a.    How does the software handle designated tasks?
b.    How does it “learn” and adapt?
c.    What mistakes does it make, and what corrective procedures does it take?
d.    What guard rails are needed to make sure that AI agents are responsive and flexible without exposing the company to undue risk. While agentic AI solutions can be quick and easy to pilot, the security and privacy bar is higher in the near-term. Sales teams will need to clear the “do no harm” bar with their customers. Solution architects, formerly in support roles, will now have a bigger voice at the table to build confidence in the delivery of performance outcomes while managing risk.

2. The sales process is evolving.

The role that agentic AI plays in SaaS means that buyers are more likely to be business function leaders rather than IT professionals. These functions aren’t just looking for productivity tools; they are seeking solutions to execute significant portions of their operations hand in hand with their staff in ways that deliver a better customer experience more efficiently. As a result, the transactional buyer-seller relationship is dying; companies today expect to be partners with SaaS providers — using strategic co-creation to build customized AI agents that can drive outcomes. Leading companies will pilot those approaches at lighthouse accounts and rapidly build new blueprints for their sales methodology and sales tools based on their learnings.

3. Sellers’ capabilities must also evolve.

Because the sales process is changing, sellers must also change, moving from being conversant in their products to also advising on business operations in the customer’s environment and sector. It’s critical that they speak the language of the customer and be capable of communicating with specificity how AI can strengthen the client’s ability to manage daily operations and how it will impact their financials. SaaS software will no longer be an IT expense outside of the business function’s financial calculation; it will be a key component of their profit and loss. The most effective salespeople will be those that have mastered value-selling, from business function return on investment (ROI) to deal structures to outcome measurement.

4. Seller incentives are shifting.

The traditional SaaS incentive compensation structure of net-new annual contract value (ACV) is being upended as agentic AI pricing shifts from seat license fees to consumption- and results-based factors. Today, companies are evaluating various compensation models, including hybrid incentives based on a blend of ACV and consumption fees, or consumption-only incentives on strategic accounts with an option for shifting back to ACV depending on outcomes. Eventually, we are likely to see a tiered structure for both pricing and incentives where sellers are rewarded if consumption exceeds certain parameters.

5. The partner value exchange is being transformed.

The relationship between SaaS companies and their channel partners isn’t immune from these shifts. Consumption pricing and its reliance on delivery of outcomes — and the uncertain revenue streams it leads to — will inevitably force changes in how partners are compensated, placing more emphasis on performance-based measures. With agentic AI, SaaS companies will automate more of the configuration and deployment in their platforms. At the same time, partners will play a critical role in inter-platform integration and implementation of agent-to-agent protocols. It’s paramount that both the SaaS company and its partners share in the risk of successfully deploying AI agents to transform the customers’ operations. We see more strategic partnerships with shared risk-reward models and use of managed services as a natural step to enable these shifts.

Real-world shifts in SaaS GTM: built for an agentic AI world

Below are several case studies that demonstrate why and how agentic AI is truly transformative for the SaaS sector: