GenAI vs Traditional SaaS: Come for the Training, Stay for the Ongoing Support

In the rapidly-evolving software landscape, Generative AI (GenAI) is shaking up the traditional Software-as-a-Service (SaaS) model among enterprise applications. Taking Salesforce’s slowing revenue growth as the canary in the coalmine, SaaS premium pricing + shifting economic conditions and enterprise budgets + GenAI’s promise to do it faster and better = an enormous opportunity for disruption. 

Startups that can ride this wave will outpace incumbents stuck in their old ways or too large to make the pivot.

While SaaS has long dominated the industry with its streamlined workflows and efficiency, the advent of GenAI introduces a new paradigm—one where content creation, real-time insights, and intelligent automation are central. 

This shift suggests a future where customers may initially seek AI solutions for their human training capabilities, but remain loyal past the onboarding phase due to the platform’s continuous support as a workflow co-pilot. 

This is essentially the tech equivalent of an athlete being trained by the best coach, then bringing that coach onto the field with them to compete at their side—something that traditional SaaS cannot do.

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The Traditional SaaS Model: Workflow Efficiency

SaaS has long been the darling of the software world, streamlining tasks and boosting productivity. From Salesforce's CRM to project management tools like Asana and Trello, SaaS has played a critical role in helping businesses to scale efficiently and cost-effectively.

SaaS is great at organizing existing processes, but it doesn't inherently generate new insights. Take Workday, a leader in HR and financial SaaS: they're aces at tracking employee records and financial planning, but they don't tell managers how to run an effective offsite or boost team performance in the wake of a re-org.

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Enter GenAI: Content Creation on Steroids

GenAI flips the script. It's not just about managing workflows anymore; it's about creating content and driving decision-making in real-time. Its ability to create personalized content at a fraction of the cost—whether it’s generating marketing copy, writing code, or producing data-driven insights—sets it apart from traditional SaaS. In a world hungry for tailored experiences, the content-centric approach is pure gold.

Businesses aren't just looking for tools that help them manage workflows; they're seeking solutions that can produce the content needed to drive growth and differentiation.

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The Trojan Horse: Training as a Gateway to GenAI Adoption

So, how do you get your foot in the door with GenAI? Training. It's the perfect entry point, complementing existing tech stacks while laying the groundwork for future expansion.

Take Rising Team: They're using AI to help managers build better team dynamics, offering real-time recommendations based on best practices and team data. They get their foot in the door with their main value proposition of guiding managers to run their own interactive skill-building workshops or connection exercises, without the need of an external facilitator. 

The stickiness comes after, in the form of an LMS maintained and utilized by an AI leadership coach that knows the manager’s team and can give recommendations for how to deal with any in-the-moment issues that arise.

As a result, managers are supported and enabled by AI, which leads to more positive employee engagement scores with each successive Rising Team session, and to long-term increases in eNPS and retention rates.

Or look at Hyperbound, using AI buyers customized to target personas to train new sales reps to become effective SDRs. The guidance doesn’t stop once the rep is onboarded; Hyperbound’s product continues to provide feedback and suggestions during live cold, warm, discovery, and post-sales calls—and the model trains on the SDR’s own calls, making sure the training is tailored to each employee’s own strengths and weaknesses.

As a result, sales reps at all levels can receive extremely personalized training without burning prospect leads in the process.

These aren't just one-off training tools; they're dynamic, evolving AI buddies that stick around, offering personalized support long after the initial training is done. 

This kind of tool requires ongoing interaction to produce the best results; the combination of workflows and advice embedded in everyday contexts—the world-class coach in your ear while you’re on the field during the big game—is the special sauce that businesses will need to stay competitive.

Once businesses are equipped with the skills to use GenAI, they will quickly realize that the real benefit comes from this continuous support.

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The Future: From Workflows to Insights & Collaboration

As we barrel into an AI-dominated future, the focus is shifting from managing rigid workflows to learning with and from dynamic, content-driven experiences and insights for everyday decision making. 

As with anything, it’s worth mentioning the considerations that ought to come with inviting that coach onto the field with you:

• What data sharing policies are in place between the enterprise customer and the GenAI copilot provider to ensure that proprietary interactions and details stay private?
• How much has the GenAI provider mitigated the risk of bias in their model?
• What are the risks associated with becoming overly dependent on a single provider, both as a company and as an intuition- and experience-driven employee?
• AI is a fundamentally different form of intelligence than ours, and at the same time can lack contextual or industry-specific understandings in obvious ways; what strategies are in place to negotiate how employees approach and use such a tool?

The battle between GenAI and traditional SaaS is just heating up, and it's clear which side has the edge. It’s important not to lose sight of why we want AI to meet its potential: to allow humans to be more creative and intuitive. We can’t let AIs enormous helpfulness turn into a crutch; it should motivate us to play even harder.

Entrepreneurs looking for opportunities in this space should look at how to leverage the Trojan Horse aspect of training→ongoing support model for GenAI applications. The future isn't just about managing workflows—it's about creating insights on the fly, and the startups that master this will be the ones writing the next chapter of the software industry.