This image illustrates the transformative potential of generative AI and its impact on business outcomes.
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As generative AI technology advances, traditional per-seat pricing models are becoming outdated. Companies need to consider outcome-based pricing, which better reflects the value and results of their AI products. This shift enables businesses to highlight the transformative impact of generative AI, driving greater investment and adoption in a competitive market. Marketers must evolve their narratives to emphasize the tangible benefits of these innovations, fostering a deeper understanding of customer needs.
The world of generative artificial intelligence (gen AI) is expanding at a rapid pace, and with that growth comes an urgent need to rethink how we price these cutting-edge products. Traditionally, many tech companies stick to a per-seat pricing model, but as the capabilities of gen AI evolve, it’s becoming clear that this approach is no longer the best fit for what these innovative solutions offer.
It’s hard to ignore the trend towards pricing software-as-a-service based on the capabilities and value it brings to customers. Despite this shift, many businesses still rely heavily on pricing models tied to the number of users, which simply doesn’t capture the true essence of what generative AI can do. Instead of just focusing on how many people are using the software, it’s time to talk about the specific outcomes the software delivers.
Generative AI is opening doors to possibilities we once thought impossible. The outcomes produced by these technologies are so significant that old pricing structures just can’t keep up. Consider this: what if a company invests in gen AI and it leads to transformative experiences, automating tasks and producing value that far exceeds the typical cost? In such cases, the traditional pricing models don’t quite illustrate the return on investment (ROI) businesses can expect.
With the tech world buzzing, venture capital investments are fueling innovations that are prompting companies to reconsider how they price their offerings. Some forward-thinking vendors are catching on and are starting to embrace pricing strategies that genuinely reflect the value these products deliver—outcomes that are becoming increasingly relevant and necessary for businesses in a competitive marketplace.
As we move further into the future, there’s a strong indication that pricing will transition away from those individual user seats and towards a more meaningful measurement: the results achieved with the technology. Signs of this change are already appearing, with some AI companies beginning to adopt consumption-based models. These models price services based on how much of the software is utilized—like charging based on tasks completed or credits consumed—paving the way for greater flexibility and fairness when it comes to cost.
The crucial point here is that the true value of generative AI lies in the outcomes it creates. This is similar to how we assess the power of quantum computing—not simply on the technology itself, but by examining the results it produces. When marketing these products, the key will shift to showcasing the concrete business value outcomes, rather than just highlighting the tools or methods involved.
To make this shift in pricing work, there’s a pressing need for tech companies to evolve their value propositions and narratives. Marketers should deepen their understanding of customer processes and focus more on conversations around what generative AI can actually deliver for their businesses. In this new landscape, being proficient in value assessments will become essential. Companies will need to effectively utilize value management tools to persuade potential buyers of the value offered.
Looking ahead, we might even see the emergence of “value agents” that can provide real-time reports on value outcomes, making it easier for businesses to assess the effectiveness of gen AI technologies. This could radically change how both customers and vendors view the value of technology, as calculations surrounding value will likely move from being speculative to being concrete.
As generative AI continues to automate tasks that once required human effort, discussions will shift toward the overall benefits these technologies provide to customers. What can a gen AI product really achieve for a business? That’s the pivotal question moving forward.
Lastly, upcoming events, such as the Gartner Tech Growth & Innovation Conference, will further explore how technology service providers can leverage emerging technologies—including generative AI—for growth and innovation. All in all, it’s a thrilling time for the tech industry as we venture into uncharted territories of value-based pricing models.
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