What Happens when the Product is no Longer the Product?
What Happens when the Product is no Longer the Product?
What Happens when the Product is no Longer the Product?
In an outcome-based economy, what does it actually mean to sell software? In a speech at Planhat Open 2026, our CEO, Kaveh Rostampor, explored the results of our customer survey and unpacked what the shift to outcome-based models means for commercial teams.
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After nearly two decades in B2B SaaS, the fundamental change I’m seeing now is that the product is no longer the product.
There’s a lot of noise out there about what’s happening in enterprise companies and across the commercial world in general. A lot of it is about AI—how it’s here to change the world, and how commercial teams are trying to address this with their customers and their own businesses.
Have a think about what business leaders have been saying in the last year:
At Anthropic, Dario Amodei warned that AI could eliminate half of all entry-level white-collar jobs and spike unemployment to 10-20% within one to five years. At almost exactly the same time, NVIDIA's Jensen Huang took the opposite line: “You're not going to lose your job to AI. You're going to lose your job to someone who uses AI.”
Anton Osika, Lovable’s CEO, suggested that rather than buying separate tools for CRM, project tracking, or inventory management, you can now simply build whatever you need on demand. A few months later, Box’s CEO Aaron Levie pushed back: “You're not going to vibe-code an ERP system. I don't think you're going to vibe-code a CRM system. The risk is simply too high.”
Klarna's Sebastian Siemiatkowski told Bloomberg his company would shrink by around 20% a year through natural attrition, and freezed hiring. Not long after, he walked it back, conceding that Klarna had overestimated what AI could do and underappreciated the human side of service. And began rehiring people.
Then SAP's Christian Klein argued that AI agents won't replace enterprise software—rather, they depend on it, and on the business context only a system like SAP holds. Forrester countered with a report championing the claim that SaaS as we know it is dead.
After nearly two decades in B2B SaaS, the fundamental change I’m seeing now is that the product is no longer the product.
There’s a lot of noise out there about what’s happening in enterprise companies and across the commercial world in general. A lot of it is about AI—how it’s here to change the world, and how commercial teams are trying to address this with their customers and their own businesses.
Have a think about what business leaders have been saying in the last year:
At Anthropic, Dario Amodei warned that AI could eliminate half of all entry-level white-collar jobs and spike unemployment to 10-20% within one to five years. At almost exactly the same time, NVIDIA's Jensen Huang took the opposite line: “You're not going to lose your job to AI. You're going to lose your job to someone who uses AI.”
Anton Osika, Lovable’s CEO, suggested that rather than buying separate tools for CRM, project tracking, or inventory management, you can now simply build whatever you need on demand. A few months later, Box’s CEO Aaron Levie pushed back: “You're not going to vibe-code an ERP system. I don't think you're going to vibe-code a CRM system. The risk is simply too high.”
Klarna's Sebastian Siemiatkowski told Bloomberg his company would shrink by around 20% a year through natural attrition, and freezed hiring. Not long after, he walked it back, conceding that Klarna had overestimated what AI could do and underappreciated the human side of service. And began rehiring people.
Then SAP's Christian Klein argued that AI agents won't replace enterprise software—rather, they depend on it, and on the business context only a system like SAP holds. Forrester countered with a report championing the claim that SaaS as we know it is dead.
What our customers are actually experiencing
Moving past these contradictory positions, I think it’s valuable to ground this discussion in what our customers are actually experiencing. Since we work with close to a thousand B2B enterprises globally, we recently ran a round of market research to better understand the reality of the current situation.
One of the survey questions was: “How has your company retention changed in the last twelve months?” If the AI alarmists are right, we’d expect retention to drop off a cliff, with customers cancelling contracts in favour of building rather than buying.
“The people seeing significant usage from AI tooling are actually the least worried about headcount reductions, which is telling. ”
What our customers are actually experiencing
Moving past these contradictory positions, I think it’s valuable to ground this discussion in what our customers are actually experiencing. Since we work with close to a thousand B2B enterprises globally, we recently ran a round of market research to better understand the reality of the current situation.
One of the survey questions was: “How has your company retention changed in the last twelve months?” If the AI alarmists are right, we’d expect retention to drop off a cliff, with customers cancelling contracts in favour of building rather than buying.
“The people seeing significant usage from AI tooling are actually the least worried about headcount reductions, which is telling. ”
What our customers are actually experiencing
Moving past these contradictory positions, I think it’s valuable to ground this discussion in what our customers are actually experiencing. Since we work with close to a thousand B2B enterprises globally, we recently ran a round of market research to better understand the reality of the current situation.
One of the survey questions was: “How has your company retention changed in the last twelve months?” If the AI alarmists are right, we’d expect retention to drop off a cliff, with customers cancelling contracts in favour of building rather than buying.
“The people seeing significant usage from AI tooling are actually the least worried about headcount reductions, which is telling. ”
Interestingly, 32% of companies reported improvements in their NRR and gross retention. Another 28% reported no significant change. So roughly 60% of those surveyed didn’t see any decline in gross or net revenue retention. Clearly the state of things is not as alarming as some people suggest.
On the question: “Are you currently using AI in your post-sales processes, and how would you describe its impact?” 52% said they see very limited or no effect, and 48% said they see moderate to significant effect. Cross-referencing with another question about who is most worried about job cuts in post-sales and customer success, the people seeing significant usage from AI tooling are actually the least worried about headcount reductions, which is telling.
I was recently at a conference with Francisco Partners, a private equity firm. As you might expect, there was a lot of talk about AI. You might be familiar with this dynamic: your company is owned by someone, there's a board meeting, there's a lot of talk about AI, the CEO comes back and says, “let’s do more with AI”, but exactly what you're supposed to do is a bit unclear.
More and more of the executives I speak to mention getting these marching orders to create value using AI, but what exactly they need to do remains vague. So here are three things I believe we know are happening.
Interestingly, 32% of companies reported improvements in their NRR and gross retention. Another 28% reported no significant change. So roughly 60% of those surveyed didn’t see any decline in gross or net revenue retention. Clearly the state of things is not as alarming as some people suggest.
On the question: “Are you currently using AI in your post-sales processes, and how would you describe its impact?” 52% said they see very limited or no effect, and 48% said they see moderate to significant effect. Cross-referencing with another question about who is most worried about job cuts in post-sales and customer success, the people seeing significant usage from AI tooling are actually the least worried about headcount reductions, which is telling.
I was recently at a conference with Francisco Partners, a private equity firm. As you might expect, there was a lot of talk about AI. You might be familiar with this dynamic: your company is owned by someone, there's a board meeting, there's a lot of talk about AI, the CEO comes back and says, “let’s do more with AI”, but exactly what you're supposed to do is a bit unclear.
More and more of the executives I speak to mention getting these marching orders to create value using AI, but what exactly they need to do remains vague. So here are three things I believe we know are happening.
One: The outcome based economy
The first comes from Dave Schneider, who was president at ServiceNow, worked with Frank Slootman for many years, and is now an investor. He says companies will always buy for the same three reasons: they want to make money; they want to save money; or they want to stay off the front page of the newspaper. If you sell one or more of those things, you will be fine.
When we ask our customers about their goals, very similar themes come up: improving net revenue retention, driving adoption, scaled customer success, and so on. Scaling post-sales is big right now—and this is about saving money and delivering better experiences through digital channels.
“This outcome-based economy is what everything is pointing towards.”
One: The outcome based economy
The first comes from Dave Schneider, who was president at ServiceNow, worked with Frank Slootman for many years, and is now an investor. He says companies will always buy for the same three reasons: they want to make money; they want to save money; or they want to stay off the front page of the newspaper. If you sell one or more of those things, you will be fine.
When we ask our customers about their goals, very similar themes come up: improving net revenue retention, driving adoption, scaled customer success, and so on. Scaling post-sales is big right now—and this is about saving money and delivering better experiences through digital channels.
“This outcome-based economy is what everything is pointing towards.”
One: The outcome based economy
The first comes from Dave Schneider, who was president at ServiceNow, worked with Frank Slootman for many years, and is now an investor. He says companies will always buy for the same three reasons: they want to make money; they want to save money; or they want to stay off the front page of the newspaper. If you sell one or more of those things, you will be fine.
When we ask our customers about their goals, very similar themes come up: improving net revenue retention, driving adoption, scaled customer success, and so on. Scaling post-sales is big right now—and this is about saving money and delivering better experiences through digital channels.
“This outcome-based economy is what everything is pointing towards.”
Now, the way in which these goals are delivered is continuously changing. If you were a coffee farmer a hundred years ago, you made your coffee, shipped it to a merchant, who sold it to an end consumer. Then the next generation didn't care about that—they went to their local coffee shop and bought coffee as a service. And now things are shifting towards outcomes: “I don't care about any of that. I just want to be caffeinated.”
This outcome-based economy is what everything is pointing towards. When it comes to B2B business systems, the first generation put a bunch of data about businesses into databases—ERP systems that streamlined and drove efficiency. Then the cloud came, businesses digitalized further, and revenue systems like Salesforce became central to go-to-market teams, focused on transacting as fast as possible. Our belief is that the next generation of systems will be outcome-based—“I don't care about the product or the software. I just want the outcome your company is promising me.” And business models are changing accordingly, from perpetual to subscription to credits, consumption, or however the outcome looks like.
We asked our customers: “Should companies sell products or outcomes?” and 90% percent think companies should sell outcomes, up from last year’s already resounding 83%.
Now, the way in which these goals are delivered is continuously changing. If you were a coffee farmer a hundred years ago, you made your coffee, shipped it to a merchant, who sold it to an end consumer. Then the next generation didn't care about that—they went to their local coffee shop and bought coffee as a service. And now things are shifting towards outcomes: “I don't care about any of that. I just want to be caffeinated.”
This outcome-based economy is what everything is pointing towards. When it comes to B2B business systems, the first generation put a bunch of data about businesses into databases—ERP systems that streamlined and drove efficiency. Then the cloud came, businesses digitalized further, and revenue systems like Salesforce became central to go-to-market teams, focused on transacting as fast as possible. Our belief is that the next generation of systems will be outcome-based—“I don't care about the product or the software. I just want the outcome your company is promising me.” And business models are changing accordingly, from perpetual to subscription to credits, consumption, or however the outcome looks like.
We asked our customers: “Should companies sell products or outcomes?” and 90% percent think companies should sell outcomes, up from last year’s already resounding 83%.
Two: Going beyond the product
The second thing is that the product is no longer the product. In an outcome-based economy, you need to deliver outcomes through services. OpenAI launched what they call a “deployment company” and somehow raised another four billion dollars around it. Anthropic is doing something similar. These moves revolve around the same idea as my first point—selling the technology alone isn't enough because people care about the outcome, so you need a team who goes in, understands the business, and helps use the technology to drive those outcomes. We also launched our AI Deployment Program early last year and have been working with customers on exactly this.
Two: Going beyond the product
The second thing is that the product is no longer the product. In an outcome-based economy, you need to deliver outcomes through services. OpenAI launched what they call a “deployment company” and somehow raised another four billion dollars around it. Anthropic is doing something similar. These moves revolve around the same idea as my first point—selling the technology alone isn't enough because people care about the outcome, so you need a team who goes in, understands the business, and helps use the technology to drive those outcomes. We also launched our AI Deployment Program early last year and have been working with customers on exactly this.
Three: The speed of commercial work
The third thing is that AI is making commercial work faster and cheaper. The majority of work in businesses today is still led by humans, but in ten or twenty years, most of that work will be automated. Those automations can be deterministic—the kind B2B has typically wanted and needed—or fully agentic, or a combination of both. We think this direction is very clear.
As part of our research, we asked our customers what AI workflows they're using. The most common were: call recording and meeting summaries, customer data summarization, customer research, and sentiment analysis. As for their impact: 43% say they're using these flows but the impact is limited and 31% report moderate impact. Only 16% are seeing significant impact—which we defined as a significant attributable lift in revenue or productivity. There is clearly room for improvement.
On how post-sales teams will evolve by end of year: 36% think teams will be more high-touch and strategic as a result of Agentic work and 30% say they will simply be able to deliver effective low-touch at a much greater scale. The interesting thing here is that the people who are adopting AI to become more strategic report struggling more with gross and net retention, while the people focused on automating their processes tend to do better results-wise. It’s hard to draw a robust conclusion from this without probing deeper, but the connection is worth reflecting on.
Closing Thoughts
So where does this leave commercial leaders? In some ways, back where we started: the product is simply no longer the product.
Companies still buy for the same three reasons—to make money, to save money, and to stay off the news—and in an outcome-based economy, the only thing that matters is whether you can connect what you deliver to those outcomes. If you cannot articulate how your product moves your customer's revenue, it will inevitably be questioned sooner or later.
All this is to say that the teams that thrive over the next few years will not be the ones with the most AI—they will be the ones who know exactly what outcome they are being paid to deliver.
Three: The speed of commercial work
The third thing is that AI is making commercial work faster and cheaper. The majority of work in businesses today is still led by humans, but in ten or twenty years, most of that work will be automated. Those automations can be deterministic—the kind B2B has typically wanted and needed—or fully agentic, or a combination of both. We think this direction is very clear.
As part of our research, we asked our customers what AI workflows they're using. The most common were: call recording and meeting summaries, customer data summarization, customer research, and sentiment analysis. As for their impact: 43% say they're using these flows but the impact is limited and 31% report moderate impact. Only 16% are seeing significant impact—which we defined as a significant attributable lift in revenue or productivity. There is clearly room for improvement.
On how post-sales teams will evolve by end of year: 36% think teams will be more high-touch and strategic as a result of Agentic work and 30% say they will simply be able to deliver effective low-touch at a much greater scale. The interesting thing here is that the people who are adopting AI to become more strategic report struggling more with gross and net retention, while the people focused on automating their processes tend to do better results-wise. It’s hard to draw a robust conclusion from this without probing deeper, but the connection is worth reflecting on.
Closing Thoughts
So where does this leave commercial leaders? In some ways, back where we started: the product is simply no longer the product.
Companies still buy for the same three reasons—to make money, to save money, and to stay off the news—and in an outcome-based economy, the only thing that matters is whether you can connect what you deliver to those outcomes. If you cannot articulate how your product moves your customer's revenue, it will inevitably be questioned sooner or later.
All this is to say that the teams that thrive over the next few years will not be the ones with the most AI—they will be the ones who know exactly what outcome they are being paid to deliver.
Kaveh Rostampor
CEO & Co-Founder
Planhat
Kaveh Rostampor is the CEO and Co-founder of Planhat, where he leads the company’s mission to help organizations automate commercial operations. Since founding Planhat, he has guided its evolution from a Swedish startup into a global software company serving customers across software, healthcare, security, financial services, and IT services. With nearly two decades of experience building and scaling software companies, Kaveh is passionate about the future of enterprise software and how humans and AI will work together to run more intelligent, efficient businesses. He also serves as an advisor and board member to growth-stage technology companies.
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