The 10% Trap: Why Your AI 'Efficiencies' Are Blinding You to the Real Disruption
Are you feeling anxious about AI? Last year, many marketing leaders were. There was a palpable panic that AI would make our jobs obsolete.
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The 10% Trap: Why Your AI 'Efficiencies' Are Blinding You to the Real Disruption
Are you playing the long game or still under pressure to "generate leads"?
If you relate to the latter, we feel you! Old habits die hard and form fills are still a key metric at a lot of companies. But with the advancements in technology and AI, listening to and building a relationship with your buying groups through marketing is well within reach. Need help making the shift? We're here to help.
Are you feeling anxious about AI? Last year, many marketing leaders were. There was a palpable panic that AI would make our jobs obsolete.
But as Inverta's AI Practice Lead, Brian Schmidt, learned at this year's Marketing AI Conference (MAICON), that panic has subsided. It’s been replaced by a new, more dangerous feeling: complacency.
Many teams are stuck in the "10% trap." They're using AI for optimization—small, short-term efficiency gains. They're automating workflows or running A/B tests that might get a 10% lift. This is fine, but it’s a distraction.
The real power of AI isn't optimization. It's innovation. It’s the ability to do things you could not do before, unlocking 10x gains, not 10%. And this innovation is about to completely upend the B2B buying process. If you're only focused on 10% efficiencies, you won't see the disruption coming until it's too late.
Ditch optimization, focus on innovation
The shift from optimization to innovation is the single biggest takeaway from this year's conference.
- Optimization is using AI to do the same things a little faster or a little better. It’s automating an existing workflow or finding a small lift.
- Innovation is using AI to do entirely new things. It's freeing up your team's time not just for efficiency's sake, but to use that new time to tackle transformative projects.
The optimization mindset is a dead end. The innovation mindset is where you'll find true strategic value.
Use AI as your strategic thought partner
AI can't fix a broken go-to-market strategy. But it can act as a powerful "thought partner" to make your strategy smarter.
For the last decade, B2B marketing has been stuck in a "promotional factory". We take a piece of content, send an email, and make an ad, over and over. We’ve become buried in campaign performance metrics—email opens, funnel stages—and lost the plot.
This is where AI innovation can break the cycle. Instead of just optimizing the factory, use AI to return to research-first marketing. Use its reasoning models to:
- Analyze macro trends influencing your audience that you lack the budget to research.
- Identify potential markets or segments you're not addressing.
- Help you think through what’s possible based on your business inputs, goals, and performance data.
[Pull quote, attributed: "No business is gonna fold because your emails are underperforming a little bit... a business will fold if your entire product is now obsolete or a disruptor has come along and tanked it." - Brian Schmidt, AI Practice Lead, Inverta]
Reacting to these macro-level, existential threats—not optimizing an email open rate—is the strategic work marketers must reclaim.
Stop chasing the 'new tool' high
One of the biggest mistakes holding teams back is "new tool obsession". It’s easy to get excited about a shiny new tool that promises a 10% boost in outreach.
But this is backward. AI is still just a tool. You must always start with the problem you are trying to solve.
- What is my role?
- What am I trying to accomplish?
- What is my process, and what systems are involved?
- Is this a people problem, a process problem, or a tool problem?
Only after answering these questions can you look for a solution.
And here’s the new reality: it has become much easier to solve these problems in-house. Tools like ChatGPT or Claude can literally help you code and produce your own solution. All it takes is someone with a good idea. You no longer need a highly technical coding skillset to prototype and build a fix.
This "AI-native" mentality—build it myself first, then look to buy—will save you from a bloated tech stack full of tools that may not exist in two years as platforms consolidate them.
Recognize the real bottleneck is enablement, not technology
Many enterprise leaders are paralyzed. They run a pilot, it works well, and then... nothing.
A recent MIT paper noted that 95% of AI pilots at large enterprises don't progress. Many took this as a sign that AI hype is outpacing reality.
That is the wrong conclusion.
This isn't an AI failure; it's an enterprise failure. Big companies are terrible at enablement. It's a miracle that 5% of pilots did progress at a Fortune 100 company. You can't roll out an enterprise tool and assess its impact on hiring practices in just six months—it's an insane metric.
[Pull quote, attributed: "Every business ever is terrible... at enablement. And until we start treating this as someone's dedicated full-time responsibility... to not just manage the tools, but identify the use cases and roll them out and enable your team, you're not gonna see the adoption." - Brian Schmidt, AI Practice Lead, Inverta]
The problem isn't the technology. It's the lack of internal capacity, space, and dedicated ownership to move from a successful pilot to a fully adopted workflow.
Prepare for the real disruption: AI buying agents
If tool obsession and enablement are the current hurdles, the existential threat is what comes next: AI buying agents.
This is the single biggest thing to pay attention to.
Right now, we're seeing SEO traffic drop as humans use AI overviews or chatbots for research instead of clicking links. That's just the start.
Imagine this scenario 18 to 24 months from now:
- An AI agent at your target account is monitoring their business performance data.
- It proactively identifies a problem—for example, "performance within this key audience segment is underperforming in terms of revenue."
- It then consults other specialized agents to determine the best go-to-market strategy for that problem (e.g., a one-to-few ABM campaign).
- It then goes out and researches the best three ABM firms in the country, pulling their pricing, case studies, and everything else it needs to make a decision.
- It presents this fully vetted short list to the human decision-maker... before that human even knew they had a problem.
What happens if you're not on that list? You're done. You are sunk before you even knew a deal existed.
What happens when an agent, not a human, writes your RFP?
This new reality fundamentally breaks the current GTM motion.
- What role do SDRs play when an agent books the demo?
- What role do email nurtures play when the buyer is already 90% of the way to a decision?
- What happens to the "MQL Industrial Complex" when the "lead" is a piece of software?
This agent-led world forces a radical, uncomfortable honesty. You must ask yourself: Am I putting everything out there that a buyer—or an agent—needs to make a decision?
The answer for almost everyone is no.
We gatekeep our most valuable content. We hide our pricing. We force buyers through a short-term, promotional, MQL-focused loop that chases quarterly numbers at the expense of long-term profitability and customer fit.
Win by enabling the buyer (and the agent)
The solution isn't a new AI tool. It's a return to first principles, amplified by technology. It's buyer enablement.
Your entire job is to provide value to the buyer. You must make it as transparent and simple as possible for them to make a decision.
This means:
- Stop gatekeeping: Put your best content, case studies, and insights out in the open.
- Publish your pricing: People say pricing pages don't convert. Who cares? That's not what they're for. They're for being valuable and informative to your buyer.
- Be visible everywhere: Your content can't just live on your website. It needs to be in all the places an agent will go looking.
The companies that do this well—that make their value clear, easy to find, and easy to understand—are the ones that will be well-positioned to win.
How to staff for an AI-native future
This agent-based world isn't here tomorrow, but it will be in the next 18-24 months. You need to start preparing your content now, and you need to start preparing your team.
When staffing for this future, don't just look for technical skills. A strong coding background isn't necessary, especially as AI tools get better at building workflows for you.
Instead, hire for:
- Curiosity: This is a massively undervalued trait. You need people who know how to ask "why" something happened, not just describe what happened.
- Critical Thinking: You need people who can see a problem, understand its components, and form a hypothesis about how to solve it.
- Data Structure: The single most critical piece is the data layer. You need people who understand how information must be structured, tagged, and described so that AI systems can access and leverage it.
The businesses that have their data structured in a clear, accessible way will have a tremendous advantage. The future of marketing is a blend of creative, curious people who understand the structure of information.
The time to prepare is now.
About the author
Service page feature
The RevRoom podcast
Are you feeling anxious about AI? Last year, many marketing leaders were. There was a palpable panic that AI would make our jobs obsolete.
But as Inverta's AI Practice Lead, Brian Schmidt, learned at this year's Marketing AI Conference (MAICON), that panic has subsided. It’s been replaced by a new, more dangerous feeling: complacency.
Many teams are stuck in the "10% trap." They're using AI for optimization—small, short-term efficiency gains. They're automating workflows or running A/B tests that might get a 10% lift. This is fine, but it’s a distraction.
The real power of AI isn't optimization. It's innovation. It’s the ability to do things you could not do before, unlocking 10x gains, not 10%. And this innovation is about to completely upend the B2B buying process. If you're only focused on 10% efficiencies, you won't see the disruption coming until it's too late.
Ditch optimization, focus on innovation
The shift from optimization to innovation is the single biggest takeaway from this year's conference.
- Optimization is using AI to do the same things a little faster or a little better. It’s automating an existing workflow or finding a small lift.
- Innovation is using AI to do entirely new things. It's freeing up your team's time not just for efficiency's sake, but to use that new time to tackle transformative projects.
The optimization mindset is a dead end. The innovation mindset is where you'll find true strategic value.
Use AI as your strategic thought partner
AI can't fix a broken go-to-market strategy. But it can act as a powerful "thought partner" to make your strategy smarter.
For the last decade, B2B marketing has been stuck in a "promotional factory". We take a piece of content, send an email, and make an ad, over and over. We’ve become buried in campaign performance metrics—email opens, funnel stages—and lost the plot.
This is where AI innovation can break the cycle. Instead of just optimizing the factory, use AI to return to research-first marketing. Use its reasoning models to:
- Analyze macro trends influencing your audience that you lack the budget to research.
- Identify potential markets or segments you're not addressing.
- Help you think through what’s possible based on your business inputs, goals, and performance data.
[Pull quote, attributed: "No business is gonna fold because your emails are underperforming a little bit... a business will fold if your entire product is now obsolete or a disruptor has come along and tanked it." - Brian Schmidt, AI Practice Lead, Inverta]
Reacting to these macro-level, existential threats—not optimizing an email open rate—is the strategic work marketers must reclaim.
Stop chasing the 'new tool' high
One of the biggest mistakes holding teams back is "new tool obsession". It’s easy to get excited about a shiny new tool that promises a 10% boost in outreach.
But this is backward. AI is still just a tool. You must always start with the problem you are trying to solve.
- What is my role?
- What am I trying to accomplish?
- What is my process, and what systems are involved?
- Is this a people problem, a process problem, or a tool problem?
Only after answering these questions can you look for a solution.
And here’s the new reality: it has become much easier to solve these problems in-house. Tools like ChatGPT or Claude can literally help you code and produce your own solution. All it takes is someone with a good idea. You no longer need a highly technical coding skillset to prototype and build a fix.
This "AI-native" mentality—build it myself first, then look to buy—will save you from a bloated tech stack full of tools that may not exist in two years as platforms consolidate them.
Recognize the real bottleneck is enablement, not technology
Many enterprise leaders are paralyzed. They run a pilot, it works well, and then... nothing.
A recent MIT paper noted that 95% of AI pilots at large enterprises don't progress. Many took this as a sign that AI hype is outpacing reality.
That is the wrong conclusion.
This isn't an AI failure; it's an enterprise failure. Big companies are terrible at enablement. It's a miracle that 5% of pilots did progress at a Fortune 100 company. You can't roll out an enterprise tool and assess its impact on hiring practices in just six months—it's an insane metric.
[Pull quote, attributed: "Every business ever is terrible... at enablement. And until we start treating this as someone's dedicated full-time responsibility... to not just manage the tools, but identify the use cases and roll them out and enable your team, you're not gonna see the adoption." - Brian Schmidt, AI Practice Lead, Inverta]
The problem isn't the technology. It's the lack of internal capacity, space, and dedicated ownership to move from a successful pilot to a fully adopted workflow.
Prepare for the real disruption: AI buying agents
If tool obsession and enablement are the current hurdles, the existential threat is what comes next: AI buying agents.
This is the single biggest thing to pay attention to.
Right now, we're seeing SEO traffic drop as humans use AI overviews or chatbots for research instead of clicking links. That's just the start.
Imagine this scenario 18 to 24 months from now:
- An AI agent at your target account is monitoring their business performance data.
- It proactively identifies a problem—for example, "performance within this key audience segment is underperforming in terms of revenue."
- It then consults other specialized agents to determine the best go-to-market strategy for that problem (e.g., a one-to-few ABM campaign).
- It then goes out and researches the best three ABM firms in the country, pulling their pricing, case studies, and everything else it needs to make a decision.
- It presents this fully vetted short list to the human decision-maker... before that human even knew they had a problem.
What happens if you're not on that list? You're done. You are sunk before you even knew a deal existed.
What happens when an agent, not a human, writes your RFP?
This new reality fundamentally breaks the current GTM motion.
- What role do SDRs play when an agent books the demo?
- What role do email nurtures play when the buyer is already 90% of the way to a decision?
- What happens to the "MQL Industrial Complex" when the "lead" is a piece of software?
This agent-led world forces a radical, uncomfortable honesty. You must ask yourself: Am I putting everything out there that a buyer—or an agent—needs to make a decision?
The answer for almost everyone is no.
We gatekeep our most valuable content. We hide our pricing. We force buyers through a short-term, promotional, MQL-focused loop that chases quarterly numbers at the expense of long-term profitability and customer fit.
Win by enabling the buyer (and the agent)
The solution isn't a new AI tool. It's a return to first principles, amplified by technology. It's buyer enablement.
Your entire job is to provide value to the buyer. You must make it as transparent and simple as possible for them to make a decision.
This means:
- Stop gatekeeping: Put your best content, case studies, and insights out in the open.
- Publish your pricing: People say pricing pages don't convert. Who cares? That's not what they're for. They're for being valuable and informative to your buyer.
- Be visible everywhere: Your content can't just live on your website. It needs to be in all the places an agent will go looking.
The companies that do this well—that make their value clear, easy to find, and easy to understand—are the ones that will be well-positioned to win.
How to staff for an AI-native future
This agent-based world isn't here tomorrow, but it will be in the next 18-24 months. You need to start preparing your content now, and you need to start preparing your team.
When staffing for this future, don't just look for technical skills. A strong coding background isn't necessary, especially as AI tools get better at building workflows for you.
Instead, hire for:
- Curiosity: This is a massively undervalued trait. You need people who know how to ask "why" something happened, not just describe what happened.
- Critical Thinking: You need people who can see a problem, understand its components, and form a hypothesis about how to solve it.
- Data Structure: The single most critical piece is the data layer. You need people who understand how information must be structured, tagged, and described so that AI systems can access and leverage it.
The businesses that have their data structured in a clear, accessible way will have a tremendous advantage. The future of marketing is a blend of creative, curious people who understand the structure of information.
The time to prepare is now.
Resources
About the author
Service page feature
The RevRoom podcast
The 10% Trap: Why Your AI 'Efficiencies' Are Blinding You to the Real Disruption
Speakers
Other helpful resources
Are you feeling anxious about AI? Last year, many marketing leaders were. There was a palpable panic that AI would make our jobs obsolete.
But as Inverta's AI Practice Lead, Brian Schmidt, learned at this year's Marketing AI Conference (MAICON), that panic has subsided. It’s been replaced by a new, more dangerous feeling: complacency.
Many teams are stuck in the "10% trap." They're using AI for optimization—small, short-term efficiency gains. They're automating workflows or running A/B tests that might get a 10% lift. This is fine, but it’s a distraction.
The real power of AI isn't optimization. It's innovation. It’s the ability to do things you could not do before, unlocking 10x gains, not 10%. And this innovation is about to completely upend the B2B buying process. If you're only focused on 10% efficiencies, you won't see the disruption coming until it's too late.
Ditch optimization, focus on innovation
The shift from optimization to innovation is the single biggest takeaway from this year's conference.
- Optimization is using AI to do the same things a little faster or a little better. It’s automating an existing workflow or finding a small lift.
- Innovation is using AI to do entirely new things. It's freeing up your team's time not just for efficiency's sake, but to use that new time to tackle transformative projects.
The optimization mindset is a dead end. The innovation mindset is where you'll find true strategic value.
Use AI as your strategic thought partner
AI can't fix a broken go-to-market strategy. But it can act as a powerful "thought partner" to make your strategy smarter.
For the last decade, B2B marketing has been stuck in a "promotional factory". We take a piece of content, send an email, and make an ad, over and over. We’ve become buried in campaign performance metrics—email opens, funnel stages—and lost the plot.
This is where AI innovation can break the cycle. Instead of just optimizing the factory, use AI to return to research-first marketing. Use its reasoning models to:
- Analyze macro trends influencing your audience that you lack the budget to research.
- Identify potential markets or segments you're not addressing.
- Help you think through what’s possible based on your business inputs, goals, and performance data.
[Pull quote, attributed: "No business is gonna fold because your emails are underperforming a little bit... a business will fold if your entire product is now obsolete or a disruptor has come along and tanked it." - Brian Schmidt, AI Practice Lead, Inverta]
Reacting to these macro-level, existential threats—not optimizing an email open rate—is the strategic work marketers must reclaim.
Stop chasing the 'new tool' high
One of the biggest mistakes holding teams back is "new tool obsession". It’s easy to get excited about a shiny new tool that promises a 10% boost in outreach.
But this is backward. AI is still just a tool. You must always start with the problem you are trying to solve.
- What is my role?
- What am I trying to accomplish?
- What is my process, and what systems are involved?
- Is this a people problem, a process problem, or a tool problem?
Only after answering these questions can you look for a solution.
And here’s the new reality: it has become much easier to solve these problems in-house. Tools like ChatGPT or Claude can literally help you code and produce your own solution. All it takes is someone with a good idea. You no longer need a highly technical coding skillset to prototype and build a fix.
This "AI-native" mentality—build it myself first, then look to buy—will save you from a bloated tech stack full of tools that may not exist in two years as platforms consolidate them.
Recognize the real bottleneck is enablement, not technology
Many enterprise leaders are paralyzed. They run a pilot, it works well, and then... nothing.
A recent MIT paper noted that 95% of AI pilots at large enterprises don't progress. Many took this as a sign that AI hype is outpacing reality.
That is the wrong conclusion.
This isn't an AI failure; it's an enterprise failure. Big companies are terrible at enablement. It's a miracle that 5% of pilots did progress at a Fortune 100 company. You can't roll out an enterprise tool and assess its impact on hiring practices in just six months—it's an insane metric.
[Pull quote, attributed: "Every business ever is terrible... at enablement. And until we start treating this as someone's dedicated full-time responsibility... to not just manage the tools, but identify the use cases and roll them out and enable your team, you're not gonna see the adoption." - Brian Schmidt, AI Practice Lead, Inverta]
The problem isn't the technology. It's the lack of internal capacity, space, and dedicated ownership to move from a successful pilot to a fully adopted workflow.
Prepare for the real disruption: AI buying agents
If tool obsession and enablement are the current hurdles, the existential threat is what comes next: AI buying agents.
This is the single biggest thing to pay attention to.
Right now, we're seeing SEO traffic drop as humans use AI overviews or chatbots for research instead of clicking links. That's just the start.
Imagine this scenario 18 to 24 months from now:
- An AI agent at your target account is monitoring their business performance data.
- It proactively identifies a problem—for example, "performance within this key audience segment is underperforming in terms of revenue."
- It then consults other specialized agents to determine the best go-to-market strategy for that problem (e.g., a one-to-few ABM campaign).
- It then goes out and researches the best three ABM firms in the country, pulling their pricing, case studies, and everything else it needs to make a decision.
- It presents this fully vetted short list to the human decision-maker... before that human even knew they had a problem.
What happens if you're not on that list? You're done. You are sunk before you even knew a deal existed.
What happens when an agent, not a human, writes your RFP?
This new reality fundamentally breaks the current GTM motion.
- What role do SDRs play when an agent books the demo?
- What role do email nurtures play when the buyer is already 90% of the way to a decision?
- What happens to the "MQL Industrial Complex" when the "lead" is a piece of software?
This agent-led world forces a radical, uncomfortable honesty. You must ask yourself: Am I putting everything out there that a buyer—or an agent—needs to make a decision?
The answer for almost everyone is no.
We gatekeep our most valuable content. We hide our pricing. We force buyers through a short-term, promotional, MQL-focused loop that chases quarterly numbers at the expense of long-term profitability and customer fit.
Win by enabling the buyer (and the agent)
The solution isn't a new AI tool. It's a return to first principles, amplified by technology. It's buyer enablement.
Your entire job is to provide value to the buyer. You must make it as transparent and simple as possible for them to make a decision.
This means:
- Stop gatekeeping: Put your best content, case studies, and insights out in the open.
- Publish your pricing: People say pricing pages don't convert. Who cares? That's not what they're for. They're for being valuable and informative to your buyer.
- Be visible everywhere: Your content can't just live on your website. It needs to be in all the places an agent will go looking.
The companies that do this well—that make their value clear, easy to find, and easy to understand—are the ones that will be well-positioned to win.
How to staff for an AI-native future
This agent-based world isn't here tomorrow, but it will be in the next 18-24 months. You need to start preparing your content now, and you need to start preparing your team.
When staffing for this future, don't just look for technical skills. A strong coding background isn't necessary, especially as AI tools get better at building workflows for you.
Instead, hire for:
- Curiosity: This is a massively undervalued trait. You need people who know how to ask "why" something happened, not just describe what happened.
- Critical Thinking: You need people who can see a problem, understand its components, and form a hypothesis about how to solve it.
- Data Structure: The single most critical piece is the data layer. You need people who understand how information must be structured, tagged, and described so that AI systems can access and leverage it.
The businesses that have their data structured in a clear, accessible way will have a tremendous advantage. The future of marketing is a blend of creative, curious people who understand the structure of information.
The time to prepare is now.
About the author
Service page feature