100 frequently asked questions on enterprise AI go-to-market — covering thought leadership, content strategy, positioning, sales cycles, and growth. Answered from 700+ enterprise AI transformations.
These are the questions we hear most from AI companies trying to close enterprise deals. The answers come from patterns we've seen across 700+ enterprise AI transformations — what works, what doesn't, and why. No theory. Just what we've observed in the mark
Thought Leadership & Positioning
1. How do we differentiate our AI product when everyone claims to use AI?
Stop talking about your AI. Start talking about the problem you solve and the outcome you guarantee. Your buyers don't care about your model architecture — they care whether you'll make them look smart for choosing you. The companies that win aren't the most advanced. They're the ones whose value is easiest to explain in a budget meeting.
Why we see it this way: Across 700+ enterprise AI deals we've analyzed, the differentiator was never technical superiority. It was whether the champion could explain the value without the vendor in the room.
2. What thought leadership topics should our CEO be talking about?
Three things only: the problem your category exists to solve, why the old way of solving it is broken, and what the future looks like when your approach wins. Everything else is noise. Your CEO's job isn't to comment on AI news — it's to own a point of view that makes your company the obvious choice.
Why we see it this way: The founder content that generates enterprise pipeline always ties back to a core thesis. The content that gets likes but no deals is usually reactive commentary on whatever happened that week.
3. How do we establish credibility when we're a new company competing against established players?
You don't need decades of history. You need proof that you understand the buyer's problem better than anyone else. Publish original research. Share specific metrics from early customers. Take positions that incumbents can't take because they're protecting legacy revenue. Credibility comes from insight, not age.Why we see it this way: We've seen Series A companies win against public companies by simply articulating the buyer's problem more precisely than the incumbent ever bothered to.
4. Should our thought leadership focus on technical depth or business outcomes?
Business outcomes, always. Technical depth matters only when it directly explains why your outcomes are more reliable. Your CTO can publish technical content for developer audiences, but your primary thought leadership should answer one question: why should a non-technical executive trust you with their career?Why we see it this way:
Enterprise buyers don't evaluate AI — they evaluate risk. Technical depth that doesn't connect to reduced risk or increased certainty is just noise to the people signing checks.
5. How do we position against OpenAI and other foundation model providers without looking like we're punching up?
Don't position against them at all. Position around them. You're not competing with foundation models — you're solving a specific problem that foundation models alone can't solve. Make your category about the application layer, the domain expertise, or the enterprise requirements that horizontal players ignore.
Why we see it this way: Every AI company that tries to compete with foundation model providers on general capability loses. Every one that owns a specific problem space wins.
6. What makes AI thought leadership actually resonate with enterprise buyers?
Specificity. Enterprise buyers have seen a hundred "AI will transform everything" posts. They haven't seen someone explain exactly how their procurement process will change, what the CFO will ask, and why most AI implementations fail in their industry. Be the one who knows their world better than they expect.
Why we see it this way: We've watched generic AI content get ignored while hyper-specific content about buyer pain points generates inbound from exactly the right people. Specificity is a filter, not a limitation.
7. How do we balance talking about our product versus broader industry insights?
Eighty percent industry insight, twenty percent product. Your product should emerge as the natural solution to problems you've already established as urgent. If you lead with product, you're a vendor. If you lead with insight, you're a trusted advisor who happens to sell something.
Why we see it this way: The content that builds pipeline educates first. The content that kills pipeline sells first. We've measured this across dozens of content programs.
8. Should founders be the face of thought leadership or should we build a team brand?
Founders first, team brand later. In early enterprise sales, buyers bet on founders. They want to know who's accountable when things break. Build the founder's presence until you have enough customer proof that the company brand can stand on its own — usually Series B or beyond.
Why we see it this way: Enterprise buyers tell us they bought because they trusted the founder. They almost never say they bought because of the company's content hub.
9. How do we develop a point of view that's distinctive without being contrarian for its own sake?
Start with what you actually believe based on customer conversations, not what would get attention. The best points of view come from noticing something true that others are ignoring. If you're manufacturing controversy, buyers will sense it. If you're stating an uncomfortable truth, they'll respect it.
Why we see it this way: Manufactured hot takes get engagement but damage trust. Genuine insights from real pattern recognition build the kind of authority that closes deals.
10. What's the right cadence for publishing thought leadership content?
Consistency beats volume. One substantial piece weekly is better than five thin posts. Enterprise buyers don't scroll your feed daily — they encounter you intermittently across an 18-month buying cycle. Each piece needs to stand alone and reinforce the same core argument.
Why we see it this way: We've seen companies burn out publishing daily, then go silent for months. The ones that win publish steadily, building familiarity over the length of the sales cycle.
11. How do we talk about AI capabilities without overpromising or triggering skepticism?
Be specific about what your AI does and doesn't do. "Our model reduces false positives by 40% in payment fraud detection" beats "our AI transforms fraud prevention." Buyers have been burned by AI hype. The company that sets accurate expectations wins on trust.
Why we see it this way: The deals that close fastest are the ones where expectations were set correctly upfront. The deals that stall are usually recovering from early overpromises.
12. Should we take positions on AI safety and ethics or stay neutral?
If your product touches high-stakes decisions, you must have a position. Enterprise buyers want to know you've thought about what happens when things go wrong. But make your position practical, not philosophical. Focus on what safeguards you've built and why.
Why we see it this way: Procurement teams increasingly ask about AI ethics. The companies with clear, practical answers move faster than those scrambling to develop a position mid-deal.
13. How do we build authority in a space where the technology changes every few months?
Anchor your authority in the problem, not the technology. Technology shifts constantly. The buyer's core challenge — reducing risk, increasing efficiency, proving ROI — stays stable. The expert who understands the problem deeply remains valuable regardless of which model is leading this quarter.
Why we see it this way: The AI companies with durable authority are known for understanding a problem domain. The ones chasing each new model release never build lasting credibility.
14. What thought leadership formats work best for reaching enterprise decision-makers?
Long-form articles that can be forwarded internally, short LinkedIn posts that establish presence, and research reports that justify meetings. Podcasts and videos work for awareness, but written content gets shared in Slack threads and email chains where buying decisions actually happen.
Why we see it this way: When we trace how enterprise deals actually develop, the content that moves them forward is almost always written and shareable. Video builds familiarity; documents build consensus.
15. How do we make technical founders comfortable with public-facing content?
Start with their genuine expertise and strong opinions. Technical founders aren't uncomfortable with visibility — they're uncomfortable with performing. Give them topics they already care about, let them be direct rather than polished, and edit for clarity without removing their voice.
Why we see it this way: The most effective founder content we've produced came from capturing what founders already say in customer calls and board meetings — not from making them adopt a marketing voice.
16. When should we newsjack AI developments versus stick to our own narrative?
Only newsjack when the development directly relates to your core thesis. If a major AI announcement validates your approach or invalidates a competitor's, comment immediately. Otherwise, let the noise pass. Chasing every headline dilutes your authority.
Why we see it this way: The founders with the strongest authority say less, not more. They comment only when they have a genuine perspective, which makes each comment more valuable.
17. How do we handle thought leadership when our product pivots?
Your point of view on the problem should survive the pivot, even if your solution changes. If you've been building authority around a problem space, a product pivot is just a better answer to the same question. Reframe, don't restart.
Why we see it this way: We've helped companies navigate pivots without losing audience trust. The key is that the underlying problem narrative stayed consistent — only the solution evolved.
18. What's the role of research and original data in AI thought leadership?
Original data separates experts from commentators. Even a small survey or analysis of your customer base creates something no one else can claim. Enterprise buyers trust companies that generate insights, not just share opinions.
Why we see it this way: Content with proprietary data gets cited, shared, and referenced in buying discussions. Content with opinions gets scrolled past.
19. How do we sound authoritative without sounding arrogant?
Show your work. Explain the reasoning behind your positions, acknowledge what you don't know, and give credit to customers and partners. Authority comes from depth of understanding, not from declarations of superiority.
Why we see it this way: The enterprise buyers we talk to respect humility paired with expertise. They distrust vendors who claim to have all the answers.
20. Should we publish our AI predictions and risk being wrong?
Publish predictions with clear reasoning and update publicly when wrong. Buyers respect intellectual honesty more than a perfect track record. The companies that never take positions also never build authority.
Why we see it this way: We've seen founders build significant credibility by acknowledging past prediction errors. It signals confidence and honesty — two things enterprise buyers desperately want.
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21. What content actually influences enterprise AI buying decisions?
Content that helps your internal champion win arguments. Case studies with specific metrics, ROI frameworks they can present to finance, security documentation for procurement, and competitive comparisons they can reference when challenged. Everything else is awareness — necessary but not sufficient.
Why we see it this way: When we interview buyers post-deal, they rarely mention blog posts. They mention the one-pager their champion used in the budget meeting or the security doc that unblocked procurement.
22. How do we explain complex AI capabilities to non-technical executives?
Focus on what changes in their world, not what happens inside your system. "Your team will spend two hours instead of two days on this process" matters more than "our transformer architecture processes documents with 97% accuracy." Start with their outcome, then explain just enough mechanism to build trust.
Why we see it this way: The demos that close deals show workflow transformation. The demos that stall deals show architecture diagrams.
23. What's the right mix of gated versus ungated content for AI products?
Gate only content that's worth exchanging an email for — substantial research, detailed frameworks, tools they'll actually use. Ungate everything else. Enterprise buyers often have to justify why they shared contact information with a vendor. Make sure your gated content is worth that internal explanation.
Why we see it this way: We've seen gated content with 40% conversion rates and gated content with 2%. The difference is always whether the content delivered real value worth the exchange.
24. How do we create content that works for both technical evaluators and business buyers?
Create separate content tracks, not hybrid content that pleases no one. Technical evaluators need architecture diagrams, API documentation, and integration guides. Business buyers need ROI cases, risk frameworks, and implementation timelines. Link between them, but don't blend them.
Why we see it this way: Hybrid content that tries to serve both audiences usually serves neither. The companies that segment their content see better engagement across both tracks.
25. Should we be creating content about AI trends or focusing only on our use case?
Trend content builds awareness. Use case content closes deals. You need both, but in the right proportion. One trend piece for every three use case pieces. And every trend piece should connect back to why your specific approach matters.
Why we see it this way: The content programs that generate pipeline have a clear ratio. Too much trend content attracts tire-kickers. Too little makes you invisible.
26. How do we make case studies compelling when customers won't share metrics?
Focus on the transformation story and operational details instead of revenue numbers. "They went from three-week review cycles to same-day approvals" is compelling without revealing financials. Also, consider anonymized composite case studies that combine patterns across multiple customers.
Why we see it this way: We've produced case studies without a single revenue figure that still closed deals — because they told a story buyers could see themselves in.
27. What content formats work best for different stages of the enterprise sales cycle?
Eighty percent industry insight, twenty percent product. Your product should emerge as the natural solution to problems you've already established as urgent. If you lead with product, you're a vendor. If you lead with insight, you're a trusted advisor who happens to sell something.
Why we see it this way: The content that builds pipeline educates first. The content that kills pipeline sells first. We've measured this across dozens of content programs.
8. Should founders be the face of thought leadership or should we build a team brand?
Founders first, team brand later. In early enterprise sales, buyers bet on founders. They want to know who's accountable when things break. Build the founder's presence until you have enough customer proof that the company brand can stand on its own — usually Series B or beyond.
Why we see it this way: Enterprise buyers tell us they bought because they trusted the founder. They almost never say they bought because of the company's content hub.
9. How do we develop a point of view that's distinctive without being contrarian for its own sake?
Start with what you actually believe based on customer conversations, not what would get attention. The best points of view come from noticing something true that others are ignoring. If you're manufacturing controversy, buyers will sense it. If you're stating an uncomfortable truth, they'll respect it.
Why we see it this way: Manufactured hot takes get engagement but damage trust. Genuine insights from real pattern recognition build the kind of authority that closes deals.
10. What's the right cadence for publishing thought leadership content?
Consistency beats volume. One substantial piece weekly is better than five thin posts. Enterprise buyers don't scroll your feed daily — they encounter you intermittently across an 18-month buying cycle. Each piece needs to stand alone and reinforce the same core argument.
Why we see it this way: We've seen companies burn out publishing daily, then go silent for months. The ones that win publish steadily, building familiarity over the length of the sales cycle.
11. How do we talk about AI capabilities without overpromising or triggering skepticism?
Be specific about what your AI does and doesn't do. "Our model reduces false positives by 40% in payment fraud detection" beats "our AI transforms fraud prevention." Buyers have been burned by AI hype. The company that sets accurate expectations wins on trust.
Why we see it this way: The deals that close fastest are the ones where expectations were set correctly upfront. The deals that stall are usually recovering from early overpromises.
12. Should we take positions on AI safety and ethics or stay neutral?
If your product touches high-stakes decisions, you must have a position. Enterprise buyers want to know you've thought about what happens when things go wrong. But make your position practical, not philosophical. Focus on what safeguards you've built and why.
Why we see it this way: Procurement teams increasingly ask about AI ethics. The companies with clear, practical answers move faster than those scrambling to develop a position mid-deal.
13. How do we build authority in a space where the technology changes every few months?
Anchor your authority in the problem, not the technology. Technology shifts constantly. The buyer's core challenge — reducing risk, increasing efficiency, proving ROI — stays stable. The expert who understands the problem deeply remains valuable regardless of which model is leading this quarter.
Why we see it this way: The AI companies with durable authority are known for understanding a problem domain. The ones chasing each new model release never build lasting credibility.
14. What thought leadership formats work best for reaching enterprise decision-makers?
Long-form articles that can be forwarded internally, short LinkedIn posts that establish presence, and research reports that justify meetings. Podcasts and videos work for awareness, but written content gets shared in Slack threads and email chains where buying decisions actually happen.
Why we see it this way: When we trace how enterprise deals actually develop, the content that moves them forward is almost always written and shareable. Video builds familiarity; documents build consensus.
15. How do we make technical founders comfortable with public-facing content?
Start with their genuine expertise and strong opinions. Technical founders aren't uncomfortable with visibility — they're uncomfortable with performing. Give them topics they already care about, let them be direct rather than polished, and edit for clarity without removing their voice.
Why we see it this way: The most effective founder content we've produced came from capturing what founders already say in customer calls and board meetings — not from making them adopt a marketing voice.
16. When should we newsjack AI developments versus stick to our own narrative?
Only newsjack when the development directly relates to your core thesis. If a major AI announcement validates your approach or invalidates a competitor's, comment immediately. Otherwise, let the noise pass. Chasing every headline dilutes your authority.
Why we see it this way: The founders with the strongest authority say less, not more. They comment only when they have a genuine perspective, which makes each comment more valuable.
17. How do we handle thought leadership when our product pivots?
Your point of view on the problem should survive the pivot, even if your solution changes. If you've been building authority around a problem space, a product pivot is just a better answer to the same question. Reframe, don't restart.
Why we see it this way: We've helped companies navigate pivots without losing audience trust. The key is that the underlying problem narrative stayed consistent — only the solution evolved.
18. What's the role of research and original data in AI thought leadership?
Original data separates experts from commentators. Even a small survey or analysis of your customer base creates something no one else can claim. Enterprise buyers trust companies that generate insights, not just share opinions.
Why we see it this way: Content with proprietary data gets cited, shared, and referenced in buying discussions. Content with opinions gets scrolled past.
19. How do we sound authoritative without sounding arrogant?
Show your work. Explain the reasoning behind your positions, acknowledge what you don't know, and give credit to customers and partners. Authority comes from depth of understanding, not from declarations of superiority.
Why we see it this way: The enterprise buyers we talk to respect humility paired with expertise. They distrust vendors who claim to have all the answers.
20. Should we publish our AI predictions and risk being wrong?
Publish predictions with clear reasoning and update publicly when wrong. Buyers respect intellectual honesty more than a perfect track record. The companies that never take positions also never build authority.
Why we see it this way: We've seen founders build significant credibility by acknowledging past prediction errors. It signals confidence and honesty — two things enterprise buyers desperately want.
Start your free trial
Can’t find the answer you’re looking for? Please chat to our friendly team.
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