The narrative that AI killed traditional GTM is false. Leaders at firms like OpenAI and Anthropic are SaaS veterans applying modified versions of proven strategies. If your GTM is failing, the problem is likely poor execution, not an outdated playbook.
Contrary to the belief that top-tier products sell themselves, even OpenAI—the hottest company on Earth—uses pilots for major deals. If your pilots aren't converting, the issue is your product's value proposition, not the pilot process itself.
The market is rejecting 'lame co-pilots' that provide minor workflow improvements for an extra fee. Successful AI products create entirely new, powerful use cases and deliver substantial, tangible value on day one, justifying their place in the budget.
LLMs can actually benefit sites with deep, authoritative content, even if it's not ranked #1 on Google. AI models prioritize surfacing the best answer, regardless of traditional rank, potentially increasing traffic for subject matter experts.
With hundreds of new AI vendors, buyers are overwhelmed and seek validation. This makes classic tactics like webinars and case studies more effective than ever. They provide the social proof needed to build trust and help buyers navigate a crowded, confusing market.
Companies like Notion and Datadog are re-accelerating by targeting new, dedicated AI budgets. This is separate from shrinking 'efficiency tool' budgets. Growth comes from solving problems that unlock this specific new spending category, not just adding a minor AI feature.
The business case for AI isn't always about revenue or cost-savings. For SaaStr, the primary driver was solving employee burnout and churn in repetitive roles like SDR and content review. AI can provide operational consistency when people no longer want to do the work.
Unlike training a human, feeding an AI SDR historical 'good' emails can limit its effectiveness. The better approach is to train it on core personas and ways to add value, allowing the AI to use its ability to scrape vast, real-time data for hyper-personalization.
The perception that AI agents require a lot of time stems from a misunderstanding of sales management. A good human sales leader spends a huge amount of time coaching their team. AI makes this necessary process visible and measurable, forcing founders to engage in it.
AI makes it easy to generate grammatically correct but generic outreach. This flood of 'mediocre' communication, rather than 'terrible' spam, makes it harder for genuine, well-researched messages to stand out. Success now requires a level of personalization that generic AI can't fake.
Selling an efficiency-focused SaaS tool is harder than ever. CIOs are cutting classic SaaS tools while expanding their AI budget. Any remaining efficiency spend is being consumed by price hikes from giants like Salesforce, leaving no room for new, non-AI vendors.