The AI Recommendation Milestone
An interesting milestone yesterday: A prospect reached out for a demo after Claude (Anthropic's AI) independently recommended Lexer as the best fit for their requirements.
This wasn't the result of targeted advertising, SEO optimization, or a carefully crafted content marketing strategy. It was an AI system analyzing requirements, considering available options, and making a recommendation based on its understanding of capabilities and fit.
In a world where AI increasingly guides business decisions, it's fascinating how traditional SEO might evolve.
The Evolution of Organic Discovery
For decades, "organic search" meant appearing in Google's unpaid search results. We optimized websites, created content, and built link strategies all designed to capture users actively searching for solutions.
But what happens when the search itself changes? When instead of typing "best customer data platform for retail," a business leader asks Claude or ChatGPT: "I need to understand my customers better across multiple touchpoints. What should I consider?"
The AI doesn't just return a list of websites to evaluate—it analyzes the requirements, considers the context, and makes specific recommendations. This is a fundamentally different dynamic than traditional search.
Will AI Recommendations Become the New 'Organic Search'?
If AI systems are increasingly making business recommendations, then being favorably positioned in these AI responses becomes critical. But how do you optimize for something that doesn't rely on traditional ranking factors?
The answer might lie less in gaming the system and more in genuinely being the best solution for specific use cases. AI systems are trained on vast amounts of information—they're looking for substance, not just SEO tricks.
This creates an interesting paradox: to be recommended by AI, you might need to focus less on traditional SEO and more on being genuinely excellent at what you do, with clear documentation of your capabilities and successful outcomes.
Do the Old Tricks Still Work?
Do the old tricks of keyword-rich landing pages have the same influence over GenAI?
My hypothesis is that they don't—at least not in the same way. AI systems are trained to understand context and meaning, not just keyword density. They're looking for:
- Clear explanations of what you actually do
- Evidence of successful outcomes
- Transparent discussion of limitations and ideal use cases
- Authentic customer feedback and case studies
The traditional SEO approach of stuffing keywords into content might actually work against you if it makes your content less clear or authentic.
The Credibility Question
Will AI-written content detract from credibility?
This is perhaps the most complex question. AI can help with structure, research, and even drafting, but the insights, experiences, and genuine expertise still need to come from humans.
I suspect AI systems will become quite good at distinguishing between content that demonstrates real expertise and content that's purely generated. The key differentiator will be original insights, specific examples, and the kind of nuanced understanding that comes from actually solving real problems.
Optimizing for AI Recommendations
If AI recommendations are becoming a new channel for organic discovery, how should businesses adapt their approach?
Focus on clarity over cleverness: Make it easy for AI to understand exactly what you do, who you serve, and what problems you solve.
Document your differentiation: Be specific about your unique capabilities and ideal use cases. AI systems need clear information to make appropriate recommendations.
Showcase real outcomes: Case studies, customer testimonials, and specific results provide the kind of evidence AI systems can use to assess fit.
Be honest about limitations: Paradoxically, being clear about what you're not good at might help AI make better recommendations when you are the right fit.
The Broader Implications
This shift represents more than just a new marketing channel—it's a fundamental change in how B2B discovery works. When AI can analyze requirements and make recommendations, it democratizes access to expertise that was previously only available through consultants or extensive research.
For businesses, this means the quality of your solution and the clarity of your positioning become even more important than your marketing budget or SEO sophistication.
Interesting Times Ahead
We're still in the early days of understanding how AI will reshape business discovery and evaluation. But one thing seems clear: the businesses that will thrive are those that focus on being genuinely excellent at solving specific problems, rather than those that are merely excellent at being found.
The AI recommendation I received wasn't the result of gaming an algorithm—it was the result of building something that actually fit the prospect's needs. In a world where AI increasingly guides business decisions, that might be the most valuable optimization strategy of all.
Interesting times ahead indeed. The question isn't whether AI will change how businesses are discovered—it's whether you'll be ready when it does.