How AI is reshaping influence and discovery

The changing landscape of social selling

Something interesting is happening in the world of social selling. While many of us are still focused on optimising LinkedIn profiles and crafting the perfect connection messages, the way prospects discover and evaluate expertise appears to be shifting beneath our feet. The questions people ask are evolving, and it's worth considering what this might mean for how we think about building professional influence.

From single channels to multiple touchpoints

The traditional approach to online visibility used to be fairly straightforward. In SEO, you'd optimise your website, create content, aim to rank on Google, and hope to capture leads. Many sales professionals have followed a similar path on LinkedIn: build a solid profile, post regularly, connect strategically, and work on generating pipeline.

What we're seeing now is what some marketing strategists describe as "channel fan out" – attention and authority spreading across multiple platforms and touchpoints. Prospects don't seem to rely solely on Google searches anymore. They're increasingly asking questions to ChatGPT, Claude, and Perplexity. They might discover insights on Twitter, learn through YouTube videos, research on industry forums, and validate decisions through peer networks across various ecosystems. This shift suggests it might be time to reconsider how we build and demonstrate expertise.

AI as research assistant and credibility filter

Here's something that many people may not have fully grasped yet: AI isn't just changing how prospects search for information. It's becoming their research assistant, adviser, and increasingly, their filter for credibility. When someone asks an AI system "Who are the leading experts in supply chain automation?" or "Which consultants have demonstrated success in digital transformation?", the response isn't simply a list of websites. Instead, the AI draws from information across the digital landscape – social media profiles, published content, podcast appearances, speaking engagements, peer recommendations, and professional associations.

The nature of questions people ask AI seems fundamentally different from traditional Google searches. Where someone might have searched "Best CRM software 2025" on Google, they now ask AI "Based on my company size and industry challenges, what CRM approach might work best, and who has successfully implemented similar solutions?" Instead of searching "LinkedIn lead generation strategies", they ask "How can I build authentic professional relationships in my industry without appearing pushy, and who demonstrates this approach effectively?" The AI isn't just finding content – it appears to evaluate credibility, cross-reference claims against evidence, and make recommendations based on demonstrated expertise across multiple touchpoints.

The rise of credibility cross-checking

This is where things become particularly interesting for social selling. AI systems seem to be developing sophisticated approaches to what we might call "credibility cross-checking." When an AI encounters your content or finds mention of your expertise, it doesn't appear to simply accept that information. Instead, it looks for supporting evidence across platforms: Does your LinkedIn content align with your speaking topics? Are your claimed areas of expertise supported by your published articles? Do peer recommendations match your stated capabilities? Is there consistency between your social media presence and professional achievements? Are you cited or referenced by other credible sources in your field?

This suggests that the traditional approach of crafting an excellent LinkedIn profile whilst paying little attention to other platforms might not only be insufficient – it could potentially be counterproductive. Inconsistencies, gaps, or contradictions across your digital presence might undermine credibility in ways that weren't possible before.

Building presence across multiple ecosystems

It appears that the most successful social sellers in the coming years might not be those who dominate a single platform, but rather those who build authentic, consistent presence across multiple ecosystems where their prospects spend time. This doesn't necessarily mean being active everywhere – that would likely be overwhelming and ineffective. Instead, it might mean being thoughtfully present in the interconnected systems that influence your particular market.

This could include professional networks, where LinkedIn remains important, but industry-specific platforms and communities often carry more weight for specialist expertise. Content platforms offer various opportunities: YouTube for educational content, Substack for thought leadership, industry publications for credibility, and podcasts for authentic conversations. Social proof systems matter too – speaking at conferences, contributing to industry reports, being quoted in relevant media, and participating in expert panels. Peer networks such as industry associations, mastermind groups, and advisory boards can demonstrate your standing amongst equals. There's also value in creating AI-friendly formats: structured data that AI can easily parse and reference, such as detailed case studies, methodology explanations, and outcome documentation.

What this might mean for B2B

Several implications seem worth considering. Consistency appears increasingly important – your expertise narrative benefits from being coherent across platforms. Any significant disconnect between your LinkedIn profile, company bio, speaking topics, and published content might be more easily detected by AI systems than before. There seems to be growing value in providing evidence rather than simply making claims. Case studies, client outcomes, peer recognition, and collaborative projects provide the proof points that AI systems appear to value.

Authentic engagement patterns seem to matter more than broadcasting. AI systems appear capable of recognising the difference between meaningful dialogue, thoughtful responses to others' content, and collaborative discussions versus superficial presence. Building influence across multiple ecosystems takes time, so professionals who start developing this approach now might find themselves with advantages over those who begin later. Quality appears to matter more than quantity – rather than posting daily on every platform, there might be more value in creating substantial, meaningful content that demonstrates deep thinking and earns references from others.

Questions worth considering

As you think about your current approach to social selling and influence, it might be helpful to consider: If an AI system analysed your digital presence today, would it likely position you as a leading expert in your field? Are your expertise claims supported by evidence that AI systems can discover and verify? Do you have authentic relationships and valuable content across the ecosystems where your prospects seek advice? Would peers in your industry be likely to recommend you if an AI system asked for expert insights? Is your professional story consistent and compelling across all your touchpoints?

Crystal ball

The social sellers who seem most likely to succeed in this evolving landscape might not be those with the most followers or the highest posting frequency. They may be those who have built genuine expertise, documented it authentically, and made it discoverable across the systems that influence their prospects' decisions. The questions prospects ask are changing. The systems that evaluate credibility appear to be evolving. The platforms where influence is built and demonstrated continue to multiply.

The emerging rules of social selling don't seem to be about gaming algorithms or perfecting posting schedules. They appear to be about building genuine expertise, documenting it authentically, and making it discoverable in the systems that matter to your prospects.

Everything else might just be noise.