Working on Wurundjeri land
Working on Wurundjeri land
Hashtags are no longer the growth lever they once were. While they still exist within platform functionality, their role in driving discovery and reach has significantly diminished. What has replaced them is more complex, more intelligent, and far more aligned with how audiences now search and consume information.
Social media is no longer just a content distribution channel. It has become part of a wider discovery ecosystem shaped by AI-powered search engines and generative tools. These systems are influencing what audiences see, trust, and act on, often before they even land on a website.
This shift introduces a new discipline for marketers: Generative Engine Optimisation, or GEO. Unlike traditional SEO, which relies heavily on backlinks and keyword structures, GEO focuses on clarity, credibility, and content that can be easily interpreted and summarised by AI systems.
SEO was built around visibility through search rankings and link authority. GEO reflects a different reality. AI-driven search tools are now prioritising content that is direct, context-rich, and demonstrably useful.
In this environment, social media plays a more active role than ever. Platforms like Instagram, TikTok, Facebook and LinkedIn are no longer just engagement tools. They are data sources that inform how AI systems understand relevance and authority.
AI models assess social content based on signals such as engagement, recency, and consistency. They also look at how often content is referenced, shared, and discussed across platforms. This means that social performance is now directly linked to broader discoverability in AI-generated answers and summaries.
One of the most significant changes is how authority is established. It is no longer defined by how a brand positions itself, but by how audiences interact with and respond to its content.
Engagement signals such as comments, shares, saves, and meaningful conversations all contribute to how content is interpreted by algorithms and AI systems. Importantly, depth of engagement matters more than volume alone. A smaller number of considered interactions can carry more weight than passive reach.
This shifts social media strategy from broadcasting messages to facilitating conversation. Content needs to invite response, not just attention.
AI systems prioritise content that is current and actively maintained. Social media feeds into this by acting as a real-time reflection of brand activity.
Consistent posting signals that a brand is active, relevant, and engaged with its audience. It also ensures that content remains fresh enough to be included in AI-generated summaries and recommendations.
In practical terms, consistency is no longer just about maintaining visibility with followers. It is about ensuring ongoing eligibility within discovery systems that prioritise recent and active content.
One of the strongest signals in GEO is earned content. This includes third-party validation such as reviews, user-generated content, media coverage, and discussions across platforms like Reddit and LinkedIn.
Unlike owned content, earned content cannot be directly controlled, but it can be influenced. It plays a critical role in how AI systems assess credibility and trust.
Brands that actively encourage positive mentions, authentic user experiences, and organic conversation are more likely to benefit from stronger visibility in AI-generated outputs.
This makes advocacy, community engagement, and reputation-building central to modern social strategy.
Search behaviour has become increasingly conversational. Users are no longer searching with short keyword phrases, but with full questions and intent-led queries.
Social content that mirrors this behaviour performs more effectively. This means using natural language, clearly framed questions, and direct answers within captions and creative.
The first few lines of a caption are particularly important. They now act as both a hook for users and a context signal for AI systems interpreting content relevance.
For example, content structured around “how to experience,” “what to do in,” or “best ways to” is more likely to align with both user intent and AI retrieval systems than generic descriptors.
As AI becomes more integrated into search and discovery, content structure plays a larger role in performance.
Clear formatting, logical flow, and easily digestible information help both users and systems understand content faster. This includes the use of:
Multimedia content is also increasingly important, as AI systems interpret images and video to better understand context and intent.
Social media is no longer operating in isolation. It now feeds directly into search engines, AI tools, and recommendation systems that shape how audiences discover information.
This means that social content is no longer just about engagement metrics. It contributes to how a brand is understood across the broader digital ecosystem.
Success is increasingly defined by:
Optimising for today’s social landscape requires a shift in focus. It is no longer enough to create content that performs within a platform. Content must now be designed to perform across systems.
This means prioritising:
Hashtags may no longer be central to discovery, but visibility has not disappeared. It has simply become more intelligent, more contextual, and more dependent on the signals brands send across their entire digital presence.
