Several months into 2026, marketing strategy focus continues to eye the sweeping introduction of AI tools, campaigns, and processes. As companies such as OpenAI and Google begin mapping the rollout for advertising opportunities in their LLMs, many business leaders wait hesitantly for this future AI advertising revolution to arrive. What most do not realise is that the most significant shifts for supporting effective AI advertising are already here, and if you are holding out on the release of adverts in ChatGPT or Gemini, you’ll find yourself far behind the curve.

Here are four things business owners should champion ahead of LLM ads arriving:

1. Data collection

It’s no secret that the rise in privacy protection, cookie policies, and GDPR rules has impacted our ability to see the full picture of what’s happening with visitors to our sites. If you are using GA4 to measure web analytics, for example, estimates reckon that as much as 50% of data could be lost to declined cookies (Cooper, 2026) (Lidner, 2026).

Previously, when advertising was founded on manual targeting options, this created some frustration with reporting discrepancies across platforms. However, in the newer era of AI and machine learning powered campaign types, platforms do not just report on data but use it to enrich their own learnings, audience targeting, and campaign adjustments automatically. If a business is feeding these algorithmic learnings incomplete or incorrect data, the AI can simply amplify these inaccuracies, leading to large amounts of wasted spend targeting the wrong target users.

To counter this, businesses must have the infrastructure in place to move away from browser-based pixel tracking, where data loss is occurring, and move towards an investment in server-side tracking. By sending data collected directly and securely from a server to ad platforms, businesses can bypass some of the client-side cracks in data collection caused by blockers and privacy settings.

2. Data enrichment

LLMs might successfully find and generate leads for your business, but without the implementation of a proper feedback loop, there is no way for this platform to distinguish between a high-value lead or sale, and a low-quality or irrelevant one. Forward-thinking companies are now utilising offline conversion imports. By syncing up CRM data back to platforms, the AI can learn and understand which specific clicks or interactions led to a “closed-won” deal or a high-value sale. Recent industry insights from Google suggest that moving from volume based bidding to value based bidding, where AI can also recognise the profit margin generated by leads and not just the volume, can improve ROI of ad investment by over 20% (Google, 2026). Without that data pipeline, you’re effectively asking AI to optimise in the dark.

3. Creative importance
   
   While data is the fuel, creative assets are the wheels that turn ‘considering users’ into engaged customers. Currently, it is theorised that platforms like Gemini will implement advertising not within the text conversations themselves, but by showcasing semantically relevant display banners and videos within the flow of a conversation.

This means that more than ever, businesses should invest in a diverse and high-quality creative library. AI-driven campaigns require a high volume of varied assets – not just headlines and descriptions, but images and videos of different formats, sizes, and lengths. Organisations already moving away from predominantly text-based campaigns and investing in high-quality, diverse creatives will be ahead of the curve, generating richer multimodal data and securing a representational advantage within LLM-driven ecosystems.

Consequently, their assets are already being embedded and interpreted by the platform’s AI systems, making them more likely to surface when a user asks a relevant question.

4. Leadership mandate

Preparing the business for AI-optimised advertising is not just a technical hurdle for an IT team or a creative task for the marketing or design team. It must become a strategic mandate for any board or senior leadership team. When it comes to benefiting from AI advertising opportunities, it’s not about becoming the most tech-savvy brand, but the most data ready one.

By auditing data pipelines now and refocusing KPIs around conversion quality, business leaders can position themselves ahead of the competition as LLM-driven advertising becomes mainstream.