From Pilot to Production | Why Half of AI Projects Fail to Scale

50% of AI projects are abandoned after proof of concept according to Gartner.

Most marketing teams have already seen flashes of AI’s capacity to collapse the time and cost of advanced analytics. Equally, they’ve seen how quickly trust disappears when an answer is wrong. 

Marketing leaders are struggling to turn promising AI pilots into systems that deliver consistently reliable results. Despite incredibly powerful AI models, the gap between experimentation and operational impact is wider than most organisations want to admit, and it’s here where most marketing AI pilots stall. 

In this session we sit down with Sameen Gul, Global IT Director Marketing & AI at Reckitt, who is navigating this journey right now; experimenting with AI, learning what works, and working out what it actually takes to move from pilot to something that scales. We'll talk honestly about where AI has got it wrong, what the blockers are, the build vs buy question, and what has to change for AI to deliver accurate, autonomous intelligence that marketers can trust.

Join us for an honest conversation about what separates AI that scales from AI that stalls, and what it takes to bridge that gap.

Audience Takeaways

• Why most marketing AI pilots stall before reaching production and what's blocking them

• What to prioritise when scaling AI across your marketing data environment

• A practical framework for moving from AI experimentation to operational impact