AI Marketing and Advertising Innovations
Artificial intelligence has moved far beyond experimental pilots and tactical add-ons. It is now embedded at the core of marketing and advertising strategy, reshaping not only how teams approach creative and campaign delivery but also how they measure outcomes and scale across markets. From hyper-personalisation to the rise of connected TV and the looming promise of quantum computing, the changes are accelerating. For marketing leaders, the challenge lies in adapting fast enough to consumer behaviour while maintaining trust and effectiveness.
### Connected TV and Beyond: Smarter Attribution in Video Advertising
For years, television and video ads were notoriously difficult to link to tangible outcomes. New AI-powered attribution tools are solving that gap by connecting TV, connected TV, and online video campaigns directly to conversions, sales, and revenue. This shift is particularly impactful in high-consideration industries such as healthcare and automotive, where consumers research extensively before purchase. AI-driven attribution not only strengthens accountability but also gives marketers confidence to invest more in video storytelling, knowing they can track real business impact rather than just brand lift.
What This Means for Marketers:
– Use AI attribution platforms to close the loop between video exposure and bottom-line outcomes
– Reinvest in TV and CTV where you can prove ROI beyond reach metrics
– Build creative content to match high-value, research-heavy purchases
### The Rise of AI-First Creative and Localisation
Generative AI is now underpinning creative development across formats. Over half of marketers are already using it for video scripts, audio tracks, or visuals. Beyond speed and cost savings, AI is enabling a scale of creative exploration that was previously unfeasible, letting smaller firms rival big-brand output. At the same time, localisation has emerged as a bottleneck. Buyers expect messaging in their own language, yet many campaigns still launch in a single version. AI is turning localisation from a cost burden into a lever for growth, creating credible, tailored content for diverse audiences. The risk lies in over-automation: while scale is easier, consumer trust and authenticity remain a concern.
What This Means for Marketers:
– Invest in AI creative tools to expand output but maintain human oversight for authenticity
– Prioritise localisation as a growth driver, not an afterthought
– Tackle trust head-on by being transparent about AI usage in consumer-facing content
### Personalisation 2.0: From Keywords to Intent
The consumer journey is shifting rapidly as AI changes search behaviour. Instead of typing specific keywords, users are asking broader intent-driven questions such as “best gifts for a football fan.” This signals a move beyond keyword-based marketing towards semantic understanding of needs. Brands that rely solely on keyword targeting risk fading into the background. AI-powered personalisation allows for tailored experiences at scale, adapting dynamically to consumer context and behaviour. Tools like Google Performance Max illustrate how generative AI can produce on-the-fly ad variations aligned with intent rather than exact queries.
What This Means for Marketers:
– Rethink search strategies around consumer intent instead of just keywords
– Deploy AI personalisation engines to serve the “next best action” in real-time
– Design campaigns with multimedia storytelling to stand out in AI-powered results
### Commerce Media and the Connected Ecosystem
Retail and commerce media are expanding from direct sales into brand-building territory. As AI bolsters signal fidelity and targeting precision, commerce media is no longer just about closing transactions but also strengthening awareness and affinity. This growth coincides with a surge in connected TV spend, projected to reach nearly half of broadcast-related advertising within a few years. Both shifts reflect the increasing overlap between media, retail, and data-driven ecosystems, where AI acts as the connector.
What This Means for Marketers:
– Allocate budget to commerce media campaigns that serve both short-term sales and long-term brand goals
– Prepare for the convergence of retail and media networks by partnering with platforms offering robust AI targeting
– Integrate CTV spend into broader omnichannel planning to avoid silos
### Looking Ahead: Agentic AI and Quantum Acceleration
While current AI applications are already disruptive, the next wave looms with agentic AI and quantum computing. Agentic AI refers to semi-autonomous systems capable of managing complex customer journeys and executing actions with minimal oversight. Nearly one in three marketers exploring this technology expects quantum computing to play a role in unlocking its full potential within two years. Quantum-level computation could process massive datasets that today’s AI systems struggle with, opening new frontiers in predictive modelling, personalisation, and optimisation at scale.
What This Means for Marketers:
– Start building literacy around quantum computing’s potential impacts on data and AI strategy
– Experiment with agentic AI use cases such as automated journey orchestration
– Future-proof marketing stacks by designing with scalability and advanced computing in mind
### Final Take
AI is no longer a box-ticking exercise for innovation agendas. It is transforming both the front-end consumer experience and the back-end economics of marketing. Brands that lean into AI attribution, intent-based targeting, creative scaling, and localisation will build a competitive edge today. Meanwhile, the marketers paying attention to commerce media ecosystems and preparing for agentic AI will set themselves up for tomorrow. The pace of change demands both tactical pivoting in the short term and strategic investment for the long horizon. The balance between speed, trust, and adaptability will separate the leaders from the laggards.
