The Marketer’s Guide to AI in 2026: Key Takeaways
As 2026 begins, artificial intelligence has moved from being a competitive advantage to a core part of everyday marketing workflows. Tools that were once considered cutting-edge are now embedded across creative production, analytics, targeting and customer engagement. However, rapid adoption has also introduced new challenges around integration, training, costs, trust and the changing nature of search.
AI adoption is high, but expertise is lagging
AI investment among brands and agencies has grown steadily, reaching 86% in 2025. Many organisations have appointed chief AI officers, reflecting AI’s growing strategic importance. Consumer adoption has increased in parallel, with brands using AI for personalised offers, chatbots and customer-facing experiences. Despite this growth, employee training and upskilling have not kept pace. Many marketers understand AI tools at a basic level but are not yet using them to their full potential, creating gaps between investment and return.
Out-of-the-box tools dominate
Most marketers rely on ready-made AI tools rather than building proprietary solutions. Eighty-five percent of surveyed professionals use out-of-the-box AI, while fewer are developing tools on existing large language models or training their own. Cost, complexity and skills shortages are key barriers. Increased collaboration between major platforms, such as Google and Adobe, has made AI more accessible and flexible, allowing brands to stack tools rather than rely on a single solution.
AI’s role within marketing workflows
Copy generation remains the most common AI use case, followed closely by multimedia creation such as images, video and music. Brands including H&M, Puma and L’Oréal have used AI-generated creative at scale, gaining efficiency while also facing criticism over reduced human involvement. Beyond creative work, AI is increasingly used for data analytics, reporting and coding, delivering significant productivity and cost savings. Across use cases, marketers emphasise the importance of identifying specific problems first and applying AI selectively, rather than adopting tools without a clear strategy.
Generative AI leads, predictive AI supports
Generative AI is more widely adopted than predictive AI, particularly in creative production, marketing and communications. Predictive AI is most commonly used for measurement and KPI analysis. While AI has transformed many workflows, marketers remain cautious about relying on it for media buying, planning and financial analysis, although smaller teams may benefit more from automation in these areas.
Agentic AI shows promise but faces barriers
Agentic AI, which can autonomously anticipate needs and take action, remains less widely adopted. Trust, governance and technical complexity are major barriers, as errors can cascade through automated processes. Marketers are experimenting with smaller, supervised tasks to build confidence, but widespread adoption will depend on improved integration, clearer controls and stronger safeguards.
AI-generated search is reshaping visibility
AI-powered search tools from Google, OpenAI and others are changing how consumers find information. Many brands are experiencing reduced website traffic due to “zero-click” search, where answers are delivered directly within AI-generated summaries. While the impact varies, marketers report challenges in tracking visibility and attribution within AI search platforms. Traditional search remains relevant, but brands must adapt to changing consumer behaviour.
GEO and AEO become essential strategies
Generative Engine Optimisation (GEO) and Answer Engine Optimisation (AEO) are emerging as the AI-era equivalents of SEO. Brands are experimenting with conversational content, FAQs and structured data to ensure AI systems can easily understand and recommend their products. While many organisations are still unsure how to approach GEO and AEO, experts agree that success often starts with optimising existing content rather than creating entirely new material.
Looking ahead
AI is no longer optional for marketers. As tools continue to evolve, success in 2026 will depend on clear strategy, thoughtful integration, human oversight and a strong understanding of how AI affects discovery, creativity and consumer trust. The next phase of AI adoption will be defined less by experimentation and more by how effectively brands turn capability into measurable value.
Source: digiday.com