AI-Powered Personalisation: 2026’s Marketing Efficiency Catalyst

AI-powered personalisation is becoming a key focus for marketing teams in 2026. This trend is happening now because of the significant advancements in machine learning and natural language processing. Vendors like Salesforce and Adobe are investing heavily in AI-powered personalisation capabilities, making it more accessible to marketing teams. What sets this trend apart from past cycles is the level of sophistication and accuracy that AI can now bring to personalisation efforts. Gone are the days of basic segmentation and generic messaging. With AI, marketers can create highly tailored experiences that resonate with individual customers. Early adopters of AI-powered personalisation, such as Amazon and Netflix, have already seen significant returns on investment. They’re using tools like AgilOne and Selligent to create complex customer profiles and deliver personalised content at scale. On the other hand, laggards are still relying on manual processes and basic personalisation techniques, which can be time-consuming and ineffective. To get started with AI-powered personalisation, marketers should follow a three-step adoption framework. First, they need to assess their current personalisation capabilities and identify areas for improvement. This involves evaluating their data management systems and customer engagement platforms. Second, they should invest in AI-powered personalisation tools that can help them create complex customer profiles and deliver targeted content. Vendors like SAP and Oracle are offering robust solutions in this space. Third, marketers need to develop a testing and measurement framework to gauge the effectiveness of their AI-powered personalisation efforts. This involves setting clear KPIs and using analytics tools to track customer engagement and conversion rates. For more martech analysis, tools coverage and strategy guides, visit MartechXpert — your independent source for marketing technology insight. Now, there are cases where AI-powered personalisation may not be the best approach. For example, if a marketing team is still struggling to get their data management systems in order, it may be premature to invest in AI-powered personalisation tools. Similarly, if a brand is focused on building broad awareness and doesn’t require complex personalisation, they may not need to prioritise AI-powered personalisation. In such cases, it’s better to focus on building a solid foundation in data management and customer engagement before jumping into AI-powered personalisation. Overall, AI-powered personalisation is a trend that’s here to stay, and marketing teams that adopt it early will be well-positioned to drive efficiency and growth in their campaigns.

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