As we step into 2026, AI tools that were cutting-edge just a year ago have now become ingrained in the workflows of brands and agencies. Marketers are leveraging AI for various tasks ranging from creating text and images to analyzing data, targeting consumers, and boosting engagement.
However, this rapid advancement has introduced new challenges such as determining the optimal way to incorporate AI into internal processes, dealing with the complexities surrounding AI’s agency, and grappling with the implications of AI-driven search functionalities.
In its investigation, Digiday delves into how marketers are maneuvering through the opportunities and obstacles presented by AI, as it evolves into an essential component of their toolkits.
Through a survey conducted by Digiday+ Research involving 142 professionals from brands and agencies, insights were gathered on their utilization of AI as well as their current and future investments in the technology. Additionally, individual interviews were conducted with marketing and technology executives overseeing AI investments and application development.
The survey conducted by Digiday revealed a significant rise in marketers’ adoption of AI technology over the years. In 2022, 44% of professionals from brands and agencies reported investing in AI technology. This percentage increased to 57% in 2023, 71% in 2024, and peaked at 86% in 2025.
The mounting importance of AI for marketers is also evident in the growing number of companies appointing chief AI officers in recent years.
Furthermore, consumer acceptance of AI has witnessed substantial growth leading many brands to routinely incorporate AI into consumer-facing applications.
Nevertheless, despite the increasing complexity of AI technology, some marketers expressed concerns about the lag in adequately training employees on utilizing AI tools effectively compared to its overall adoption rate.
When organizations, including marketing teams, rush to adopt AI technology without a fully developed plan on its application, a gap often emerges between the investment made in AI tools and the returns garnered from such investments.
The majority of marketers are seen integrating out-of-the-box AI tools into their workflows rather than developing tools alongside existing large language models (LLMs). This preference can be attributed to the costs associated with customizing AI tools through existing LLMs or building and training proprietary LLMs, coupled with the learning curve involved in implementing these options.
Digiday’s survey highlighted that copy generation remains the most commonly used application of AI by marketers for two consecutive years. The survey also noted an increased use of AI for multimedia generation among marketers in 2025.
Despite wider adoption of AI applications among marketers, both H&M and Puma faced criticism for eliminating the human touch from their creative endeavors.
L’Oreal’s CREAITECH lab exemplifies another scenario where they leverage AI to create localized visuals and campaign assets from simple text prompts using models like Google’s Imagen 3 and Gemini. This strategic move aided in cost reduction and accelerated storyboarding, concept generation, and visual testing for the company.
When asked about specific types of AI technology utilized across different workflows, generative AI was found to have higher adoption rates than predictive AI among brands and agencies. Interestingly, marketers appear to use AI less frequently in workflows related to media buying and planning as well as financial analysis.
While agentic AI has gained traction as a buzzword within the marketing realm, Digiday’s survey indicates that it still lags behind predictive and generative AI concerning adoption among marketers. Numerous barriers hinder widespread adoption of agentic AI within marketing teams despite its potential use cases.
The landscape of AI-powered search applications is expanding rapidly with Google introducing functions like its AI Overviews search feature in 2024 followed by AI Mode in 2025. Although relatively new compared to traditional search results, marketers are beginning to feel their impact significantly.
Marketers face challenges relating to understanding how brands appear in AI-generated search results which signifies an obstacle needing attention amidst evolving trends in AI-driven search strategies such as GEO (generative engine optimization) and AEO (answer engine optimization).
Several industry executives interviewed by Digiday emphasized the need for brands to adapt their earned media strategies and organic social media tactics for optimal visibility within evolving frameworks of AI-generated search results.