AI transformation: 2025 predictions

There’s been a lot of potential in the last year with all kinds of AI-powered tools and updates. This is also shown by studies traders refine and organizations they plan to continue investing in AI in the coming year. There’s a lot of transformation going on — but what does that mean in practice?

This means that many companies will be hiring new workers to support the changes. And they will use data and other marketing tools in new ways to stay competitive in this changing environment. Here are some of the areas where organizations will adapt and use AI tools and processes in 2025.

AI councils and AI chief officers

With the influx of AI-powered tools and processes available in the market, businesses will look to adapt through new hiring and restructuring. Many companies will establish AI councils or hire chief AI officers to lead the AI ​​transformation.

“I expect these initiatives and hiring to increase in 2025,” said Eric Williamson, director of marketing for conversations at CallMiner.

Williamson explained, “On the one hand, educated adoption decisions can help ensure that your AI investments deliver the value you expect, whether that’s improving CX, increasing operational efficiency, supporting contact center agents, or other goals. On the other hand, involving an unnecessary number of decision makers can slow down or even stop procurement processes, causing organizations to fall behind the AI ​​curve. Organizations must find a balance between agility and responsible AI adoption if they want to remain competitive.”

Dig deeper: How to reshape AI adoption to focus on outcomes, not tools

Automating analytics and data enrichment

One of the primary ways marketers will use AI in 2025 is to enrich and analyze their data. For example, AI-powered tools can reduce time and increase efficiency in scoring and identifying ideal customer profiles (ICPs) — those customers or prospects most likely to be heavy spenders.

“I’m excited about how AI is helping to modernize the way marketers, especially in B2B, approach the age-old problem of ICP analysis and account data enrichment,” said Gurdeep Dhillon, CMO of Contentstack, a composable CRM. “New ways to approach determining ICP, as well as automating account data and research, will help marketing and business development scale and leverage their technology stack more effectively.”

The ability to analyze and quickly activate using AI-powered capabilities will have implications across the entire martech stack. As it relates to customer experience, marketers will have the firepower to implement hyper-personalization. It will have real-time data insights and genAI content production to rapidly deliver hyper-personalized messages and experiences.

“The number one use case I see is finally delivering on the promise of personalization,” Dhillon said. “Real-time audience and content insights combined with on-brand genAI will make hyper-personalization at scale a reality.”

Dhillon added, “Retailers will use modern DXPs with CMS, Personalization Engine, real-time CDP, LLMs plus RAG (augmented retrieval generation)and automation tools that can achieve this. The biggest challenge marketers will face will be getting the personalization logic in place to begin with. AI will help improve and optimize, but the team needs to set an initial strategy.”

Dig deeper: The AI-Powered Path to Smarter Marketing

Redefining content optimization for genAI retail search

If you’re in e-commerce, AI is already changing the game through genAI search tools like Amazon RUFUS. Shoppers don’t just use keywords to find products and brands, they search more conversationally. This means that customers ask general questions, describe shopping opportunities, ask about product comparisons, and ask follow-up questions.

To keep up and remain a top scorer in this environment, marketers will need to optimize content to cover a wider range of contexts.

“GenAI retail search will bring a new focus on content optimization and increased content refresh requirements,” said Megan Harbold, vice president of strategy and growth for omnichannel marketing platform Skai. “GenAI search, like RUFUS, will move from testing to the normal flow of online shopping behavior.”

Harbold explained: “Marketers will need to evolve how they collect keywords, optimize product content and contextual targeting to stay relevant as models refine search definition. This will result in increased technology investments to optimize product content and dynamically change content and creative as contextual goals are refined.”

Integrating causal artificial intelligence

In the new year, AI will not only be used to augment analytics and content creation. AI will also be used to analyze scenarios and assist in decision-making. This is a category of AI tools called “causal AI.”

Dig deeper: Why causal AI is the answer for smarter marketing

“Undoubtedly, in 2025 and beyond, a lot of energy will be spent on integrating causal AI with generative AI and large language models,” said Mridula Rahmsdorf, CRO at IKASI, a causal AI company with tools for traders and finance. services. “Current machine learning models are still extremely useful in multiple disciplines and an upgrade is planned in the coming year. Causal AI—integrated with these forms of AI—will greatly improve accuracy and improve decision-making, especially when decision-making involves multiple and seemingly conflicting indicators based on correlations rather than causation.”

Rahmsdorf adds: “The integration of causal AI will also increase the reliability of generative AI by giving it a deeper and broader understanding of how different factors interact and influence each other. As a result, turn to generative artificial intelligence that will be more adept at presenting scenarios that reflect realistic outcomes, leading to more coherent and relevant results.

“As causal AI becomes more deeply integrated with other AI technologies and confidence in causal inference based on accurate results grows dramatically, there will be a sharp increase in its use to drive material impact in a variety of use cases across verticals.”