Envisioning 2025: The Future of AI Transformation

The past year has been marked by significant advancements in various AI-driven technologies and innovations. Research indicates that marketers are enhancing their skill sets and that companies are planning further investments in AI for the upcoming year. Transformations are in progress — but what does that imply in practical terms?

This signifies that numerous businesses will be onboarding new personnel to facilitate these changes. They’ll be employing data and other marketing resources in innovative ways to stay ahead in this dynamic landscape. Below are some key areas where businesses will be evolving and utilizing AI solutions and strategies in 2025.

Establishment of AI Councils and Chief AI Officers

With the growing popularity of AI tools and methodologies, companies will look to adapt through hiring and organizational restructuring. Many will establish AI councils or appoint Chief AI Officers to steer their AI initiatives.

“I anticipate these efforts and hires will surge in 2025,” noted Eric Williamson, CMO at CallMiner, a company specializing in conversational intelligence.

Williamson elaborated: “On one hand, informed adoption choices can ensure that your AI investments yield desired outcomes, whether it be enhancing customer experiences, boosting operational efficiencies, aiding contact center personnel, or reaching other objectives. Conversely, having too many decision-makers involved can slow procurement processes, resulting in organizations lagging in AI advancements. Companies must strike a balance between agility and prudent AI integration to maintain their competitive edge.”

Learn more: How to pivot AI adoption to emphasize results over tools

Enhancing Data Analytics and Enrichment through Automation

One of the primary methods marketers will harness AI in 2025 is through data enhancement and analysis. For example, AI technologies can significantly cut down the time required for identifying and scoring ideal customer profiles (ICP) — effectively pinpointing those customers most likely to make substantial purchases.

“I’m thrilled to see how AI is revolutionizing the approach to ICP analysis and account data enrichment in B2B marketing,” stated Gurdeep Dhillon, CMO at Contentstack, a flexible CRM platform. “The fresh methodologies for identifying ICPs and automating account data processes will empower marketing and business development to scale operations and utilize their technology stack with greater efficiency.”

The capacity to swiftly analyze and activate data using AI capabilities will impact the entire marketing technology ecosystem. As this progresses within customer experiences, marketers will gain the ability to implement hyper-personalization. They’ll have access to real-time insights and content generation from generative AI to promptly deliver tailored messages and interactions.

“The leading application I see is the actual realization of personalization,” said Dhillon. “Combining real-time audience insights with generative AI content will enable hyper-personalization at scale.”

Dhillon further observed: “Marketers will leverage advanced digital experience platforms that include CMS, personalization engines, real-time customer data platforms, large language models, along with retrieval-augmented generation and automation tools to achieve this. The most significant hurdle marketers will face will be establishing the initial personalization framework. While AI will aid in refining and optimizing, the foundational strategy set by the team is crucial.”

Learn more: The AI-driven route to smarter marketing

Revamping Content Optimization for GenAI Retail Search

For those in the e-commerce sector, AI is already reshaping the industry with generative AI search solutions like Amazon RUFUS. Customers are not simply employing keywords; they are engaging in more conversational searches. This entails asking general inquiries, detailing shopping occasions, comparing products, and posing follow-up questions.

To thrive and secure top search rankings, marketers will need to optimize their content to address a wider array of contexts.

“Generative AI retail search will enhance the emphasis on content optimization and necessitate more frequent content updates,” said Megan Harbold, VP of strategy and growth at Skai, an omnichannel marketing platform. “Generative AI searches like RUFUS will transition from test phases to integral parts of online shopping behavior.”

Harbold explained: “Marketers will be required to modify their keyword harvesting practices, improve product content optimization, and contextually target audiences to remain relevant as models evolve their search definitions. This will demand increased technological investments to enhance product content and allow for dynamic content and creative adjustments as contextual targets evolve.”

Incorporating Causal AI

In the upcoming year, AI will not only expand analytics and content generation but will also play a crucial role in scenario analysis and decision-making. This category of AI tools is known as “causal AI.”

Learn more: Understanding why causal AI is essential for smarter marketing

“Undoubtedly, in 2025 and beyond, considerable focus will be placed on the integration of causal AI with generative AI and large language models,” stated Mridula Rahmsdorf, CRO at IKASI, a company specializing in causal AI solutions for the retail and finance sectors. “Current machine learning models remain highly effective across various fields and are due for enhancements next year. The integration of causal AI with these existing AI forms will significantly boost precision and improve decision-making, especially when these decisions must consider multiple, sometimes contradictory indicators based on correlations rather than direct causal links.”

Rahmsdorf continued: “The combination of causal AI with other AI technologies will also enhance the trustworthiness of generative AI by providing a comprehensive understanding of how various factors interact. Consequently, expect generative AI to better present scenarios that yield realistic outcomes, leading to more coherent and pertinent results.”

“As the integration of causal AI deepens within broader AI technologies and confidence in causal inference rises based on reliable outcomes, we can anticipate a marked increase in its application across different industries to achieve tangible impacts.”