2026 Marketing Operations Predictions

Marketing is at the forefront of AI adoption in the enterprise, but mostly as a tool for drafting content. Some brands are seeing success with heavily optimised custom models, while other brands produce content that requires heavy re-writing before it can be used. Translation is another discipline with strong AI uptake with similar results. Lower cost and quicker turnaround times mean that human translation is being relegated to more complex scenarios.

AI automation moves beyond the hype phase

Trouble is, content generation doesn't justify the stratospheric valuations behind the AI bubble. Investors need AI automation to make a return. A lot of effort has gone into creating agentic workflows. So far, outputs and business benefits have been relatively mixed. AI technology is being used for research and content summarisation, but mostly through the familiar chatbot interface. AI firms have bigger ambitions.

AI automation was the story of 2025. Yet, it remains a long way from becoming a practical reality for many marketing teams. That's far from a bad thing. Many widely touted use cases for the technology make little sense. However, AI chatbots are a day-to-day reality in many businesses, and marketers are adopting them to drive better internal efficiency and higher customer engagement. Many of these pilots are an extension of existing technology trends.

Marketers have been experimenting with chatbot based data collection for a long time. The concept is how Drift made their name. Generative AI makes chatbots more useful because it allows them to interpret vague language and understand the underlying context. As an automation tool though, they are somewhat limited. That's one of the key reasons AI startups have seen more success with vibe coding and developer assistants.

AI startups penetrate the enterprise

Vibe coding has its place within the martech landscape, primarily as a mechanism for quickly generating interactive content and internal prototypes. While not the primary audience for vibe coding technology, ops teams still benefit when using it for simple tasks. Security and reliability concerns will hold back adoption among non-developers for a while longer.

Instead, VCs are betting on a new generation of domain-specific AI apps to displace the existing SaaS martech stack. However, AI-based apps remain a niche concern. Although there are exceptions. Clay in particular is seeing strong enterprise adoption. An AI data enrichment platform, Clay has been the most hyped martech platform of 2025. Pioneering a business model that has plenty of imitators, among both new startups and established vendors. In doing so, they've accelerated a trend which has been building for a while.

AI becomes a data enrichment solution 

Marketing leaders have long believed that stagnant marketing automation platforms were holding marketing back. Their outdated data model and restrictive workflow capabilities are harming data quality and hampering sales alignment. ABM platforms such as 6sense pitched themselves as the solution, but their feature set is far too narrow to be a long-term solution. 6sense and Demandbase are still very much seen as intent data providers and predictive scoring models, rather than as an orchestration solution.

Clay have been able to bridge the gap. Combining AI research tools with deep data management capabilities allows marketing ops teams to better align the marketing database with business needs. It's a much more flexible approach than centralising everything in a rigid CRM system optimised for sales or an inflexible marketing automation platform. That's not why people love Clay though. AI allows marketers to break free of the inaccuracies and inconsistencies of the established data brokers.

Existing data management tools are adding AI enrichment features to their platforms. Adoption of these features is growing as marketers become frustrated with the limitations of mainstream data vendors. Getting a good match rate from the most widely used data sources is far too expensive for most companies, and that's before considering whether the purchased data is accurate. AI allows resource constrained ops teams to roll their own data enrichment framework, rather than relying on the least worst data broker. More importantly, AI-enabled data enrichment is a useful answer to two of the biggest board-level mandates of recent years.

Attribution remains a top priority

Data is the lifeblood of the business. Yet, most C-level executives have spent years doing very little to address the problem of poor data quality. AI has pushed that problem to the top of the agenda, which is exactly where marketing operations want it to be. In turn, ops teams need to expand the scope of their efforts - which have mostly focused on gap filling account data until now. If marketers are serious about AI, they need to go beyond that and look at filling the gaps in attribution information too.

If AI is to be successful, it needs real time updates about the success of different campaigns and different content. Google and Meta are already using AI to automatically optimise ad campaigns. Martech platforms want to bring the same techniques to content marketing. Predictive content and adaptive nurturing is an old dream that has been re-awakened by generative AI. Except this time, your CMO wants it too.

Marketing has long struggled to prove the link between campaigns and revenue. An entire industry has grown up around automating attribution. Yet, not everyone wants a black box reporting solution like Bizible. The CFO doesn't just want ROI, he wants to know how that ROI was calculated. Thankfully, the convergence of AI driven data modelling and better ad tech integrations is helping break down reporting silos. ABM even helps with the age-old sales alignment disconnect.

BDRs get more help

Sales are struggling. Deal sizes have collapsed since the pandemic, while sales cycles have extended. It's a lot harder to close opportunities than it used to be. That's a serious problem for marketing, as well as for sales. In 2026, revenue teams will start using AI to drive increased sales productivity. The leading CRM vendors already offer a host of sales agents, while a host of startups are pitching to replace your BDR team.

Sales is the next frontier for AI. Some brands are already experimenting with automated outreach or sales chatbots. These pilots are mostly intended to supplement existing BDR teams, allowing them to focus on higher value deals. CRM vendors are integrating sales coaching into their products. Meanwhile, overly generic sales emails are one tactic that is ripe for LLM driven content personalisation. It's merely a matter of getting the balance right, so that campaigns aren't seen as irrelevant or creepy.

AI mandates become more realistic

Marketing will need to contribute to this AI led effort to drive increased sales support, mostly through better data sharing and better content support. Given the low productivity and high turnover inherent to most BDR teams, AI enablement is a real opportunity to drive increased conversion rates. Just don't use AI as the main touchpoint for high value prospects. The human connection is still very important in closing deals.

Expect to see a lot of AI doom talk next year. The limitations of existing AI technologies have become abundantly clear. C-level execs are starting to take notice, as are the LLM model makers. The leading AI labs have new techniques which are in the pipeline, but it's not clear if they will reach the market in 2026. In the meantime, business teams will still be expected to embed further automation into their processes. The drive for increased productivity has deep macro-economic roots. It isn't going away anytime soon.

The Future of Marketing Operations

Marketers want to move faster, but need the operational support to deliver it. CMOs want to deliver smarter campaigns, but need the data foundations to make that happen. The business wants to see more ROI on marketing spend, but needs the reports to prove it. Marketing ops is being asked to do more, and to take a bigger role in the organisation. Read the CRMT Digital 2026 predictions to see how marketing operations will evolve to meet those new business needs.

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