The 5 AI investments marketing teams should make in 2026

 

The 5 AI investments marketing teams should make in 2026

Marketing leaders aren’t just facing a technology shift – they’re facing a behavior shift. Buyers are changing how they do product research, who they trust, and what they expect from a digital experience.    So a marketer's role shifts from broadcasting messages and optimizing isolated channels to architecting self-serve buying experiences. They’ll spend less time manually tweaking bids, writing generic content, or pushing people from the top of the funnel into a sales cadence – and more time designing the information, data, and journeys that let buyers make up their own minds.   HubSpot’s SVP of Marketing, Kieran Flanagan, says there are 5 AI-powered investments CMOs should make in 2026 to capitalize on this shift.

1. Redesign your paid engine around data quality and creative volume Paid advertising is moving from manual optimization to model-driven systems. Tools like Google P-Max automate targeting and asset generation, but only perform well with strong data inputs.   “It's kind of doing the job of a paid marketer,” Kieran says.   Three things to keep in mind: The cleaner your first-party data, the better. These platforms use your data to identify micro-audiences, so poor data leads to broad, expensive targeting. Do more creative testing with the same resources. AI tools will allow you to generate 40-50 variations of an image or video ad for the cost of producing one. Your role will shift from operator to orchestrator. Instead of manually optimizing campaigns, teams will focus on data pipelines, creative workflows, and testing. Media buying becomes a strategy problem, not an execution problem. Kieran’s tip: Focus your paid marketing on these kinds of efficient scalable approaches, learn what works, and optimize quickly. Your paid marketer's job becomes way less about individual campaigns and manual tuning and more about designing end-to-end experiences that AI can operate.

2. Pivot to AI-driven inbound prospecting Cold outbound email is oversaturated because AI has made it easier for everyone to send more outreach, which vastly reduces its effectiveness. The performance of these campaigns is plateauing.   But inbound prospecting – aka, reaching out when someone has already shown interest in some way (visiting your site, browsing product pages, or engaging with content) – still delivers strong results.   This approach works because the message matches the moment: the user already cares.   “It just comes down to: do you have good data sources and can you prompt well?” says Kieran.   Kieran’s tip: Don’t waste effort on an already noisy strategy. If you have meaningful intent data and an AI-powered personalization layer, this is a high ROI investment.

3. Focus on content that LLMs find valuable Last week we wrote about why GEO might be hype – but Kieran disagrees. With ChatGPT or Google’s AI Overviews (the only two AI experiences worth optimizing for, in Kieran‘s opinion), buyers don’t use keywords to find something like they have in the past. They articulate context, constraints, and preferences.    “People conversate around your product and service differently than they search about it via keywords,” Kieran says.    There are thousands of ways a person could ask questions about your product or service, which means a few things for marketers:   1. Search visibility now depends on answering intent, not ranking for keywords Instead of writing five product pages to cover the core keywords you want to rank for, you need 100-200 targeted pieces of content to cover the nuanced, scenario-specific ways buyers describe their needs to AI, for example: “What’s the best CRM for a three-person solar sales team?” “I need a scheduling tool for hourly workers rotating weekend shifts” If your site doesn’t answer a question, AI engines assume you’re irrelevant. So content just became king.   2. AI engines rely on citations, not links LLMs infer authority by scanning how often you’re mentioned across the web, not just where you’re linked. So mentions on high-trust sites influence which products show up in model-generated recommendations.   3. Your pages must be structured for machine interpretation AI models parse pages differently than crawlers. Clear headings, consistent schema, and explicit descriptions help models find and summarize your value to users.   Kieran’s tip: AI search is becoming the first step in B2B research and people don’t want a list of links anymore: they expect tailored answers. Teams that invest early will own the top of the AI funnel and starve competitors of visibility.

4. Build a creator-led content engine AI-generated content is starting to outnumber human-created content from brands. As a result, buyers are paying less attention (and giving less trust) to branded content and relying more on people they can connect with.   “Creators are going to become a bigger and bigger part of your marketing strategy,” Kieran says.   Three things he’s seeing: Creators produce the human signal buyers crave. In an AI-saturated content landscape, personality, perspective, and lived experience stand out. So creator-led channels – like YouTube, TikTok, and LinkedIn – become massive brand assets. Founder-as-creator strategies outperform brand accounts. Many high-growth companies now grow the founder’s audience faster than the company’s because buyers want to learn from a person. Creator partnerships strengthen the paid mix. With Meta and Google CAC rising, creator ads often deliver stronger engagement and trust at lower cost. Kieran’s tip: This isn’t a new approach for the AI era – influencer marketing has been on the rise in response to waning interest in traditional advertising. But it’s going to become more important for building brand trust in the AI era than before. Your job as a marketer is to deliberately create and distribute voices consumers can relate to and trust – not just campaigns.

Bleeding-edge bonus: Pilot multimodal AI agents Multimodal AI (aka voice, video, and visual reasoning) is advancing quickly and Kieran believes it will fundamentally change how buyers interact with companies online in 2026.   A multimodal agent can: Speak naturally with a site visitor Display product visuals and walkthroughs Answer technical or workflow-specific questions Qualify the buyer Hand off to sales when appropriate This effectively conducts an early-stage sales call without human involvement.   “AI will bring about the entire sales process earlier in the funnel,” Kieran says.    Kieran’s tip: There is a large population of buyers who do not want to talk to sales but want accurate information about your product. Multimodal agents unlock that demand. Your job as a marketer becomes more about feeding AI and the buyer everything they need to arrive at decisions on their own.

How to lead your marketing team into the AI era Search, content, paid media, and prospecting is getting an AI facelift and the winning brands will be the ones that seize the opportunity. Here’s Kieran’s parting wisdom for marketing leaders: Build team-level curiosity. AI is rewriting all marketing workflows, so teams need to explore, test, and learn continuously. You can’t afford to have anyone using the old playbook. Choose 1-2 bets to make in Q1. Concentrate resources on a few key areas where you feel strongly that AI can meaningfully shift results for your team. Don’t try to pilot it on all Jan 1. Lead from the front. If you want an AI-enabled team, become the most informed, experimental practitioner in the room. You as the leader need to be the most proficient and prolific AI user. TL;DR – the modern AI-powered marketer will move from “talking at” the market to landscaping an environment in which informed decisions happen organically for buyers.

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