AI, Trust, and Personalization: A Harvard Business School Lecturer Explains B2B Consumer Strategy in 2026

Since AI is bringing fundamental changes in how consumers behave, it has become imperative to rethink strategies to deploy AI in B2B marketing—especially in consumer strategy. 

Planning, creating, and disseminating information is a traditional system B2B has long been preoccupied with, while sidelining personalization. 

Segmentation or categorization of consumers gets decided first, and then communication happens through predefined campaigns, and brands must change this in 2026.

Ad Pulse has published the “AI Buyer Files” study to spotlight ever-evolving B2B buyer behaviors as well as their buying funnels. 

While talking to InformaTech target, David Edelman, a senior lecturer at Harvard Business School, has consistently argued, personalization is no longer about targeting better—it’s about delivering customer-centric value at the exact moment it matters. And AI, paired with the right data, is what finally makes that possible at scale. 

We have a lot to tell—and to direct you toward—better AI adoption in B2B marketing and B2B consumer strategy in the AI era as we move into 2026. Let’s dive in. 

Personalization as a growth engine in 2026

Today, personalization is fast becoming the backbone of go-to-market (GTM) strategy, driven by the convergence of AI and data, and reshaping how brands identify, engage, and convert buyers. 

The business case for personalization is no longer theoretical. A survey conducted by David Edelman and BCG, covering 87 companies evaluated through BCG’s Personalization Index, revealed a blunt truth: companies that score high on personalization grow revenue 10 percent faster than their peers. 

That growth isn’t coming from prettier emails or smarter subject lines. It comes from a fundamental shift in how companies use information—moving from static segmentation to dynamic, value-based engagement. 

In modern GTM models, personalization means using data to create relevance that is specific, contextual, and timely. The focus isn’t “Who is this buyer?” but “What does this buyer need right now, and how do we show up with value?” 

The real shift in GTM is from segmentation to signals 

Traditional segmentation—industry, company size, job title—was built for scale, not accuracy. Today, buyers don’t move in segments; they move in signals. 

AI allows GTM teams to process massive volumes of multi-source information—combining internal interaction data with external signals such as content consumption, intent data, and market movements. This aggregation changes everything. 

Instead of guessing where a prospect is in their journey, AI can: 

• Detect behavioral patterns  

• Identify optimal engagement moments 

• Connect those moments to relevant value propositions, guidance, or support 

This is where personalization stops being a campaign tactic and starts becoming a decision-making system. 

ABM grows up: from targeting to serving

Account-Based Marketing (ABM) was supposed to fix B2B’s personalization problem. Edelman has been blunt about this evolution. ABM, he argues, has moved beyond simple targeting and is now about “servicing and providing value to the customer.” That shift is critical, and impossible to execute without AI and data working together. 

AI enhances ABM by: 

• Filling gaps in customer understanding using second-party data 

• Enriching first-party interaction signals 

• Enabling intelligent sales interactions with context-rich insights 

The endgame is arming sales teams with value-creating material: insights, narratives, and recommendations grounded in real customer behavior. 

Omnichannel: the personalization multiplier

Buyers interact with brands across multiple touchpoints, and personalization must extend consistently across these channels. Personalization combined with an omnichannel strategy can lead to a multiplier effect in real time. 

Analytical AI can identify what topics are capturing a buyer’s attention and predict which format or channel they’re most likely to engage with next. This matters because modern B2B journeys are fragmented, non-linear, and increasingly self-directed. 

AI-powered omnichannel strategies enable companies to: 

• Map cross-channel buyer behavior more accurately 

• Understand real buyer journeys instead of idealized funnels 

• Predict next-best actions based on successful interaction patterns 

Intelligence-based routing directs prospects to the most relevant experiences, offers, or interactions based on demonstrated interest and journey stage. 

Scaling contextual and relevant content

As personalization becomes central to B2B’s consumer strategy, content must evolve accordingly. 

B2B buyers need different information at different stages of understanding. Early-stage buyers need clarity; mid-stage buyers need validation; late-stage buyers need confidence. Scaling relevance across these stages manually is impossible. AI makes it feasible. 

This is where content strategy intersects with emerging practices like GEO and AIO content designed for prompts, context, and intent. 

AI supports content scaling by: 

• Identifying recurring question patterns across buyer networks 

• Optimizing content discovery as buyers rely less on direct website visits 

• Curating and generating contextually relevant content from existing assets 

The result is better-aligned content, delivered when and where buyers are actually looking. 

Reframing B2B consumer strategy around value

The convergence of AI tools with behavioral data—spanning first-party and second-party signals—is reshaping B2B’s consumer strategy. The signal-based approach allows organizations to move beyond static models. As a result, it allows them to respond dynamically to buyer needs, delivering information and guidance that supports decision-making in real time. 

As Edelman’s work suggests, the future of B2B GTM lies in the ability to use AI and data not as ends in themselves, but as enablers of personalization that create tangible value for buyers. 

Companies that succeed will be those that embed this capability across GTM, ABM, omnichannel engagement, and content strategy—aligning their operations around relevance, timing, and customer value. 

Cut to the chase

David Edelman, Senior Lecturer at Harvard Business School, conversed with the InformaTechTarget Group on the evolving nature of AI and data in B2B marketing. He focused on rethinking B2B consumer strategy in the AI era. 

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