Decentralizing B2B marketing: more voices, stronger foundations

AI makes content easier to create. The real opportunity is to connect expert voices with shared brand and product intelligence — without losing trust.

Lately, I’ve come across the idea of decentralizing marketing communications. Is it a thing? And, more importantly, is it a new thing?

In B2B, impact has always come from involving your experts. Buyers of industrial products and enterprise software need more than polished messaging. They need verified research, industry knowledge and product claims they can trust — particularly when technical products and complex buying processes are involved.

Engineers, product specialists and sales teams have long been essential to that work. What is changing is how easily they can take the initiative themselves. With GenAI and AI-powered tools, producing decent content is becoming faster and cheaper. Content is no longer scarce. What remains scarce is what it is made from: expertise, evidence and strategic intent.

I’ve heard of companies building websites with Slack Code, where updates can be made by people across the company. Salesforce’s announcement describes a collaborative environment for teams and AI coding agents, with shared plans, code diffs and live previews. For marketing, that raises a familiar question with new urgency: when anyone can publish, what gets published — and who checks it?

Are we moving towards centralizing brand and product intelligence so we can decentralize content creation and outbound activity? I think this is the more interesting shift. It is not about removing marketing from the process. It is about making the organisation’s knowledge usable beyond the marketing team, while keeping a shared strategic foundation.

Looking at companies at the forefront of this shift, implementation is not easy. But the momentum is here. For me, four priorities stand out.

1. Give AI a strategic brief

Educate the tools with your strategy, positioning, tone, visuals, templates, product claims and the proof behind them. Think of this as your creative brief to AI. Without that foundation, faster production simply scales the wrong message. Garbage in, garbage out still applies.

2. Build security and compliance in from the start

Data security, compliance and strategic direction cannot be an afterthought. Decide what information can be used, what claims need evidence and where human judgement remains essential before opening up production.

3. Rethink approvals and governance

A more distributed model needs clear ownership. Who validates technical accuracy? Who checks the evidence behind a claim? Who approves publication? The approval structure has to support expert contributions without losing accountability.

4. Bring people into the shift

This is a change in how people work, not just a new set of tools. It calls for unlearning, upskilling and a willingness to be challenged — across marketing, product, engineering and sales.

Scary? Yes. Worth it? I think so.

For B2B, this can create the strong alignment we need between marketing and expertise teams. Powerful, compliant product claims and research that buyers trust can come to life at scale — not because everyone is saying more, but because more people are working from the same intelligence.

The opportunity is not simply to decentralize communications. It is to connect expert voices to a stronger shared foundation. What do you think?