The Coordination Gap

Most AI in customer service was built to close a simple question without a human ever getting involved. B2B service rarely works that way. Issues move across teams, systems, and people, and a tool designed for one-and-done consumer support tends to create new problems instead of solving them.

This Harvard Business Review Analytic Services briefing paper, sponsored by Front, looks at what happens when transactional AI tools meet the multi-team reality of B2B support, and gives leaders a way to evaluate whether a tool is actually built for their environment.

What you’ll get:

• A breakdown of why B2B companies are adopting AI in customer service faster than any other function, and why so few have scaled it past early pilots

• Four recurring failure modes that show up when tools built for single-agent, single-interaction support get deployed on multi-team B2B work

• Three questions to pressure-test any AI tool before you buy it: does it preserve visibility, support multi-party workflows, and strengthen human judgment rather than replace it

• Real examples from B2B operators, including Countsy and Essentialist, who rebuilt their AI approach around coordination instead of deflection

• Front CEO Dan O’Connell’s sponsor perspective on what he’d ask before trusting any AI tool with account relationships that took years to build