33% of B2B Teams Don't Trust Their Own Data — AI Widens That Gap

Forrester data shows 33% of B2B data and analytics decision-makers cite a lack of trust in data sources as a barrier to acting on insights; 29% distrust the analysis itself, and 28% lack the skills to interpret what the numbers say. Those are the numbers behind a new Forrester report, Close The Gap Between Insights And Impact, which argues a point most GTM (go-to-market) teams haven't priced in: AI can accelerate the flow of insights far faster than an organization can accelerate its ability to act on them.

Why does that matter? Because insights have a shelf life. A shift in buyer behavior, an emerging customer need, a change in campaign performance, or a competitive signal loses value when it takes weeks to travel through the organization and influence a decision. AI doesn't fix that latency — for teams already struggling to turn insights into action, it could widen the gap rather than close it.

What does the gap look like in practice?

Forrester lays out a scenario most revenue teams will recognize. AI detects a shift in buyer behavior, and marketing sees the signal first. Sales continues with the existing conversation. Customer success holds corroborating evidence from existing customers. Product teams sit on relevant usage data.

Everyone holds a piece of the picture, yet nobody changes course quickly enough. The business had the insight and still missed the opportunity. It's the classic silo problem, but AI multiplies the number of signals flowing through it — more analysis, more recommendations, at greater speed, with the same bottlenecks downstream.

Which questions should GTM leaders be asking?

Companies understandably ask where to deploy AI and which use cases create value. Forrester argues leaders should add a different question: how much faster can the business turn a new signal into a better customer or commercial decision?

The answer depends on the entire loop — signal to interpretation, decision, action, outcome, and adaptation. The report identifies what leaders must do across that loop:

• Identify which signals matter
• Challenge existing assumptions
• Make decisions
• Coordinate action across teams
• Determine whether the action produced the intended customer and business outcome

The loop can't stop at execution. Teams need to know whether a changed message improves engagement, whether a different sales approach advances an opportunity, whether an experiment changes customer behavior. Those outcomes become evidence for the next decision.

What separates winners in the AI race?

Forrester's framing: access to AI will spread rapidly, and so will the ability to generate and analyze enormous amounts of information. That means access itself stops being an edge — roughly like everyone getting the same radar while only some ships can turn.

Sustainable advantage will depend on what happens next: understanding what matters, mobilizing the right parts of the GTM organization, learning from outcomes, and continuously improving the next decision. The report extends earlier Forrester research on continuous learning and adaptation by connecting customer, market, and performance insights directly to decisions, actions, and measurable business impact.

For practitioners, the report's sharpest line is this: AI is compressing the time between signal and opportunity — businesses need to compress the time between uncovering insights and deriving impact from them. Expect the insights-to-impact gap, not AI access, to become one of the less obvious dividing lines in the AI race.