Adoption
Phase: OperateTurn a bought tool into a habit people actually use well.
Adoption is what happens after deployment: people use the AI, use it well and fold it into how they work. It’s measured in real usage and results, not seats bought. An AI function with low adoption is cost with no return.
What it includes
- Measure real usage per team and person, not active licences.
- Spot where people get stuck and remove the specific friction.
- Create "how to use this for your job" playbooks per function.
- Close the loop: take friction back to whoever builds the agents.
When you need it
- You pay for licences almost nobody uses.
- A few enthusiasts use the AI and the rest never open it.
- The tool is fine but doesn’t change how the team works.
How it’s measured
- Real active users / target users.
- Usage frequency (daily, weekly) per function.
- Result per adopting user (time saved, cases resolved).
Common mistakes
- Measuring adoption by licences sold instead of real usage.
- Letting only the enthusiasts adopt and not helping the rest.
- Ignoring reported friction and hoping people "get used to it".
FAQ
- Are adoption and change management the same?
- Closely linked but not identical. Change management prepares the organisation for the change; adoption is the measurable result of people using the tool well and sustainably.
- How do you actually measure adoption?
- By real usage and results, never by seats bought. Ten people using AI daily for their work are worth more than a hundred with an open account they never open.
Related capabilities
Recent signals
Trends, practices, tools, cases and market data for this capability, with sources. Updated weekly.
Data
Salesforce: los agentes activados por organización casi se triplican y el tiempo medio de creación cae un 53%
Agentic Enterprise Index 2025-2026, telemetría de uso real de Agentforce entre febrero de 2025 y abril de 2026: las organizaciones que usan agentes de forma sostenida casi triplicaron los agentes activados a cierre de ejercicio y redujeron un 53% el tiempo medio de creación. Los agentes también se vuelven más versátiles: el agente medio ejecuta hoy seis skills frente a dos a comienzos de 2025, con picos de hasta 350% de expansión de su conjunto de habilidades en momentos de alta demanda. Nota metodológica: es la base instalada de un proveedor, no el mercado, y sesga al alza.
Salesforce · 2026-08-07 · E2El 86% de las empresas superó la fase piloto de agentes, pero solo el 34% confía en las decisiones que toman
Estudio de Forrester Consulting para Boomi: el 86% de las organizaciones ha superado la fase piloto con agentes de IA y solo el 34% dice confiar en sus decisiones. Algunas operan hasta 200 agentes simultáneamente en lo que el informe llama "purgatorio de pruebas de concepto": agentes que no llegan a conectarse con los sistemas empresariales necesarios para ejecutar decisiones reales. Entre las organizaciones con control agéntico, el 59% reporta mejoras de productividad, el 51% mayor innovación, el 46% capacidades reutilizables y el 45% automatización de tareas repetitivas.
IT User (estudio Forrester Consulting para Boomi) · 2026-08-06 · E2Missing any of these?
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