Change management in marketing, data, and AI: how to plan for adoption
Luís Paravato
Change management organizes the work needed for people to adopt new processes, responsibilities, and tools. In marketing, data, and AI, it connects technical implementation to teams' daily work.
An available platform does not mean an adopted process. The team needs to understand what is changing, how to perform tasks, and where to find support. Leadership needs to provide the conditions for that use.
Your company should track adoption through use in daily activities and the quality of outputs. Training and login counts indicate implementation effort, but do not prove that the new workflow works.
Explain the change in terms of the work
Communication presents the purpose, affected activities, and expected result. Each team needs to understand how its routine will change.
When implementing a CRM, for example, staff need to know which records will be required, who will use the information, and how sales activity will be tracked. The rationale becomes clearer when tied to specific tasks.
It is also necessary to communicate the stages, responsibilities, and transition conditions. Known uncertainties should be addressed explicitly, with someone assigned to resolve them.
How to identify the conditions for adoption
| Aspect | What to check |
|---|---|
| Understanding | Do people know which activity is changing and why? |
| Access | Are user profiles, equipment, and information available? |
| Skills | Can the team perform the planned tasks? |
| Time | Is there room in the daily workload to learn and adapt? |
| Support | Is someone responsible for questions and failures? |
| Management | Do leaders use the process and monitor its application? |
Lack of use calls for an analysis of these conditions. Labeling every difficulty as individual resistance overlooks design flaws, workload, and technical limitations.
Leadership's role
Leaders help define the process and use the information it produces. Requesting parallel reports after implementing a system perpetuates duplicate work and reduces confidence in the chosen workflow.
Objectives and incentives also need to reflect the change. A team evaluated solely on speed will struggle to dedicate time to the recordkeeping needed for data quality.
Managers identify obstacles and arrange corrections. Accountability for compliance should reflect the conditions actually provided to people.
Training with real tasks
Training needs to replicate everyday tasks. Recording an opportunity, querying a database, and reviewing an AI response require practice with representative situations.
Support materials explain steps and exceptions. Users need to be able to consult these references after the training session.
For AI applications, preparation includes checking responses, protecting information, and escalating errors. Users should understand the tool's operating limits and the cases that require additional review.
Pilots and phased implementation
An initial group tests the process within a controlled scope. Selection considers a range of tasks and conditions of use, avoiding a pilot made up only of experienced users and simple cases.
Monitoring records failures, questions, task completion times, and output quality. Adjustments are made before extending use to other teams.
The transition establishes when the previous workflow will end and how historical records will be preserved. Maintaining two ways of working indefinitely increases discrepancies and reconciliation effort.
Illustrative example: a new sales process
A company organizes opportunity qualification in its CRM, but the team continues to keep notes in spreadsheets. The initial assessment shows that some fields require information the buyer only provides at later stages.
The process is revised to record what is available at each stage. Training uses authorized real-world deals, and managers begin using the CRM to track meetings.
The company establishes a transition period, checks the required historical records, and discontinues the parallel report. A designated owner answers questions and monitors configuration adjustments.
The evaluation tracks completeness at the appropriate stage, information quality, and use in sales activities. Login counts remain a supplementary measure.
How to measure adoption
Track task execution, record quality, workflow completion, and rework. Compare performance with the previous situation and account for the learning period.
Conversations with users help interpret the numbers. An empty field can reflect different situations: unavailable information, lack of understanding, or difficulty using the system.
Monitoring needs to lead to corrections. Materials, configuration, and responsibilities are reviewed based on the findings, and adjustments are documented for new team members.
How to sustain the change
Adoption continues after implementation. New staff receive training, changes are communicated, and documentation reflects the version in use.
The company also reviews whether the process remains appropriate for the business. Changes in offerings, teams, and volume alter operational needs.
The process owner maintains regular monitoring and a channel for suggestions. User participation helps identify improvements based on daily execution.
Frequently asked questions
Does internal communication ensure adoption?
Communication explains the change. Adoption also depends on access, skills, time, support, and leadership participation.
How should low usage be addressed?
Examine tasks, conditions of use, and solution quality. Talk with users and document obstacles before deciding on adjustments.
What is the best adoption metric?
The measure should represent correct use in the intended activities. Task completion and output quality provide information more closely aligned with that purpose than logins alone.
How does Kronos Experience contribute?
Kronos connects processes, responsibilities, data, and monitoring to support the adoption of marketing, product, revenue, and technology initiatives.
About Kronos Experience
Kronos Experience is a Brazilian business strategy and intelligence consultancy focused on market, customer, product, and revenue intelligence for digital and service businesses.
We work to increase your company's value to the market and its customers, turning that value into competitive advantage. Our work connects market strategy, positioning, brand, acquisition, media, and sales with customer intelligence, experience, product, data, retention, and monetization.
Through assessment, strategic direction, implementation, and monitoring, we structure opportunities to increase returns on your brand, customer base, channels, products, and infrastructure, while developing new offerings and revenue streams.
Written by Luís Paravato
