AI in business: how to choose applications with economic value
Luís Paravato
AI in business is the use of artificial intelligence in activities with a defined business purpose. The application needs to connect a task, its users, the information used, and the expected result.
Organizing customer service records, preparing sales drafts, and consulting documents are examples of activities worth evaluating. The choice depends on workload, required quality, and the ability to verify the output.
For your company, economic value emerges when use improves an activity and produces a benefit the operation puts to work. Time freed up, for example, needs to be linked to the work performed with that capacity.
Describe the activity before the solution
The assessment records who performs the task, what information they consult, how much time they spend, and which errors create rework. It also identifies volume, frequency, and variations.
A description such as “use AI in sales” leaves the scope open. “Prepare a proposal draft based on an approved offer and the opportunity data” makes it possible to evaluate sources, permissions, and quality.
The design specifies what the application delivers and what remains people's responsibility. This makes it easier to compare the current workflow with the proposed approach.
Assistance, automation, and autonomous action
In task assistance, AI produces a suggestion or draft for a person to use. In automation, a sequence performs activities according to rules. Autonomous applications select steps and use tools within the limits granted to them.
The application's scope changes its control requirements. Summarizing a document for review has different consequences than sending a proposal or modifying customer information.
The project needs to define permissions, approvals, and conditions for stopping. Expanding autonomy depends on evidence of performance and the impact of potential failures.
How to compare use opportunities
| Dimension | Evaluation question |
|---|---|
| Value | What business result does the activity support? |
| Frequency | How often does the task occur, and for how many users? |
| Data | Is the necessary information available and up to date? |
| Quality | How will the output be checked for accuracy? |
| Consequence | What happens when the application makes an error? |
| Operations | Who maintains the solution and handles exceptions? |
| Investment | What resources will be needed for testing and operation? |
The comparison considers all these factors together. A frequent activity becomes less attractive when review consumes all the time saved. A less frequent task deserves attention when it involves substantial effort or business impact.
How to estimate the benefit
Record current performance before the test. Time per task, rework, response time, and quality provide benchmarks for comparison.
The financial estimate includes implementation, licenses, usage, integrations, data preparation, review, and maintenance. Revenue benefits require a substantiated link to the application, accounting for other factors at work during the period.
Hours freed up represent capacity. They become a realized financial benefit when the company demonstrates how that capacity is used, such as reduced overtime or additional service with a known return. Reporting should distinguish expectations, capacity freed up, and verified results.
How to conduct a useful test
The pilot uses representative activities, including common cases and exceptions. The team defines a quality benchmark and compares execution with and without the application under conditions as similar as possible.
The test records total time, including preparation and review. Incomplete responses, corrections, and handoffs to people are included in the analysis.
Before expanding, the team checks performance, user acceptance, and maintenance requirements. A good demonstration result does not replace testing with the company's actual documents, processes, and constraints.
Illustrative example: classifying service requests
A software company receives requests that need to be classified by topic before routing. The team performs this triage manually and records the time spent.
The AI pilot suggests categories based on the authorized content of each request. The responsible staff review a sample and all cases where the application indicates uncertainty or encounters a situation outside its scope.
The evaluation considers classification accuracy, total time, incorrect routing, and the need for new categories. The team also checks whether the data used are appropriate for the purpose and existing permissions.
Expansion depends on the results of this evaluation. Monitoring continues after implementation to identify changes in request types and correct classification rules.
How to organize a portfolio of initiatives
Selected applications are assigned business and technology owners. Planning identifies shared sources and components, preventing each department from maintaining incompatible versions of the same documents.
Initiatives in testing, in operation, and discontinued remain clearly distinguished. The record explains the reason for continuing or stopping, preserving useful lessons for new projects.
Investment follows demonstrated value and operational capacity. New applications begin with a specific purpose, rather than interest in a tool alone.
Frequently asked questions
Which activity should be chosen first?
An activity with a clear purpose, accessible data, verifiable quality, and available owners provides better conditions for learning from the test.
Does every application need to reduce headcount?
No. Benefits include quality, speed, service capacity, and information organization. The economic result needs to be demonstrated against the chosen purpose.
How do you avoid a pilot that never reaches production?
Include maintenance, users, sources, and conditions for expansion from the design stage. The test should establish whether the application meets the needs of the actual workflow.
How does Kronos Experience contribute?
Kronos connects AI opportunities to processes, data, customer experience, and revenue through assessment, strategic direction, implementation, and ongoing monitoring.
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 a competitive advantage. Our work connects market strategy, positioning, brand, acquisition, paid media, and sales with customer intelligence, experience, product, data, retention, and monetization.
Through assessment, strategic direction, implementation, and ongoing monitoring, we structure opportunities to increase returns on your brand, customer base, channels, products, and infrastructure, while developing new offers and revenue sources.
Written by Luís Paravato
