Three Questions to Ask Before You Build With AI

It’s easy for an AI initiative to start with the technology: a new capability, an interesting use case, or a process that seems ready for automation.

But before deciding what to build, there’s a more useful place to start: What would a better day at work look like for the people doing the work?

Maybe a service team could get the information it needs without jumping between systems. Maybe an order could keep moving without someone tracking down the next approval. Maybe employees could spend less time gathering information and more time using it to make decisions.

Those are the kinds of outcomes that give an AI initiative direction.

At Palladin, we connect business planning with Salesforce implementation, data, integration, and AI. That experience has shown us that successful delivery starts with a clear understanding of the work you want to improve and the people involved in it.

Before moving an AI initiative into delivery, start with three questions.

Focus: What are we trying to improve?

AI can create possibilities across the business, but not every possibility needs to become a project.

Once you’ve identified two or three priority areas, narrow the conversation to the first process you want to improve and define what success should look like.

Consider order fulfillment. “Make it more efficient” gives a team very little direction. Instead, look at where work slows down today. Are employees waiting for information? Are approvals creating delays? Are people spending time manually following up?

Then choose a meaningful way to measure improvement, such as reducing the time between order and fulfillment or decreasing the number of manual follow-ups required.

Establishing that starting point gives everyone something more meaningful to work toward than simply delivering a successful AI demonstration. It also creates a foundation for lasting change, greater productivity, and improved employee satisfaction.

Rewire: What needs to work differently?

Once you know what you want to improve, the next question is how the work itself should change.

Before getting attached to a particular AI feature, map the process you want people to follow. For an order, that might mean understanding what information needs to move between Salesforce and other systems, which decisions AI could support, and where human review or approval still matters.

This is also an opportunity to question the process itself.

Automating an unnecessary step only makes that unnecessary step happen faster. Sometimes the better approach is to remove it, redesign it, or rethink how information moves through the business.

At Palladin, our AI work includes connecting data and applications alongside implementing AI capabilities. Those pieces need to be part of the design conversation because AI rarely operates in isolation.

The goal is not simply to add AI to an existing workflow. It’s to decide what the work should look like and build the technology around it.

People: Who gets a say before launch?

A process can make perfect sense on paper and still fall apart when it meets the realities of someone’s workday.

That’s why the people who will use, manage, and support the process should be involved before launch, not introduced to it afterward.

Identify the business owner early as well as other impacted stakeholders. Give all users opportunities to identify and eventually test realistic scenarios. Ask where the proposed workflow creates friction, what information is missing, and what doesn’t reflect the way the work actually happens.

Their involvement shouldn’t end when the system goes live.

Decide who will answer questions, review feedback, monitor how the process is working, and determine when adjustments are needed. At Palladin, our Salesforce implementation services include training, maintenance, and ongoing support because adoption continues well beyond launch.

Start With the Work, Then Build

Focus gives AI a clear purpose. Rewiring turns that purpose into a better way of working. People help make sure what you build can succeed in the real world.

Bringing those decisions into the conversation early gives your teams a clearer brief, better measures of success, and a stronger foundation for whatever comes next.

Considering where AI could make a meaningful difference in your business? Talk with Palladin about turning the opportunity into a practical plan.