How to Choose an AI Consultant in Grand Rapids, MI

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Most businesses begin by asking whether an AI consultant can build what they want.

A more useful question is whether that consultant can help the business choose the right project, involve the right people, and create something the team will still be using six months later.

A working tool is only the beginning. The real return comes when people adopt it, trust it, and use it as part of their everyday work.

A 2025 MIT NANDA report found that the vast majority of enterprise generative AI pilots were producing little or no measurable impact on profit and loss. The technology was only part of the challenge. Workflow integration, customization, organizational learning, and adoption all affected whether a pilot created value.

This is why choosing an AI consultant requires more than reviewing a list of tools they know how to use.

You need someone who can understand how your business operates, recognize which opportunities are worth pursuing, and help your people use what gets built.

Here is what that looks like in practice, and then the questions worth asking.

What This Looks Like Inside a Real Business

These questions are not theoretical. They affect what gets built, who needs to be involved, and whether the finished system becomes part of the business.

Turning Years of Agricultural Knowledge Into a System People Can Use

I am currently working as an AI strategy partner with a family-owned agricultural business that operates across several states.

The opportunity was not simply to give employees access to AI.

The company has decades of operational knowledge spread across experienced employees, existing procedures, equipment information, meetings, documents, and day-to-day decisions.

That creates many possible AI projects. It does not mean they should all be built at once.

Our work includes determining how to organize the knowledge, which systems need to come first, and how employees in different roles can use AI to create more valuable outcomes.

For example, a maintenance manager should not receive the same tool or training as the CFO.

A useful maintenance system could combine the company's own procedures with publicly available equipment information. That system might help the maintenance manager investigate an issue, prepare a maintenance plan, or find the correct instructions faster.

A financial leader may need an entirely different system for analyzing information, preparing forecasts, identifying trends, or supporting leadership decisions.

We are also exploring larger operational projects, including a dashboard that follows the work a farmer needs to complete throughout the year and an HR dashboard built around the company's actual processes.

The technology matters, but the larger job is deciding what should be centralized, what should stay role-specific, what information can be trusted, and which project will create the greatest value first.

Making a Founder's Expertise Available to the Team

Another company came to me with a different challenge.

Much of the company's working expertise sat with one long-tenured person.

The team needed access to that knowledge, but transferring years of experience into a useful system required more than recording a few instructions or building a general chatbot.

We needed to identify how those decisions got made, what information the team needed in specific situations, and how to structure that knowledge so employees could use it without losing the judgment and personal approach that made the company successful.

The goal was to reduce the number of situations in which progress stopped because only one person knew what to do next.

This is an important distinction when choosing an AI consultant.

A tool can store information. A useful business system helps the right person apply the right information at the moment they need it.

Building With the Team

These companies have different needs, but the approach is consistent.

The people closest to the work help shape what gets built. Leadership establishes the priorities. Each project has a clear purpose and an internal owner. Training happens through real work instead of disconnected demonstrations.

The company is not left with a collection of tools nobody fully understands.

It gains systems its people can use, along with the knowledge and confidence to continue improving those systems as the business changes.

None of that happens by accident. It comes from asking the right questions before the work starts. Here are the ones worth asking any consultant you are considering.

Ask What They Would Tell You Not to Build

A good AI consultant should be able to identify opportunities. A great one should also recognize distractions.

Sometimes the process needs to be clarified before anything can be automated. Sometimes the information is too inconsistent to support a reliable system. Sometimes the task requires human judgment and should stay that way.

There are also times when the requested tool is possible to build, but it is not the best place for the business to invest its time or money.

Ask a potential consultant to describe a project they advised a client not to pursue. Listen for how they evaluated the opportunity.

Did they consider the business outcome?

Did they look at how often the problem occurred?

Did they estimate the time or cost it could save?

Did they consider whether employees would use it?

The goal is not to find the consultant who can build the most impressive system. It is to find someone who can help you make a sound business decision.

Ask How They Decide What Comes First

Once people begin seeing what AI can do, the list of possible projects grows quickly.

Marketing wants help creating content. Human resources wants a better onboarding system. Operations wants dashboards. Leadership wants access to company information. Employees want tools designed for their individual roles.

All of these ideas may have value, but they cannot all be the first priority.

Sequencing is one of the clearest differences between strategic consulting and order-taking.

A strong AI consultant should help you distinguish among:

• Foundational systems other projects will depend on
• High-impact opportunities that could save significant time or money
• Quick wins that help the team build confidence
• Accessory projects that can wait
• Interesting ideas that do not solve an important enough problem

One operations director I work with described this clearly. She wanted the foundational pieces built before the accessory items, and she wanted to know which sequence would produce the highest return in time saved or cost saved.

She was not asking for a feature list.

She was asking for judgment.

Ask Who Will Own the System After It Is Built

Every AI project needs an internal owner.

This does not necessarily mean the owner of the company. In many cases, the best person is someone closer to the daily work who understands how information moves, where employees get stuck, and what needs to happen for the new system to become part of the routine.

That person also needs actual time set aside for the project.

Without an internal owner, a system can be delivered, admired, and then quietly abandoned when daily work becomes busy again.

Before a project begins, ask:

• Who will help make decisions during the build?
• Who will test the system using real situations?
• Who will collect feedback from employees?
• Who will maintain the information?
• Who will notice when the process changes?
• Who will be responsible for continued use after the consultant leaves?

A consultant should help you establish this ownership before implementation, not after adoption has already stalled.

Ask How They Will Involve the People Doing the Work

Leadership can identify business priorities, but employees often know where the real friction lives.

They know which spreadsheet is always missing information. They know which approval slows everything down. They know which customer question gets answered repeatedly. They know which instructions no longer match what happens in practice.

If a consultant designs the solution without learning from those employees, important details will be missed.

That does not mean every employee should direct the project or contact the consultant whenever a new idea appears. That can create scattered priorities and prevent anything from being completed.

A better structure includes:

• A leadership team that establishes the business priorities
• A primary contact who coordinates the work
• Department representatives who understand their processes
• Employees who test systems in real situations
• A defined method for gathering feedback
• A clear order for reviewing and approving new ideas

The people doing the work should have a voice in the process without turning the project into a free-for-all.

Ask Whether They Build for Demonstration or Daily Use

Some AI systems are impressive during a presentation.

That does not mean they will survive contact with a busy workday.

A system intended for daily use needs to account for the actual people, information, decisions, exceptions, and time constraints inside the business.

Ask the consultant how they test what they build.

A useful testing process should include questions such as:

• Can an employee understand where to begin?
• Does the system have access to the right information?
• Are the instructions specific enough to produce consistent results?
• What happens when information is missing?
• Does the employee know when human review is required?
• Can the process be completed without the consultant in the room?
• Does the result save enough time or improve the work enough to justify using it again?

The goal is not simply to produce an output.

The goal is to create an experience that people can successfully complete and want to use again.

Ask How They Will Transfer Knowledge to Your Team

Businesses are often presented with two choices.

One option is to enroll employees in a course and expect them to determine how AI applies to their work.

The other is to hire someone who builds everything behind the scenes and delivers a finished system the team does not fully understand.

There is a valuable middle ground.

A consultant can bring the technical knowledge and strategic guidance while building alongside the people who understand the business.

This allows the team to learn through real work. They understand why decisions were made, how the system works, what its limitations are, and how to improve it as the business changes.

Before hiring an AI consultant, ask what your team will know how to do when the engagement ends.

You should be gaining more than a tool. Your business should also be developing the confidence and internal capability to use it.

Ask How They Decide Between One AI System and Several

One client asked me a particularly important question during an early conversation:

Do we build one agent or ten, with one for each subject?

There is no responsible way to answer that without understanding the business first.

The right structure depends on:

• Which employees will use the systems
• Whether the information is shared or separate
• How sensitive the information is
• Which roles need access
• How frequently the information changes
• Who will maintain each system
• Whether different tasks require different instructions
• How much complexity the team can realistically support

Businesses sometimes build a separate AI tool for every possible subject, then discover they have created a maintenance problem.

They may also put everything into one large system and make it difficult for employees to find the right starting point.

A consultant should investigate how knowledge, roles, and responsibilities overlap before recommending the structure.

Ask How They Measure Whether the Project Worked

A successful project needs a business outcome.

That outcome does not always need to be immediate revenue. It may be:

• Fewer hours spent searching for information
• Faster preparation for client or leadership meetings
• More consistent follow-up
• Fewer repeated questions directed to one employee
• Shorter onboarding time
• Better access to company procedures
• Fewer steps in an administrative process
• More consistent decisions across locations
• Faster completion of routine documentation
• Reduced dependence on one person's memory

The measure should connect directly to the original problem.

If the system was built to save time, identify where that time should be saved and how you will recognize the difference.

If it was built to improve consistency, determine what a consistent result looks like.

If it was built to transfer knowledge, identify who should be able to complete the work without relying on the previous knowledge holder.

Clear measures protect the business from investing in AI simply because the finished system looks impressive.

Ask How They Protect the Human Side of the Business

AI can help draft communication, prepare information, organize knowledge, identify patterns, and complete repetitive tasks.

It can also create distance when used in the wrong places.

A consultant should help you decide where efficiency improves the human experience and where personal attention still matters.

For example, AI may help a manager prepare for a difficult employee conversation. It should not automatically conduct that conversation.

It may help a salesperson understand a prospective client before a call. It should not replace the relationship being built during the call.

It may help organize information from customer requests. It should not make every response sound generic and impersonal.

The purpose of efficiency is to create more room for leadership, judgment, service, and connection.

AI should support the relationships that make your business valuable.

When Working With a Local AI Consultant Matters

What West Michigan businesses often have in common

Many established businesses across West Michigan share a set of operational challenges, and those challenges affect what successful AI work looks like.

Family ownership often passes into a second and third generation, and with it comes decades of knowledge that lives in long-tenured employees rather than in documentation. West Michigan is a manufacturing and food region with an agricultural belt running through it, which means a lot of operations are physical, seasonal, and spread across more than one site. Many have operations spread across multiple locations or states, with workforces that may change with the calendar.

Those traits matter more than the industry label:

• Knowledge that walks out the door when a long-tenured employee retires
• Processes that differ quietly from one location to the next
• Seasonal swings that make some months impossible and others open
• Physical work that does not describe itself well on a screen
• Decisions made in a room, by people who have known each other a long time

Those are the conditions where AI work either fits the business or gets rejected by it.

Proximity is valuable when the work needs to be seen

Shop floors, front desks, warehouses, farms, and multi-location operations can be difficult to understand entirely through a video call. Sometimes the consultant needs to see how employees move through the work, where information is stored, and what happens when a process leaves the written procedure and enters the real world.

In-person work can also help when several leaders or departments need to make decisions together.

Local access matters less when the entire process lives inside systems that can be reviewed through screen sharing.

Do not choose a consultant simply because they are nearby. Choose someone local when their ability to enter the business, observe the work, and build relationships with the team will make the project better.

What This Kind of Work Costs

The cost of AI consulting depends on the problem being solved and the level of support the business needs.

A clearly defined automation is a different engagement from helping a multi-location company identify opportunities, organize decades of knowledge, prioritize projects, build new systems, and prepare employees to use them.

The factors that most often affect the investment include:

• How many people, departments, and locations are involved
• Whether the business already knows what it needs
• How much company knowledge must be collected and organized
• Whether existing systems need to be connected
• How much testing and customization the project requires
• Whether the team needs training and ongoing strategic support

A business that needs one workflow connected should not pay for a company-wide strategy partnership. A company with several departments, multiple locations, and years of undocumented knowledge should not expect one automation to solve the larger problem.

The purpose of an initial strategy call is to understand the problem, determine the appropriate scope, and decide whether the potential business value justifies the investment.

How I Work

I am based in Caledonia, just outside Grand Rapids, and work with growing businesses throughout West Michigan and beyond.

My role sits between two common approaches.

Some consultants give businesses a course and expect the team to figure out the implementation. Others disappear behind the scenes, build a system, and deliver something the company does not fully understand.

I build alongside businesses.

That means helping you identify the right opportunities, decide what comes first, involve the people who understand the work, and create systems your team can confidently use without becoming dependent on a consultant.

My work may include:

• Identifying the best opportunities for AI across the business
• Prioritizing projects based on impact, effort, and readiness
• Organizing company knowledge so employees can access it
• Designing role-specific AI tools and workflows
• Building operational dashboards and internal systems
• Training employees through real business use cases
• Establishing ownership and feedback processes
• Helping leadership evaluate new opportunities as AI evolves

The goal is not to add more AI to your business.

The goal is to make your business easier to run.

Looking for an AI Consultant in Grand Rapids, MI?

You do not need to arrive with a list of tools or a fully defined project.

Start with the part of your business that takes too much time, depends too heavily on one person, creates repeated frustration, or prevents your team from moving forward.

During a strategy call, we can look at what is happening now, where AI may create meaningful value, and what should come first.

Most of what separates a good consultant from an order-taker is not local, it is structural. The same judgment applied to AI consulting for small businesses anywhere.