AI Enablement
AI is already changing how people work. How should your company use it?
Your employees are experimenting with it. Software vendors are adding it to products you already use. New tools seem to appear every week.
Some of it is genuinely useful. Some of it isn’t. And somewhere in the middle are real opportunities to save time, improve how people work and solve problems that have been difficult to solve before.
Marshall Technology helps organizations figure out where AI makes sense, where it doesn’t, how to use it safely and how to turn worthwhile opportunities into something useful.
You may already be using more AI than you realize.
- Someone used ChatGPT to rewrite a proposal.
- Another employee uploaded a spreadsheet to analyze it.
- Marketing is experimenting with an AI tool they found online.
- Microsoft is adding Copilot throughout the applications your employees already use.
- Your HR, CRM, accounting and other software vendors are introducing AI features of their own.
Before deciding what to buy or launching an AI initiative, there are some more useful questions to answer.
What are people already doing? What company information are they putting into these tools? Which tools should they be allowed to use? What capabilities are you already paying for? Where could AI actually improve the business? Who is responsible for making those decisions?
AI adoption doesn’t always wait for an AI strategy.
Making AI useful starts with understanding where it belongs.
There is no shortage of impressive AI demonstrations.
Putting AI to work inside a real company is different. There are employees, business processes, applications, data, security requirements, vendors, budgets and existing technology to consider.
Marshall Technology looks at AI Enablement through four practical questions.
UnderstandWhat’s happening?
What is happening today?
What are employees already using? What capabilities already exist? What information is being shared? Where are the risks, gaps and opportunities?
ProtectUse it safely.
How should AI be used safely?
Which tools are appropriate? What information can be used with them? What security, privacy and governance need to be in place?
Find the ValueWhere can it help?
Where can AI actually make a difference?
Look across departments, workflows and systems for work that is repetitive, manual, slow or unnecessarily complicated.
Make It WorkProve it works.
How does a good idea become useful?
Choose the right technology, put it into a real workflow, test it with real users, measure the results and expand what proves worthwhile.
Your AI question may start somewhere completely different.
Most AI conversations don’t start with a service name. They start with a question.
I don’t know what our employees are already doing with AI.
Maybe people are using personal ChatGPT or Claude accounts. Maybe departments have adopted tools nobody else knows about. Maybe AI capabilities already exist inside software you’re paying for.
There may be questions about usage, accounts, company information, licensing, existing capabilities and risk.
That’s exactly the kind of question AI Enablement should answer.
I’m worried about company information going into AI tools.
That’s a legitimate concern, and the answer is more nuanced than simply blocking AI.
Which platforms are being used? Are they company-managed? What information is appropriate to use? What security and privacy protections apply? What rules should employees follow?
That’s part of the conversation too.
I know AI could help us somewhere. I just don’t know where.
Start with the work.
Where are people spending too much time? What is still being done manually? Where are employees moving information between systems, searching for answers or doing the same thing over and over?
Those questions can uncover opportunities for AI, automation, integration or better use of technology you already have.
You don’t need to know the solution before bringing us the problem.
We have an idea. How do we know if it will actually work?
Then let’s find out.
We can look at feasibility, the systems and data involved, the right technology, the risks and what a meaningful pilot would need to prove.
A good idea should be testable before it becomes a major investment.
We’re considering Copilot, ChatGPT, Claude or another AI platform. Which one should we use?
The answer depends on what you’re trying to accomplish, what systems and data you use, how employees will access it, what security and governance controls you need and what capabilities you’re already paying for.
The tool comes after the requirements.
Before deciding where you’re going, understand where you are.
AI Readiness Assessment
For organizations that want a structured look at the bigger picture, the Marshall Technology AI Readiness Assessment provides a practical starting point.
The result isn’t a generic AI maturity score.
You get a clear current-state picture, findings and priorities, opportunities worth exploring and a practical roadmap for what should happen next.
An IT Health Check looks broadly across the entire technology environment and includes AI at a high level. An AI Readiness Assessment goes intentionally deeper into AI usage, governance, risk, readiness and opportunity. Which starting point makes sense depends on the questions you’re trying to answer.
Explore the IT Health CheckGiving employees access to AI is easy. Giving them the right access is harder.
Blocking every AI tool probably isn’t sustainable.
Allowing employees to put company information into whatever AI service they happen to find isn’t acceptable either.
There is a practical middle ground.
Marshall Technology helps organizations work through which platforms should be approved, when company-managed accounts make sense, what information employees can use, what security and privacy controls are appropriate, how vendors should be evaluated and who should be responsible for oversight.
Policies and governance matter, but they also have to work in the real world.
Employees should understand what they can use, what they shouldn’t use and what is expected of them without needing to interpret a compliance manual every time they open an AI tool.
That creates room for people to explore what AI can do while giving the company reasonable control over how it is being used.
The best AI opportunities usually don’t start with AI.
We spend way too much time doing this.
- A report has to be assembled manually from several systems.
- Employees spend hours searching through documents for information.
- The same customer or employee questions get answered over and over.
- A spreadsheet has become the unofficial system connecting two applications that don’t talk to each other.
Those are the places worth looking.
We work with leadership, department heads and the people actually doing the work to understand where time is being spent, where processes break down and where technology could make things better.
The right technology follows the right problem.
- Sometimes the answer is AI.
- Sometimes it’s automation.
- Sometimes it’s integration.
- Sometimes it’s simply using technology you already own more effectively.
The objective isn’t to find somewhere to put AI. It’s to find business problems worth solving.
Good ideas should prove themselves.
A promising use case doesn’t automatically need to become a major technology project.
Understand the problem and the current process. Decide what a successful result would look like. Then test the idea in a controlled way with real users and real work.
Depending on the opportunity, Marshall Technology can help evaluate the approach, configure an existing platform, build a controlled pilot, develop a workflow or automation, integrate existing systems or help select and oversee a specialized technology partner.
Then we measure what happened.
- Did it save time?
- Did it improve the process?
- Did people actually use it?
- Did it create enough value to justify taking the next step?
If it works, build on it.
If it doesn’t, stop.
Not every pilot needs to become a production system. Learning that something doesn’t work before making the larger investment can be a successful outcome too.
AI is new. The challenge of introducing powerful new technology into an existing business isn’t.
Today’s AI tools can do things that weren’t practical even a few years ago.
But eventually they have to live inside a real company.
They have to work with existing applications and data. They have to protect company information. They have to fit into real workflows. Employees have to adopt them. Vendors have to be managed. Investments have to be justified.
We understand what happens after the demo.
Marshall Technology combines hands-on use of today’s AI tools with decades of experience implementing and managing technology inside real organizations.
Our hands-on AI work includes AI-assisted software development, methodology development, research and analysis, document and data analysis, and workflow automation.
We’re looking for places where AI can make real work easier, faster or more reliable.
We’re not tied to one AI platform. Recommendations start with the business problem and what makes sense for the organization.
You don’t need to have an AI strategy before starting the conversation.
You may have a specific idea you want to explore.
You may have questions you haven’t been able to answer.
Or you may simply be sitting in a leadership meeting wondering:
What should we be doing with AI?