AI & Operations | June 2026 | By Ciara D. Long, Founder & Principal Strategic Advisor
AI & Operations | June 2026 | By Ciara D. Long, Founder & Principal Strategic Advisor
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Artificial Intelligence (AI) is moving quickly, and organizations are under a great deal of pressure to keep up with the ever changing technology. Every new tool promises faster work, reduced overhead, better decisions, and less administrative tasks.
Some of those tools can help.
But AI can't fix a process no one fully understands. It can't clarify responsibilities that were never clearly assigned. It can't repair inconsistencies, poor communication, missing documentation, or decisions that stall out because no one knows who actually has the authority to make them.
While technology can make a stronger operation move faster, it can also make a weak operation even more confusing.
That's why AI shouldn't be your starting point, operations should.
Start With the Work, Not the Tool
Start With the Work, Not the Tool
Before you choose a platform and before you start building an automated workflow, you need a clear picture of how the work moves, from start to finish.
Consider questions like:
Where does the work start?
Who owns each step?
What information is needed to move to the next step?
Where do delays or errors typically happen?
Which decisions require approval(s)?
Where is the information stored?
What happens when someone, or a system, or a partner doesn't follow-through?
These questions might sound like basic common sense, but you'd be shocked, or maybe you wouldn't be, to learn how the answers are usually spread across various inboxes, meetings, shared drives, personal habits, and systems that don't talk to each other.
Adding AI before addressing those gaps doesn't alleviate the confusion, it just hides it behind a newer, shinier interface.
Automation Doesn't Replace Clarity
Automation Doesn't Replace Clarity
A process shouldn't be automated just because it "takes up too much time".
Some work takes too long because the steps are repetitive, and automation could be useful. But then, there's other work that takes too long because the process has unneccessary approvals, duplicate reviews, hazy instructions, or just poor handoffs.
Automating the second type of process would most likely create a faster version of the same problem.
A useful review looks at:
Tasks that are repeated frequently
Information entered into multiple places
Reports created manually from existing data
Common requests that follow a standard process
Delays caused by 'fuzzy' ownership
Approval steps that no longer serve a clear purpose
Work that relies too heavily on one person's memory or experience
Your goal shouldn't be to automate everything. It should be to effectively determine which work should be simplified, documented, reassigned, automated, or altogether stopped.
AI Readiness Is an Operations Question
AI Readiness Is an Operations Question
A number of organizations are approaching AI readiness as a technology issue. They focus on the software, the security settings, the licenses, and the training.
All of those things are important, but readiness also depends on how the organization manages its existing work.
Your organization may not be ready to use AI across a process if:
Procedures are outdated or undocumented
Teams use different versions of the same information
Roles and approval authority aren't clear
Data is incomplete, inconsistent, or hard to access
Staff doesn't understand how their work connects
There isn't a process for reviewing AI-generated output (because we know AI likes to hallucinate!)
Leadership hasn't defined acceptable use
This doesn't mean your organization should avoid AI. It simply means you should prepare the work before expanding the technology.
The People Actually Doing the Work Need a Voice
The People Actually Doing the Work Need a Voice
AI planning should't just happen in the c-suite, executive office, or the techology department.
Your teams managing the day-to-day work can more efficiently explain where things get stuck, which steps are the most frustrating, what customers or stakeholders constantly ask for, and which workarounds have officially become a part of the unofficial process.
Their insight helps you separate the process shown in a policy or flowchart from the process that is actually happening.
Including staff early also improves the adoption. People are more likely to use a new process when they understand why it's changing, how it affects their role, and where their experience influnced the decision.
This is especially important for organizations working across departments, contractors, community partners, or external service providers. Each group may only see their portion of the process. Successful implementation requires a connecting of those parts.
Documentation Makes Improvement Possible
Documentation Makes Improvement Possible
A process that only exists in someone's head is pretty difficult to improve and even harder to automate.
Clear documentation creates a shared reference point. It helps teams identify missing steps, conflicting information, unnecessary work, and points where human review should stay in place.
Useful documentation might include:
Process maps
Standard operating procedures (SOPs)
Decision and approval points
Roles and responsibilities
Templates and checklists
Data sources and reporting requirements
Escalation procedures
Quality review standards
Documentation should support the work, not create another administrative burden. The best materials are easy to find, easy to follow, and updated whenever the process changes.
Good AI Implementation Takes More Than A Technology Vendor
Good AI Implementation Takes More Than A Technology Vendor
Technology firms play an important role in AI implementation. They bring the platform knowledge, development experience, integration support, and technical expertise.
But, the technology partner shouldn't have to guess how your organization operates.
Strong implementation needs several types of expertise working together:
Organizational leaders who define priorities and acceptable risk
Program and operations teams that understand the work
Technology partners who configure and integrate the tools
Legal, security, privacy, or compliance advisors who define ethics and boundaries
Training and change-support partners who help teams adjust
Operations advisors who connect the business need, the workflow, and the implementation plan
This is where the right partnerships genuinely matter.
A strong partner isn't competing to own every part of the engagement. They understand their role, communicate clearly, share information, and helps the full team deliver a better result.
A Better Starting Point
A Better Starting Point
Before you invest in a new AI tool, start with a focused operations review.
Identify one process that's important, time-consuming, or just consistently annoying. Document how it works now. Talk with the people involved. Review the data, decisions, handoffs, and reporting requirements. Then you should be able to more effectively determind where AI or automation may add value.
A strong starting process typically has:
A clear beginning and end
Repeated steps
Defined information inputs
A manageable level of risk
Staff members who can actually explain the current process
A clear reason for improving it
Results that can be reviewed after the change
Starting with one well-defined process gives your organization room to learn, adjust, and build confidence before expanding.
The Strategy Is Really Better Work
The Strategy Is Really Better Work
AI can help your organization save time, improve access to information, reduce redundant work, and even support better decisions.
But those results don't just come from the tool singularly.
They are the result of clear priorities, better processes, reliable information, defined responsibilities, good documentation, and people who understand how the work all fits together.
AI might be a part of your solution, but it's your operations that determine if that solution works or not.
About Long Legacy Collective
About Long Legacy Collective
Long Legacy Collective helps public-sector, nonprofit, community-based, and mission-driven organizations improve how their work is planned, coordinated, documented, and carried out.
Our AI & Operations support includes workflow reviews, process improvement, documentation, automation planning, implementation coordination, and partner support. We also work with technology firms, prime contractors, consultants, and other service providers that need an operations partner to strengthen the business and implementation side of an engagement.
Planning an AI initiative or supporting a client whose operations need attention first?
Planning an AI initiative or supporting a client whose operations need attention first?
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