Enterprise AI Enablement
Make effective AI use a shared way of working
Help leaders and teams build practical AI capability around real work. KeenSight connects role-specific practice, manager support, shared standards, and workflow improvement so useful individual habits can become repeatable organizational capability.
Your organization may already have approved tools and enthusiastic users. The next question is how people should apply those capabilities consistently: what work changes, what good output looks like, how managers support the change, and when a repeated task deserves a more structured workflow.
We help connect those questions across leadership, functions, and the enterprise, with practical learning grounded in the work people need to perform.
Define what should change in daily work
Start with a task people recognize. A team prepares customer briefings, reviews information, assembles reports, answers internal questions, or develops proposals. How could AI support that work? What context would it need? What should a person check before using the result?
Those questions create a useful basis for enablement. People can see where the capability applies, practice with relevant examples, and understand how to judge the output. Managers can discuss the work itself rather than treating use of a tool as the objective.
The starting point will differ across roles. An executive may need a better way to examine alternatives. A functional team may need a shared approach to preparing documents. A manager may need to establish review expectations for AI-assisted analysis.
Enablement should connect each role to practical behavior: how the person prepares context, uses the capability, reviews its contribution, and carries the work into the next step. That makes the change more concrete and easier to support.
Capability at three levels
Leadership
Leaders establish the purpose and conditions for changed work. They need enough fluency to ask informed questions, recognize useful applications, and understand what responsibilities accompany a new capability.
Practical leadership work can include using approved tools on relevant tasks, examining the quality of AI-assisted outputs, and connecting potential applications to business priorities. It also includes decisions about ownership, practice time, and how the organization will assess progress.
Visible participation gives managers and teams context for what leadership expects. It creates a basis for discussing the work that should change and the boundaries within which people can experiment and learn.
Functions and teams
Teams turn capability into working methods. Their needs are specific to the information they handle, the decisions they support, and the people who receive their outputs.
A functional program can examine real tasks, establish examples of useful output, and develop repeatable approaches to context preparation and review. Managers help reinforce those practices through normal work discussions. Champions provide peer support and bring feedback from day-to-day use.
The aim is a method that colleagues can understand and improve together. Shared expectations should make it easier to assess quality and identify where a process needs additional support.
Enterprise
The enterprise provides the conditions that allow useful practices to spread. Those conditions include approved access, clear information boundaries, relevant support, shared standards, and a way to learn from what teams are doing.
Enterprise capability also connects enablement to investment and governance. Repeated workflow needs should have a path into prioritization. Questions about permitted use or review responsibilities should reach the people who can resolve them.
This creates a relationship between practical learning and the wider AI agenda. Teams develop capability while the organization learns which changes deserve shared investment.
Programs shaped around the work
Executive sessions support fluency and judgment around the questions leaders need to address. They can connect hands-on exploration with discussion of business priorities, operating implications, and the decisions leadership should sponsor.
Functional programs focus on a team’s work. A commercial team might examine research, proposals, and follow-up. An operations team might explore information assembly, exception handling, or document review. The scope follows the tasks and quality expectations of the function.
Enterprise capability programs connect practices across the organization. They can establish a common foundation while allowing different roles to develop relevant methods. Coordination with technology and governance helps keep access, information use, and support aligned.
Champions networks provide a route for peer learning and feedback. Champions can demonstrate useful practices, support colleagues, and identify recurring needs. Their contribution works best when it is connected to managers, approved capabilities, and a clear path for escalating questions.
The program design should reflect the organization’s starting point and the work it wants to change. Existing practices, internal expertise, and approved tools provide material to build on. The objective is practical capability that remains useful after a session ends.
New ways of working
AI can support several kinds of knowledge work, but each requires an appropriate method for preparing context and reviewing the result.
Research and synthesis. Teams can develop a shared approach to identifying sources, organizing information, and distinguishing evidence from interpretation. The review should preserve the connection between a statement and the material supporting it.
Analysis and decision support. AI-assisted work can help explore questions, structure alternatives, or prepare an initial analysis. People still need to examine assumptions, calculations, missing information, and the implications of a recommendation.
Communication and documents. Drafting becomes more useful when the intended audience, purpose, relevant facts, and review expectations are clear. Shared formats can help colleagues understand what has been checked and what still requires judgment.
Internal knowledge work. Repeated questions can reveal where information is difficult to find or apply. That may lead to better knowledge organization, improved access, or a more structured support workflow.
These examples are starting points for practice. The right method depends on the task, the information involved, and what another person will do with the output.
Measure use, work quality, and outcomes
Measurement should help the organization decide what to improve. Different signals answer different questions.
Scroll horizontally to see all columns.
| Layer | Question | Possible evidence |
|---|---|---|
| Access | Can the intended people use an approved capability? | Availability, permissions, and support coverage |
| Activation | Have people begun using it on relevant work? | First completed tasks and initial feedback |
| Meaningful use | Is the practice recurring and useful? | Task-level use, accepted outputs, and manager observations |
| Workflow change | Has the way work moves changed? | Handoffs, cycle time, consistency, and exception handling |
| Quality | Is the output suitable for its purpose? | Review findings, rework, completeness, and downstream feedback |
| Business outcome | Is the intended operational or commercial result improving? | Measures connected to the original objective and baseline |
Select measures that fit the purpose of the program and the work involved. A practice may become easier to use while still requiring better output quality. A workflow may release capacity that leadership then needs to decide how to use.
The review should bring these observations together. It should help managers understand what is working, identify where colleagues need support, and surface opportunities that warrant a different kind of investment.
Capability in practice
BNY’s October 2025 account describes shared access through its Eliza platform alongside role-specific learning, problem-driven bootcamps, practical application, and peer communities. It provides a concrete example of connecting technology access with how people learn and apply AI in their roles. BNY’s program description.
The useful question for an enablement program is how access, practice, support, and application fit together in your organization. The scope should follow the capabilities your people need and the work they are responsible for.
When a useful habit becomes a workflow opportunity
Some patterns deserve attention beyond individual practice. Several people may be gathering the same context, moving information between the same systems, or checking outputs against the same rules. A useful method may also depend heavily on one person’s knowledge.
Those observations can support a workflow conversation. What could be standardized? Which context should come from an authoritative source? What review is required? Where would a more consistent process help the team or its customers?
The next step may be a shared working method, a configured capability, or a workflow that connects systems and responsibilities. The choice depends on the value, the effort involved, and the conditions around the work.
Bring the current steps, the information people use, and the parts that still need judgment. You do not need a predetermined technical solution to discuss the opportunity.
How this connects
AI Opportunity & Roadmap helps compare the workflow opportunities that emerge from practical use and decide which deserve investment. AI Governance & Operating Model defines permitted use, review responsibilities, and accountability as those practices develop.
The Workflow Discovery Template can help capture a recurring process. The AI Agent Governance Checklist provides a related way to consider the controls around an agent initiative.
Build capability around your next priorities
Bring the teams, tasks, and working practices you want to develop. We can start with your existing tools and experience, identify what useful progress would look like, and connect the program to the wider business agenda.
Whether the immediate need is leadership fluency, a functional program, shared practices, or a workflow opportunity, the conversation begins with how your people need to work.