Services

Practical support from AI understanding to implementation.

Engagements can begin with training, a specific business problem, an implementation opportunity, or a broader strategic question. The scope is built around what your organization actually needs.

Corporate AI Training and Adoption

Build practical AI fluency across an organization, from foundational understanding to role-specific use. Training is designed around your team’s existing technology, workflows, documents, and level of experience.

Explore Training

Company-wide AI foundations
Executive and leadership education
Role-specific workflows
Prompting and context techniques
Microsoft 365 Copilot and other approved platforms
Custom AI tool training
Responsible use and human review
Follow-up adoption support

AI Strategy and Implementation

Understand where AI actually belongs in the business, test emerging capabilities against real problems, and build the systems that prove useful.

Workflow and opportunity identification
AI readiness assessment
Model and platform evaluation
AI-assisted knowledge retrieval
Custom assistants and agents
Workflow automation
Internal knowledge systems
Prompt and context architecture
Guardrails and review processes
Pilot design and evaluation
Implementation inside existing software stacks

Also available — beyond AI

Business and Founder Advisory

Strategic support for business problems that extend beyond AI, particularly when technology, growth, operations, positioning, and leadership decisions intersect.

Business strategy
Go-to-market planning
Positioning and messaging
Early-stage operations
Growth planning
Process improvement
Pricing strategy
Founder decision support
International and U.S. market expansion

How I approach the work

Understand first. Test before deciding.

Understand

Learn the people, workflows, software, institutional knowledge, constraints, and actual problem.

Experiment

Test capabilities across models and tools before assuming what the solution should be.

Translate

Turn technical possibility into something the organization can understand and use.

Apply

Build the workflow, system, training, or strategy that proves useful in real work.

Understand → Explore → Test → Refine → Apply

Case Studies

What the work looks like in practice.

Every engagement starts somewhere different. Sometimes it is a team trying to understand AI. Sometimes it is an operational bottleneck, disconnected systems, or a founder trying to turn expertise into a more scalable business. The examples below show how AKW translates different starting points into practical systems, strategies, and next steps.

Organization

Turning AI interest into an implementation roadmap

Starting point

The organization had no shortage of AI ideas across project work, historical documents, reporting, planning, billing, permitting, and internal knowledge. The harder question was determining what was actually worth implementing.

AKW's role

Discovery + Prioritization

Organizational discovery, workflow and pain-point identification, use-case prioritization.

Training + Experimentation

Organizational AI training, knowledge and archive retrieval, AI-assisted document workflows, prompting and source-boundary testing.

Feasibility + Systems

Feasibility assessment, existing-system investigation, integration possibilities, implementation constraints.

Operational Strategy

Operational automation planning, connected workflow opportunities, implementation roadmap development.

Key finding

One of the largest constraints was not AI capability itself. It was getting the right organizational information into the right place, with the right structure, permissions, and context.

The question shifted from “What can AI do?” to “What would a useful system need to know?”

Result

A broad collection of AI opportunities became a more structured set of priorities, tested workflows, known constraints, and implementation paths. The organization also developed a stronger internal understanding of where AI could provide value and where human judgment, source quality, or systems integration remained essential.

Founder

Building the infrastructure around existing expertise

Starting point

A founder had deep subject-matter expertise and an established service offering, but needed stronger systems around how that expertise was communicated, discovered, purchased, and maintained.

AKW's role

Positioning + MessagingService positioning, customer-facing communication, educational content and resources.
Digital + AcquisitionWebsite and digital infrastructure, testimonial infrastructure, referral, directory, and local discovery strategy.
Operations + EnablementPayment processes, contract and invoice infrastructure, reusable content templates, founder training.

The goal was not to add more technology. It was to build a simpler system around the value that already existed.

Result

A stronger digital and operational foundation with clearer positioning, reusable materials and acquisition infrastructure, and systems the founder could increasingly manage independently.

Team

Moving a team from access to practical understanding

Starting point

Employees increasingly had access to powerful AI systems, but access alone did not mean they understood how to use them effectively, safely, or in ways relevant to their actual jobs.

AKW's role

Fundamentals + PromptingAccessible AI fundamentals, prompting frameworks, context and source quality.
Responsible Use + ReviewHallucinations and verification, human review, responsible use.
Applied WorkflowsWorkflow-specific examples, employee use-case discovery, prioritization frameworks.

Employees cannot identify sophisticated applications of a technology they do not yet understand.

Result

Employees left with a shared foundation for understanding AI, practical frameworks, reusable prompting resources, and a clearer process for identifying and evaluating potential use cases.

Different starting points. A consistent approach.

Understand the problem → Map the work → Identify the opportunity → Test what is possible → Build what is useful

Start with the problem, not the platform.

Tell me where work is repetitive, confusing, slow, or difficult to scale. We’ll figure out whether AI belongs there and what the next step should be.

Book a 30-Minute Strategy Call Amanda@akwaiconsulting.com