Current use and application landscape
Formal and informal AI usage, applications, systems of record, integrations, data flows, embedded capabilities, licensed tools, overlap, and unmet needs.
AI Adoption and Readiness Assessment
In development - pilot not open
We are developing an assessment that starts with business opportunities and readiness, then uses that evidence to inform platform requirements. A limited paid pilot is planned but not open. Scope, method, delivery readiness, pricing and release approval must be confirmed before participation.
Typical warning signs
What we examine
Formal and informal AI usage, applications, systems of record, integrations, data flows, embedded capabilities, licensed tools, overlap, and unmet needs.
Source quality, authority, ownership, permissions, confidentiality, privacy, retention, and lifecycle.
Failure impact, prohibited uses, representative evaluations, quality checks, approval, escalation, and accountability.
Qualified workflows, vendor-neutral platform fit, measures, observability, support, recovery, portability, ownership, and stop conditions.
Proposed assessment outputs
These are proposed outputs, subject to method validation and pilot scope. No assessment package or pilot place is currently available to book.
Applications, owners, authoritative systems, interfaces, material data flows, and integration dependencies.
Knowledge sources, authority, ownership, access boundaries, confidentiality, retention, and material gaps.
Current workflow, measures, candidate capabilities and platform requirements. A final selection depends on evidence and agreed scope; a validation path may be the appropriate result.
Process, data, access, governance, adoption, safety, and operating gaps, including reasons to defer or stop.
Bounded inputs and outputs, representative tests, measures, review steps, permissions, rollback, and stop conditions.
Training, governance, implementation, operating ownership, improvement cadence, and review sequence.
Planned limited paid pilot
The pilot is planned but not open. Development, human rehearsal, method validation, commercial terms and release approval remain outstanding. The principles below describe the intended paid assessment model after those gates are complete.
The first conversation is a brief no-cost fit and scope discussion. Evidence collection, analysis, scoring, findings, and roadmapping begin only after a written scope and fixed fee are approved.
The completed assessment organizes the material findings, risks, responsibilities, decisions, and sequenced roadmap so leadership can act with an internal team, Carolina Technology Pros, an existing provider, or another qualified provider. Implementation is optional, priced separately, and the assessment fee is not an implementation deposit or automatic credit.
From diagnosis to delivery
The assessment identifies the responsible path forward. Implementation is not assumed and is scoped separately only after the findings, priorities, dependencies, and ownership are clear.
Primary service outcome
Connect websites, business applications, Microsoft 365, information, and workflows through a practical architecture built around business value.
Explore servicePrimary service outcome
Explore three practical AI courses, individual coaching and leadership advisory. Scope, platform access and delivery readiness are confirmed before work begins.
Explore servicePrimary service outcome
Explore AI Foundations, AI Practitioner and Advanced AI Practitioner: eight lessons each, with weekly, accelerated or 4.5-hour workshop delivery.
Explore serviceRelated service outcome
Help your small business get more value from Microsoft 365 while improving files, collaboration, access, devices, governance, and continuity.
Explore serviceGo deeper
Use these practical resources to prepare questions, compare options, and decide what evidence should come next.
Compare ChatGPT, Claude, Copilot, and Gemini by business fit, governance, cost, and adoption before choosing a platform and planning a controlled pilot.
Read resourceLearn how governed industry, business, competitive, and client context can turn general AI capability into accountable support for one bounded workflow.
Read resourceEvaluate use cases, information sensitivity, human review, governance, and proof-of-value before broad AI adoption.
Read resourceSeparate AI drafting from controlling law, maintained legal guidance, firm precedents, matter records, and accountable attorney verification clearly.
Read resourceCompare legal AI choices through authoritative content, governance, integration, support, portability, and verified reviewer effort before selection.
Read resourceBuild a law-firm AI operating boundary around confidentiality, verification, supervision, client communication, fees, approved tools, and accountable review.
Read resourceA practical first conversation
This is a fit conversation, not pilot enrollment or a delivery commitment.