Services

AI Implementation & Assurance

AI adoption roadmaps, workflow automation, responsible implementation and independent system assessment, with focused support for healthcare and public-sector organizations.

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Choose where to start

AI strategy & governance

Prioritize use cases, define measurable value and establish ownership, oversight and an adoption roadmap.

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Implementation & automation

Configure workspaces and bounded workflows, test a pilot and prepare staff to use it.

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AI Assurance

Assess a system's transparency, human review, access, burden and accountability through a separate engagement.

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Many small practices see the potential in AI but lack a dedicated team to turn scattered experiments into a reliable operating workflow. Arclight helps identify where the work is repetitive, where judgment must stay with staff, and what can be implemented safely and usefully.

Our experience includes administering and deploying ChatGPT Enterprise for healthcare use, configuring workspace access and controls, and building agent-assisted workflows. We can support general business automation as well as healthcare-specific implementation, from a first pilot through staff training and ongoing refinement.

Start with the business priority, then build a sequenced AI adoption roadmap. We help prioritize use cases, define measurable value, establish governance and an operating model, and assign ownership and sponsor responsibilities. Pilot evidence informs what to expand, change, or stop as workflows move from design through deployment.

Professional development

OpenAI Academy · AI Leadership

Lance McNeill completed OpenAI Academy's AI Leadership course. The course covers aligning AI adoption with business priorities, sequencing a roadmap, assigning governance and ownership, and using evidence to guide deployment and expansion.

AI roadmap prioritization
Evidence-backed AI value articulation
AI governance and operating model design
AI adoption planning and change leadership
Responsible AI solution design and deployment

Issued October 6, 2026 · Credential expires April 6, 2027

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Wound-Care EMR Templates & Documentation Optimization

For wound-care documentation inside your EMR, template development is led by an advanced practice provider: a clinical nurse specialist with years of experience in wound care. Work with your vendor on template content, conditional fields, reassessment prompts, and carry-forward controls.

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Audience

Independent healthcare practices
Specialty clinics and provider groups
Practice administrators
Clinical operations teams
Organizations starting or expanding AI use

From use case to working practice

AI roadmap prioritization and workflow discovery
Evidence-backed AI value articulation and success measures
AI governance and operating model design
Platform selection and workspace administration
Role-based access and data-handling design
Agent-assisted and repeatable task automation
Human review, escalation, and quality checks
AI adoption planning, change leadership, and staff training
Stakeholder alignment, governance specifications and pilot evaluation
AI Assurance assessments

Where implementation can help

Practice Operations

Map high-friction administrative work and pilot tools for drafting, organizing, routing, and checking routine materials.

Healthcare Documentation Workflows

Design clinician-reviewed assistance for patient communications, referral and authorization drafts, policy lookup, and documentation preparation.

Workspace & Agent Deployment

Configure eligible enterprise workspaces, permissions, approved tools, reusable instructions, and bounded agents around the practice's actual workflow.

Governance & Training

Establish an AI operating model with sponsors, workflow owners, approved uses, review responsibilities, escalation paths, and staff training before broader adoption.

What an engagement can deliver

Sequenced AI adoption roadmap and prioritized workflow map
Business-value measures and pilot evaluation criteria
Governance, ownership, and sponsor responsibilities
Configuration and access-control plan
Pilot workflow or agent with human checkpoints
Testing criteria and observed results
Staff instructions and training
Rollout and improvement roadmap

A practical rollout

Find the right workflow

Prioritize a specific workflow around business value. Map its source data, users, exceptions, and current review process, then define success measures.

Set the safeguards

Assign workflow ownership and sponsorship. Confirm applicable agreements, approved features, permissions, data boundaries, and human decision points.

Build and test

Configure a limited pilot, test real-world edge cases, and measure usefulness and error modes before expansion.

Train and improve

Train the team and review observed performance against the success measures. Use that evidence to decide what to expand, change, or stop.

AI Assurance

Independent assessment of high-stakes AI systems for objective alignment, transparency, human review, appeal pathways, access, burden, and accountability.

Implementation includes testing the workflows we help build. Independent AI Assurance is a separate assessment engagement focused on the system's governance, evidence and effects on people.

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Assurance dimensions

Objective and incentive alignment
AI governance, operating model, and ownership clarity
Stakeholder participation
Human review and appeal pathways
Rationale transparency and documentation
Accuracy, access, and burden metrics
Independent oversight and public reporting

Outputs

AI Assurance assessment
High-level grade or rating
Explanatory findings
Recommended corrective actions
Optional briefing

Framework in development. Methodology and rating scale will be published separately.

Implementation case study

What the CMS WISeR AI rollout shows about readiness

WISeR is a Medicare model launched in six states that uses AI technology together with the clinician review to assess selected services before payment. Six participating companies were named in November 2025. Live requests began 60 days later, while records from Ohio showed unfinished end-to-end testing.

By April, Ohio's Medicare contractor reported requests on hold and claims suspended. The timeline below follows the rollout from participant selection through those reported backlogs. It illustrates why a pilot needs tested handoffs, a correction path, and a way to pause before expansion.

WISeR timeline: six participants were named November 6, 2025; live requests began 60 days later; CGS marked Ohio yellow in December and red on April 6 after requests and claims accumulated. — Figure 1. WISeR rollout milestones and Ohio implementation status. Innovaccer proposed a 45-to-60-day auto-affirming period; the reviewed records do not establish how long it actually operated. April counts are a CGS operating snapshot, not a count of unique patients. Sources: CMS WISeR model and CMS records released by EFF, PDF pp. 200–201, 216–218, 220–221.

Read the WISeR Case Study

PHI use is scoped only after confirming applicable business associate agreements, HIPAA-eligible products and features, practice policies, minimum-necessary access, retention, and human oversight. No platform or configuration alone guarantees HIPAA compliance.

AI Implementation & Assurance

AI adoption roadmaps, workflow automation, responsible implementation and independent system assessment, with focused support for healthcare and public-sector organizations.

Discuss AI Implementation Explore AI Assurance