A comprehensive evaluation of your team's hardware, software configuration, AI tooling, and security posture — mapped against your stated AI goals for the next 12 months.
Acme Labs has a solid foundation for cloud-based AI tools but significant gaps in hardware capacity and policy that will limit your planned expansion into AI coding assistants and local model inference. 8 of 22 devices need attention before Q3.
| Device | Assigned To | Chip | RAM | Storage | Tier |
|---|---|---|---|---|---|
| MacBook Pro 16" | Sarah K. (CTO) | M3 Max | 36 GB | 1 TB | Ready |
| MacBook Pro 16" | James L. (Sr. Eng) | M3 Pro | 36 GB | 1 TB | Ready |
| MacBook Pro 14" | Alex M. (Sr. Eng) | M3 Pro | 18 GB | 512 GB | Ready |
| MacBook Pro 14" | Dev Team (x5) | M2 Pro | 16 GB | 512 GB | Capable |
| MacBook Air 15" | Design Team (x3) | M2 | 16 GB | 512 GB | Capable |
| MacBook Air 13" | Operations (x4) | M2 | 8 GB | 256 GB | Limited |
| MacBook Air 13" | Sales Team (x4) | M1 | 8 GB | 256 GB | Limited |
Your 8 devices with 8 GB RAM will struggle with AI-enhanced productivity tools (Zoom AI + Notion AI + Slack AI running simultaneously). These machines swap to disk frequently under normal workloads today — adding AI features will make this worse. Priority upgrade candidates for Q2.
Local AI models (even small ones) require 4-8 GB each. Combined with normal application storage, the 256 GB machines have less than 30 GB free. This prevents local model experimentation and limits future Apple Intelligence features.
Every device in the fleet has Apple Silicon with Neural Engine support. This means the entire team qualifies for Apple Intelligence features and has the basic hardware architecture for AI workloads. The constraint is RAM and storage, not chip capability.
All devices are on macOS 15.3 (Sequoia), which supports Apple Intelligence and the latest AI framework APIs. OS update compliance is excellent.
Current MDM configuration restricts installation of unsigned applications. This blocks Ollama, LM Studio, and other local inference tools that your engineering team has requested. Recommendation: Create an "AI Tools" exception group in MDM rather than a blanket policy change.
Full disk encryption is enforced fleet-wide. This is important for AI workloads where sensitive data may be processed locally.
Current AI tool adoption across your team, based on our device audit and employee interviews.
4 of 8 Copilot seats are on 8 GB machines where IDE performance degrades significantly with AI completions enabled. These engineers report disabling Copilot suggestions to keep their editor responsive — you're paying for AI they can't use.
During interviews, 4 team members reported using personal ChatGPT accounts to process work documents, customer data, and code. This data is subject to OpenAI's consumer terms of service and may be used for training. This is the highest-priority finding in this report.
6 engineering machines have API keys (OpenAI, Anthropic, Stripe) stored in unencrypted .env files. If any of these devices are lost or compromised, these credentials are immediately exposed. Recommend migrating to 1Password or similar secret management.
There is no documented policy for which AI tools are approved, what data can be shared with AI services, or how AI-generated code should be reviewed. This creates compliance risk, especially with client data.
Team members are signing up for AI tools individually with personal emails. There's no centralized visibility into what tools are in use, what data they access, or what they cost.
Define approved tools, data handling rules, and review requirements for AI-generated work. We can provide a template based on what we see working for teams your size. This addresses your biggest risk area immediately.
Move all plaintext credentials from .env files into 1Password (which you already use for team passwords). Set up .env files to pull from the vault. Simple change, major security improvement.
Replace the 8 M1/M2 Air machines (8 GB) with M3/M4 Air models (16 GB minimum). This unlocks AI productivity tools for your ops and sales teams, and makes Copilot actually usable for the 4 engineers on limited hardware. Estimated cost: $8,800–$12,000 (with trade-in credit).
Add Ollama, LM Studio, and Claude Code to your MDM allowlist. This unblocks your engineering team's local AI experimentation without removing security controls for unapproved software.
Move individual ChatGPT, Claude, and other AI subscriptions to team plans under IT management. This gives you visibility, central billing, and the ability to enforce data policies through admin controls.
| Item | Qty | Unit Cost | Total |
|---|---|---|---|
| MacBook Air M4 15" (16 GB / 512 GB) | 8 | $1,499 | $11,992 |
| Trade-in credit (M1/M2 Airs) | 8 | -$350 | -$2,800 |
| Setup, migration & enrollment (per device) | 8 | $0 | Included with Simple Devices |
| Net Hardware Investment | $9,192 |
This estimate assumes Apple's current trade-in values and education/business pricing. Actual costs may vary. Simple Devices handles procurement, configuration, data migration, enrollment, and old device recovery at no additional cost for managed clients.
Deploy AI usage policy draft. Migrate API keys to 1Password. Enable Apple Intelligence fleet-wide. Identify and consolidate shadow AI accounts.
Create MDM allowlist for approved AI tools. Deploy Claude Code to engineering team. Set up centralized AI tool billing. Begin hardware replacement planning.
Replace 4 engineering machines with 16 GB+ devices first (highest ROI). Migrate, enroll, recover old devices. Validate Copilot performance improvement.
Replace remaining 4 ops/sales machines. Full fleet at AI Capable or above. Re-assess readiness score.
Quarterly AI readiness check-ins. Track AI tool utilization vs. spend. Adjust policies as new tools emerge. Plan for next-gen hardware needs.
30 minutes. No commitment. We'll map your fleet to your AI plans and give you a clear picture of where you stand.
Book Your Free Audit