Lots of hype, no plan, scattered pilots.
What we did
- Ran an opportunity + risk assessment
- Prioritized a roadmap by ROI
- Stood up a governed first use case
Result Replaced scattered experiments with one funded roadmap and a working pilot.
AI Consulting
AI Enablement & Training
Upskill your team to use AI safely, effectively, and every day.
What it is
Adoption is the hard part.
The best AI system fails if no one uses it well. We train your team on practical workflows, prompt patterns, and the guardrails that keep usage safe and on-brand.
Core services include
- Role-based AI training workshops
- Prompt libraries and playbooks
- Internal usage policy and guardrails
- Tool selection and rollout support
- Office hours and ongoing enablement
- Adoption measurement
Definition
What is AI Enablement & Training?
AI Enablement & Training teaches your team how to use AI tools well in their actual jobs, covering practical skills, safe usage rules, and repeatable workflows so AI becomes part of everyday work instead of a one-off experiment.
How it works
It combines role-based training (prompting, tool selection, reviewing AI output), clear usage policies and guardrails around data and confidentiality, and hands-on workflow playbooks tailored to how each team actually works. Sessions, reference guides, and follow-up coaching turn one-time training into lasting habits.
Who it’s for
For businesses whose staff have access to AI tools but aren't using them consistently or safely; the outcome is faster, more confident daily work, fewer wasted hours, and less risk of misuse or data leaks, rather than a direct revenue lift.
In practice
A professional-services firm runs role-specific workshops so its account managers learn to draft client emails and summarize meeting notes with AI, paired with a short internal policy on what customer data may and may not be pasted into public tools.
Outcomes.
- Teams that use AI daily, not occasionally
- Consistent, on-brand outputs
- Fewer risky or wasted prompts
- A culture that compounds AI gains
See if AI Enablement & Training is the right move for your team.
Request a free quoteBuild, manage, run
We Train Your Team and Run It Alongside Them
Enablement only works when it comes from people who actually build and operate AI. Our senior team trains your staff on the same kinds of AI systems we build and run, from Claude and GPT to open models. We do not stop at a workshop. We embed, build playbooks against your real workflows, and stay close while your team takes ownership, so the skills stick after we hand off.
We measure enablement by adoption and output in live workflows, not attendance, and stay engaged through the agreed rollout and handoff plan, with playbooks and adoption metrics designed to help your team operate independently.
- We train teams on the exact stack we deploy, including models like Claude and GPT, platforms like Salesforce Agentforce, and open models and agent frameworks
- We build role-specific playbooks, prompts, and guardrails tied to your actual processes
- We set up governance and usage policies so adoption is safe and accountable
- We run side by side with your team during rollout, then hand off a system they can operate
See it in action
From AI-curious to AI-fluent, team-wide.
AI Enablement Hub · Your Brand
Cohort 2 · Week 6 of 8Weekly active use
82% ▲ from 31%
Certified teammates
14/19 5 in progress
Most-used prompt patterns · this week
Proposal first draft · Sales46 runs ✓ on-brand
Meeting notes → actions · Ops38 runs ✓ on-brand
Client-PII paste · guardrail3 caught · redacted
Next live session, Prompt patterns for Sales · Thu 10:00 · 12 enrolled
Illustrative example, styled to show the kind of output we deliver.
Selected work
Representative engagements.
Turning AI hype into a funded plan and a working first use case.
Wanted answers grounded in their own docs, not hallucinations.
What we did
- Built a RAG system over their knowledge base
- Added citations + an evaluation harness
- Access controls + monitoring
Result Deflected common tickets with sourced answers the team could trust.
Examples are anonymized to honor client NDAs and edited to illustrate typical scope, outcomes vary by market, budget, and starting point.
How & why it works
Adoption is a system, not a workshop.
Durable AI usage comes from removing the two things that stall it: uncertainty about what's allowed, and not knowing what to actually type. We install an approved-tool and use-case inventory, role-specific prompt patterns, and clear data-handling guardrails, then measure real adoption rather than attendance.
- Baseline usage and map use casesWe survey current tool usage and shadow real workflows to find the highest-volume, highest-friction tasks per role, then rank candidate use cases by time-saved potential and risk. This produces a scoped use-case inventory instead of generic "learn AI" training.
- Set guardrails and an acceptable-use policyWe define an approved-tool list and a tiered data-handling policy (e.g. public / internal / confidential) that spells out which data may enter which tool, when human review is mandatory, and how to handle PII, client data, and hallucination risk, aligned to your existing security and compliance posture.
- Build role-based prompt patterns and playbooksFor each priority use case we create reusable prompt templates, context-injection patterns, and worked before/after examples tied to real artifacts (a proposal, a support reply, a spec), so people copy a known-good pattern rather than starting from a blank box.
- Train in workflow, not in the abstractSessions are hands-on and role-specific, using the team's own tasks and tools. We appoint internal champions and run recurring office hours so questions get answered in context and new patterns get captured and shared instead of lost.
- Measure adoption and close the loopWe track weekly active usage, use-case coverage, and self-reported time saved, not seats sold or attendance. Low-adoption pockets get targeted follow-up, and champions feed new vetted prompts back into the shared library each cycle.
Worked exampleA 120-person professional-services firm where a handful of power users leaned on AI while most staff avoided it, unsure what was allowed.
- Ran a usage baseline and role interviews, then scoped an approved-tool list and a three-tier data policy (public / internal / confidential) mapping which data may enter which tool
- Built a vetted prompt library for the 6 highest-volume tasks (proposal drafts, meeting recaps, RFP responses) with worked before/after examples per role
- Delivered role-based hands-on sessions plus weekly office hours, and named 4 department champions to field questions and log new patterns
- Over the following quarter, weekly active usage rose from roughly 20% to about 65% of licensed seats, with champions contributing new vetted prompts each month
Why it works
People abandon tools that feel risky or that they can't get good output from, so the binding constraints on AI ROI are usually psychological and procedural, not technical. Removing the "am I allowed?" question with clear guardrails and the "what do I type?" question with proven patterns is what turns a spike of launch-week curiosity into steady daily use. Because a champion network and a living prompt library keep improving after we leave, capability compounds internally instead of decaying once the training ends.
FAQ
Questions, answered.
It is built around your real workflows, not generic slides. Before any session we interview your teams and review the tools and tasks they touch every day, then design role-specific tracks. For example, your sales team learns AI for call prep and follow-up while your finance team learns it for reconciliation and reporting, each using the actual tools and data they have access to.
We train on the stack that fits your security posture and budget, including Claude, OpenAI GPT, and open models like Llama, Qwen, and Mistral for private or on-prem use. If your Salesforce edition supports Agentforce, we enable it inside your existing CRM rather than bolting on a separate tool. We are not tied to one vendor, so the recommendation follows your needs, not a reseller agreement.
Safety is a core module, not an afterthought. We help you set an acceptable-use policy, define what data can and cannot go into which tools, and teach practical habits like spotting hallucinations and verifying outputs before they ship. For regulated or sensitive work, we steer teams toward private or self-hosted deployments with controls intended to keep sensitive data within approved environments, subject to your hosting, logging, integration, and governance requirements.
A typical engagement includes a discovery and needs assessment, role-based live workshops, hands-on exercises with your own data, a written playbook of prompts and policies, and a follow-up session weeks later to reinforce adoption. Most programs run a few weeks depending on team size and number of roles. We can deliver remote nationwide or on-site in the Phoenix area.
Standalone courses often teach concepts in the abstract, and adoption can stall without workflow-specific practice. We run the enablement hands-on with your real tasks, leave behind documented standards, and because NYFTY also builds and runs AI systems, we can connect what we teach to the actual workflows and automations in your business. The goal is daily, confident use, not a certificate that gets forgotten.
Let’s make it measurable.