AI at Work is one integrated program that communicates your AI strategy to your entire organization and builds AI literacy at every level.
AI literacy does not sit in one part of the org chart. AI at Work trains the four audiences whose engagement determines whether AI changes how the business actually runs — each with a learning path built for their role in the rollout.
Each component is built for a specific audience and the role they play in adoption. They draw on the same module foundation, sequenced and delivered for that audience.
Instructor-led training that gives executives the language to sponsor AI — not just authorize it. Delivered live by Jeff in three formats sized to your leadership team’s time and objectives, setting the tone the rest of the organization takes its cues from.
A practical training series that turns AI fluency into applied workflow change. It opens with a kickoff conversation from the CEO, followed by topic sessions from Jeff — each pairing a short podcast with a hands-on exercise.
A blended program that prepares managers to lead teams through the change in how work gets done — combining pre-work, live instructor-led sessions, online video modules, and assignments applied directly to their own team.
A blended program that equips your champion network to drive day-to-day adoption — combining pre-work, live instructor-led sessions, online video modules, and assignments. Champions spend the program designing, building, and deploying real AI solutions.
Every component of AI at Work draws on the same content foundation — a library of video modules with embedded coaching and applied exercises. Three tiers, from core foundations through advanced topics and role-specific editions.
Meet your instructor, understand the program structure, and learn why AI fluency is the most critical leadership skill of this decade.
Build a rock-solid understanding of what AI actually is, how it evolved, and the transformer architecture that powers the current revolution.
Understand what generative AI can actually do today, then master the skill of prompting — the new interface between humans and AI.
Move from experimentation to execution. Build an AI strategy that aligns with business objectives and creates sustainable competitive advantage.
The next frontier — AI systems that can plan, reason, and take autonomous action. Understand agentic architectures and what they mean for your organization.
Learn how to identify, evaluate, and prioritize AI use cases that drive real business value — not just impressive demos.
AI is only as good as its data. Understand data quality, content pipelines, and the foundational infrastructure that determines AI success or failure.
Build the governance frameworks, policies, and oversight structures required to deploy AI responsibly at enterprise scale.
AI changes how organizations operate and how people work. Lead the transformation in culture, skills, and operating models.
Synthesize the full program into an actionable framework. Your AI journey starts now — this training only works if you take action.
How AI systems are built and integrated inside a large organization. Key architectural decisions every leader should understand before committing to a platform.
What privacy means in an AI context — where data goes, how models are trained, and what regulators expect from organizations deploying AI with personal data.
The questions every organization must ask before signing with an AI vendor. How to evaluate capability claims vs. marketing and spot red flags before they become problems.
What vibe coding is and why it is changing software development. What non-technical leaders need to know to oversee AI-assisted development teams.
What board members are responsible for when it comes to AI oversight. The five questions every board should be asking management — and the fiduciary dimensions of AI risk.
The CEO’s five decisions that no one else in the organization can make. Why AI transformation fails when treated as a technology project — and how to lead it right.
Practical guidance for leading a team through the shift to working with AI: setting expectations, coaching direct reports, and managing the change in how work gets done.
Deeper enablement for the ambassador network that drives day-to-day adoption: coaching prompting, spotting use cases, and helping colleagues put AI to work.
The doing-to-directing shift — what AI is taking over, where human judgment grows in value, and what actually stays human. Includes a function-by-function breakdown, a self-audit framework, and five moves for professionals whose roles are at risk.
Moving from principles to policy — how organizations build ethical AI in practice. Covers bias, transparency, accountability, and building governance that holds up under scrutiny.
What every leader needs to understand about the threats AI creates and the defenses it enables. Covers AI-enabled attacks, new attack surfaces, the insider threat redefined, and the minimum security posture every organization needs before deploying AI broadly.
How to build the business case, establish the right KPIs, and hold your organization accountable for capturing real value. Covers the baseline imperative, the cost/revenue/risk framework, attribution, time horizons, and the governance model that makes measurement stick.
How AI is changing financial planning, analysis, and reporting. CFO oversight responsibilities, model risk, and where AI creates real efficiency versus where human judgment remains essential.
AI’s impact on content creation, personalization, and campaign management. How to use AI to generate customer insight at scale while maintaining brand integrity.
How AI tools are reshaping scheduling, document management, and coordination. Practical use cases that save real time — without requiring a technical background.
The risk and compliance implications of AI at enterprise scale. Model risk, algorithmic bias, and how to build a compliance posture that enables AI adoption rather than blocking it.
How AI changes the audit landscape — both as a tool auditors use and as a subject of audit review. Covers AI-assisted audit techniques and evaluating AI systems for risk.
Legal implications, risk exposure, and opportunities for legal professionals. Contract analysis, due diligence, regulatory research — and what lawyers need to know about AI liability.
Talent strategy, workforce planning, and employee experience in an AI organization. How HR leaders should think about reskilling, hiring, and building a culture that embraces AI.
How AI augments the sales process from prospecting to close. Pipeline management, forecast accuracy, personalization at scale — and where AI makes salespeople more effective, not replaceable.
How AI is reshaping executive search — from candidate research and LinkedIn mapping to client intelligence and search strategy. Covers the six core use cases and two emerging service lines that separate AI-enabled firms from the field.
How AI gives advisors more time with clients. Covers meeting prep, post-meeting summaries, email personalization at scale, and portfolio review generation — attacking the overhead that keeps advisors from the work only they can do.
How to research prospects in minutes instead of hours, personalize outreach at scale with compliance embedded in the prompt, mine your existing book for referral opportunities, and manage a pipeline that doesn’t rely on memory.
Using AI to surface planning gaps, optimize Social Security and retirement income sequencing, flag estate planning triggers, and run tax planning conversations — faster. AI generates the strategic framework; your planning software runs the numbers; you make the recommendation.
How to use AI as a research analyst, risk diagnostic, and client communication engine — without crossing the line into portfolio management. Covers research synthesis, manager due diligence, earnings transcript analysis, portfolio risk diagnostics, and market volatility communication.
How to get dramatically more out of every platform your firm already pays for using the Export → Upload → Prompt workflow. Covers CRM optimization, portfolio analytics, financial planning software, firm research, and navigating compliance restrictions.
How to use AI to understand your practice as a business. Covers book segmentation, revenue and profitability analysis, attrition risk scoring, growth pattern analysis, and capacity planning — all from a single quarterly spreadsheet.
What the AI-native practice looks like, what’s changing in the profession, and what’s not. A 90-day implementation roadmap, prompt library structure, team adoption framework, and the closing argument for why the best advisors will use AI to become more human — not less.
Tell us roughly how many learners and which audiences you need to reach, and we’ll come back with a program built to fit. Pilots available.
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