In 2025, as AI swept through the enterprise, layoffs at major tech firms made headlines.
But behind the headlines was a quiet transformation: many of the same companies rehired—not for AI model development, but for roles that could apply AI in marketing, finance, HR, and operations.
Klarna made headlines cutting workers, then did this.
IBM Chief Executive Arvind Krishna said the tech giant has used artificial intelligence, and specifically AI agents, to replace the work of a couple hundred human resources workers. As a result, it has hired more programmers and salespeople, he said.
These aren't technical jobs in the traditional sense. They're AI-augmented roles—hybrid positions where domain expertise is amplified by AI fluency. Think account managers who use AI to summarize CRM updates, analysts who prototype forecasts with GenAI, or HR leads who automate onboarding sequences.
This is the new hiring frontier. And if you're mid-career, it's your next big move.
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AI-Augmented Roles Are the New Tech Jobs—And They’re Hiring
They’re not in engineering. They’re in your department—and they’re your best bet for staying relevant.
Imagine it’s time to do your next performance review. You start doing your self-evaluation. You start looking through your progress over the year and since adopting AI into your workflows. Your output increased by 30%. That’s not just a pipe dream—it’s a proven possibility.
AI-augmented roles are transforming what it means to be "technical." These aren't data scientists or ML engineers. They're marketers using AI to generate client-ready copy. They're sales leads who automate CRM entries. They're operations managers who prototype new processes using AI-powered tools.
These professionals aren't eliminating jobs with AI—they’re eliminating busywork and reclaiming time for strategic contributions.
Examples:
HR leads creating onboarding plans with AI templates.
Marketing teams using prompt libraries to generate first-draft campaign content.
Legal staff using structured prompts for initial contract reviews.
Sales reps turning meeting transcripts into follow-ups with AI.
How to Augment Your Role with AI
Real examples from top firms showing how AI fluency drives rehiring and results.
At Goldman Sachs, AI assistants help analysts draft investment memos. Goldman Sachs’ CEO says that AI can draft 95% of an IPO prospectus in minutes. Instead of replacing them, the tool expands capacity—letting teams handle more deals with higher quality.
At Shopify, they are enabling their customers with AI, using tools like Shopify Inbox with Shopify Magic and Sidekick, you can review, edit, and respond to customer messages to drive conversions and turn more chats into checkouts.
These aren't one-off pilots. They're strategic deployments. And they reflect a broader pattern: companies that laid off generic roles are rehiring AI-augmented ones.
How to Implement
Tactical steps to shift from job protection to career acceleration.
Identify friction points. List 3 tasks you do weekly that are repetitive, time-consuming, or rule-driven.
Use our AI Toolbox to find examples—and start building your own. Our curated collection includes tools across writing, automation, meetings, research, and process design.
Example tools:
ChatGPT: Flexible general-purpose assistant.
Scribe: Auto-generates documentation.
Tactiq: Summarizes meetings.
Magical: Automates CRM input.
NeuronWriter: Supports SEO-focused content.
Create your own AI Toolbox. Build a personal set of tools that reflect your job’s needs. Categorize by task type—e.g., writing, summarizing, planning, tracking.
Document your workflow. Save before-and-after examples. Log effective prompts. Note the gains. Turn this into a reusable playbook.
Make the case in performance reviews. Show metrics: "Cut reporting time by 60%" or "Reduced email response prep from 30 min to 5." Demonstrate how your AI fluency drives measurable results.
Common Missteps
What slows down adoption—and how to sidestep it.
Treating AI like a gadget instead of a teammate.
Over-indexing on general-purpose tools without fitting them to your workflow.
Not tracking performance impact—and losing credibility as a result.
Business Value
Why AI-augmented roles are being fast-tracked and funded across the org.
They deliver ROI in weeks, not quarters.
They increase retention by removing low-value work.
They create upward mobility: professionals who adopt AI are more likely to lead change—not be disrupted by it.
Bottom line: you don’t need to code. You need to know how to think with AI—and how to show the results.
Tactiq – AI-driven meeting workflow automation tool. Automates meeting insights, updates, and actions.
Magical – AI agent for autofill automation. Seamlessly fills out forms on platforms like Salesforce, HubSpot, and more.
NeuronWriter – AI-powered content optimization tool. Helps plan, write, and optimize content with user intent in mind.
Scribe – AI-powered process documentation tool. Automatically creates step-by-step guides with screenshots and text instructions.
Prompt of the Week: AI Upskilling Plan
Whether you’re leading AI transformation across a company or pursuing personal upskilling to stay ahead in an AI-driven workplace, success requires more than just access to tools—it demands intentional learning aligned with specific outcomes.
This prompt provides a structured framework to design an AI upskilling strategy tailored to the needs of organizations or individuals. It guides you through identifying the right roles, use cases, learning formats, and measurement methods to ensure the effort drives business value.
For companies, it supports scalable, role-specific enablement aligned with strategic goals like improving efficiency or launching new AI-powered products and services. For individuals, it helps define a focused path to build AI fluency that matches your career goals and the way you expect to work with AI—whether as a user, collaborator, or builder.
Start by answering a series of targeted questions. These inputs will feed into a comprehensive plan that includes training goals, delivery formats, timelines, and success metrics—all designed to produce measurable results.
To get started just cut and paste this into your favorite AI chatbot.
You are an expert AI transformation consultant. Develop a comprehensive AI upskilling strategy for one of the following contexts:
1. **Organization** rolling out AI across its workforce
2. **Individual professional** seeking to build AI capability
The strategy must be structured, role‑specific (or task‑specific for an individual), and designed to achieve one or both measurable outcomes:
- **Improved Efficiency** – time savings, automation, cost reduction
- **New Opportunities** – AI‑enabled products, services, or business models
---
### Step 1 – Gather Contextual Inputs
Ask the client only the questions relevant to their situation.
#### 1. Context Overview
- **If an organization**
- Company name and industry
- Total number of employees
- AI maturity level (Emerging / Developing / Advanced)
- Strategic objective (Efficiency, Opportunity, or Both)
- Primary business goals for AI adoption
- **If an individual**
- Current job title, function, and industry
- Years of experience in the role
- Personal AI maturity level (None / Basic / Intermediate / Advanced)
- Personal objective (Efficiency, Opportunity, or Both)
- Career or business goals driving AI adoption
#### 2. Role or Task Segmentation
- **Organization:** Key functions/departments (e.g., Exec, Ops, HR, Finance, Product, Marketing, IT) and head‑count per area
- **Individual:** Core responsibilities or workflows to be improved with AI
For each function or task, capture:
- Current AI literacy (None / Basic / Intermediate / Advanced)
- Expected AI interaction type (Consumer / Collaborator / Builder / Maintainer)
#### 3. Use‑Case Alignment
- Top 3 AI initiatives or capabilities being prioritized
- Functions or tasks most affected by these use cases
#### 4. Training Objectives
For each function (organization) or key task (individual):
- Required AI fluency (Strategic / Operational / Technical)
- Preferred training modality (Async course / Live session / Hands‑on lab)
- Target business outcome (Efficiency / Opportunity / Both)
#### 5. Measurement Plan
Recommend KPIs and tracking methods:
- AI adoption and usage rates (team‑level or personal)
- Training completion and engagement
- Efficiency gains (time saved, cost reduced)
- Innovation metrics (new offerings, customer engagement, or personal revenue/recognition)
#### 6. Change Management & Support
- **Organization:** Internal owner of training, existing L&D resources, reinforcement mechanisms (champions, office hours, forums)
- **Individual:** Accountability plan (mentor, peer group, scheduled practice), resources or communities for ongoing support
---
### Step 2 – Generate the Structured Strategy
Using the collected inputs, produce a tailored AI‑upskilling strategy with these sections:
1. **Executive Summary** – Brief context and intent (corporate or personal).
2. **Strategic Objectives** – State focus on Efficiency, Opportunity, or Both.
3. **Role‑ or Task‑Based Training Matrix** – Map each role/task to literacy level, modality, and desired outcome.
4. **Delivery Timeline** – Phased rollout by quarter/milestone (organization) or weekly/monthly plan (individual).
5. **Success Metrics** – How impact will be measured.
6. **Post‑Training Support Recommendations** – Reinforcement approach (champions, refreshers, forums—or personal checkpoints, continued practice, and community involvement).
---
### Tone Guidelines
- Write concisely and professionally.
- Avoid generic advice; anchor every recommendation to the stated objectives and maturity level.
- State actions, owners, and timelines clearly.
- Use business‑relevant language.
I appreciate your support.
Your AI Sherpa,
Mark R. Hinkle
Publisher, The AIE Network
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