Under the Radar

UNDER THE RADAR – Friday, January 23, 2026

by

The Extraction Layer: When Platforms Come for Your Job

ServiceNow + OpenAI = The Complete Automation Stack. Google captures commerce. OpenAI formalizes extraction. Your timeline: 12-18 months before critical mass.

TABLE OF CONTENTS

  • Bottom Line Up Front
  • I. What Happened This Week
  • II. The Extraction Model Comes for Workers
  • III. Who’s At Risk – The Enterprise Operations Layer
  • IV. What Happens When Entry-Level Work Disappears?
  • V. Top 5 Career Opportunities This Week
  • VI. Career Intelligence Skills – Week 7: Threat Assessment
  • VII. Action Items
  • VIII. Resources & Community
  • IX. What to Watch Next Week
  • X. Bottom Line
  • XI. Methodology & Sources

BOTTOM LINE UP FRONT

This week, the automation stack became complete. ServiceNow handles enterprise workflows (IT tickets, HR queries, business operations). OpenAI provides the agents that automate responses. Together, they eliminate the humans who used to coordinate those systems.

Meanwhile, OpenAI formalized the extraction model: they plan to take revenue shares from customer discoveries and innovations. Not charging for tool access – claiming ownership of what customers create. This is wealth extraction with algorithmic justification.

Google inserted itself between every customer and merchant with Universal Commerce Protocol. Twenty major companies signed on: Shopify, Walmart, Target, Visa, Mastercard, PayPal. When AI handles the checkout, merchants lose the last customer touchpoint – and workers lose jobs on both sides.

Anthropic hit $2.7 billion annual run rate. From $200 million to $2.7 billion in 18 months (MIT research). Enterprise adoption isn’t speculation – it’s measurable and accelerating.

Your timeline: 12-18 months before ServiceNow/OpenAI deployment reaches critical mass in enterprise operations. IT support, HR coordinators, business operations roles face direct automation. Retail sales faces 2-3 year timeline as commerce layer deploys. This isn’t distant future – this is procurement departments signing contracts right now.

The job market remains weak. Most recent BLS data (December 2025, released January 9): Only 50,000 jobs added, 4.4% unemployment. Next report not until February 6. AI deployment accelerates into that weakness.

Career Intelligence Skills starts this week: Not Python tutorials. Not resume tips. The honest question: Are you in danger, and do you have the courage to act on it?

But we also need to acknowledge something uncomfortable: Individual career intelligence helps the 20-30% of workers who have runway, capability, and time to transition. For the other 70%? We need systemic solutions we can’t provide through career advice alone.

I. WHAT HAPPENED THIS WEEK

Monday-Wednesday (Jan 20-22):

🎯 ServiceNow + OpenAI = The Complete Stack

  • ServiceNow handles enterprise workflows: IT service desk, HR support, change management, incident response
  • OpenAI agents automate responses to those workflows
  • Result: Humans who coordinate between employees and systems become redundant
  • Target roles: IT support specialists, HR coordinators, business operations, help desk

💰 OpenAI’s Extraction Model Announced

  • OpenAI announced plans to take revenue shares from customer AI-aided discoveries
  • Not tool licensing fees – ownership stakes in what customers create
  • Source – The Information: “OpenAI Plans to Take Cut of Customers’ AI-Aided Discoveries”
  • No implementation date announced yet, but intent is clear and this will no doubt be watched
  • This formalizes extraction: inserting rent-seeking into value chain

💳 Google Captures the Commerce Layer

  • Google Universal Commerce Protocol announced January 11, 2026
  • Twenty companies signed on immediately: Shopify, Walmart, Target, Etsy, Wayfair, Best Buy, Macy’s, Home Depot, etc
  • Payment processors integrated same day: Mastercard, Visa, PayPal, Stripe, American Express
  • Richard Crone (CEO, Crone Consulting) to American Banker: “If the checkout goes to Gemini, the merchant loses the last touch point”
  • That touch point accounts for 33-76% of upsell/cross-sell opportunities
  • Google now sits between every customer and every participating merchant

📈 Anthropic Revenue Explosion

  • $2.7 billion annual run rate (Bloomberg)
  • From ~$200M to $2.7B in 18 months
  • Validates enterprise adoption acceleration
  • CEO discussing potential IPO at Davos
  • Possibly connected to IRS AI deployment (100,000+ employee agency)

🏭 Infrastructure Acceleration

  • Microsoft: 15 new data centers in Mount Pleasant, Wisconsin (Journal Sentinel – paywalled but confirmed)
  • Google: Winning race for data center power capacity
  • Federal policy: $83B in energy loans cancelled/revised
  • Grid connection acceleration plan announced
  • US power grid changes to speed data center connections

💡 Platform Consolidation Continues

  • Salesforce + Google Universal Commerce Protocol
  • Apple Siri revamp with Google Gemini (second half 2026)
  • Apple considering running chatbot on Google Cloud + TPU chips
  • Apple wearable pin development (AI hardware competition)

🏘️ Community Resistance

  • Columbiana, Alabama town hall on data center proposal
  • Pattern continues: local opposition vs developer pressure

II. THE EXTRACTION MODEL COMES FOR WORKERS

Last Tuesday we published “The Extraction Protocol” analyzing infrastructure. This week proved the same pattern applies to employment AND commerce.

OpenAI Announces Extraction Model

OpenAI announced plans to take revenue shares from customer AI-aided discoveries (no implementation date yet). Not tool licensing fees – ownership stakes in what customers create using OpenAI’s platforms.

This formalizes the extraction pattern: Instead of charging for access, they claim percentage of value created. It’s not “sell you a tool” – it’s “insert ourselves into your value chain and take a cut of everything you produce.”

Google Inserts Commerce Rent Layer

Google Universal Commerce Protocol creates a new extraction point between consumers and merchants. Twenty major companies already signed on: Shopify, Walmart, Target, payment processors Visa, Mastercard, PayPal.

Richard Crone, CEO of Crone Consulting: “If the checkout goes to Gemini, the merchant loses the last touch point.” That touch point accounts for 33-76% of upsell opportunities.

What this means:

  • Google sits between every customer and merchant
  • Controls customer interaction, product recommendations, purchase decisions
  • Merchants lose direct relationships, upsell opportunities, customer data
  • Once critical mass achieved: Google sets terms, merchants must comply

This is the app store model (Apple/Google taking 30%) applied to ALL retail commerce.

For workers: Those 4.6 million retail sales jobs disappear when AI agents handle interactions AND merchants lose direct customer relationships. No salesperson needed. No direct merchant contact. Just AI intermediary extracting rent from every transaction.

The MIT Research Applied to Careers

MIT documented companies trapped by switching costs: They stay locked into expensive closed AI platforms even when better open alternatives exist. Potential savings if they switched: $24.8 billion. They don’t switch because “systems and workflows become adapted to idiosyncratic behaviors of specific models.”

Workers face the identical trap:

You specialize in Company X’s proprietary CRM system. You become expert in Tool Y’s specific workflows. You build a career around Platform Z’s architecture. Then the platform gets automated or replaced, and your specialized skills become worthless.

The switching costs trap works both ways:

  • Companies can’t easily switch platforms (even when better alternatives exist)
  • Workers can’t easily switch careers (even when their positions are being automated)

The Acceleration Into Weakness

Most recent employment data (December 2025, released January 9, 2026):

  • Total nonfarm payroll employment: +50,000 jobs
  • Unemployment rate: 4.4%
  • Next Employment Situation report: February 6, 2026

That’s weak job creation. And AI automation accelerates into that weakness.

For workers, extraction means:

  • Productivity gains from AI don’t flow to you
  • Efficiency improvements justify eliminating your position
  • Companies capture automation value, workers bear displacement costs
  • No profit-sharing, no transition support, no protection

ServiceNow + OpenAI partnership proves it: The complete automation stack is here. The technology works. Enterprise procurement is signing contracts. Your 12-18 month timeline starts now.

III. WHO’S AT RISK – THE ENTERPRISE OPERATIONS LAYER

ServiceNow Workflow Automation Targets:

IT Support & Service Desk (500,000+ roles)

  • Tier 1/2 technical support
  • Help desk specialists
  • IT ticket management
  • Password resets, access requests, basic troubleshooting
  • Timeline: 12-18 months as enterprises deploy

HR Support & Coordination (300,000+ roles)

  • HR service representatives
  • Benefits coordinators answering routine questions
  • Onboarding coordination
  • Leave management support
  • Timeline: 12-18 months for enterprise rollout

Business Operations Coordination (400,000+ roles)

  • Operations coordinators
  • Process documentation specialists
  • Change management support
  • Workflow coordination between departments
  • Timeline: 18-24 months – more complex integrations

The Pattern: If your job is “coordinate between employees and systems” or “answer routine questions by looking up information in systems,” you’re in the automation path.

Google Commerce Layer Targets:

Retail Sales Workers (4.6 million jobs – BLS)

  • Store sales associates
  • Product specialists
  • Customer service in retail settings
  • Timeline: 2-3 years as Universal Commerce reaches critical mass

When customers ask AI agents “find me winter boots under $100,” they’re not walking into stores and talking to salespeople. When AI processes the transaction, customer service representatives aren’t answering questions.

Not at Immediate Risk:

  • Physical presence requirements (healthcare patient care, skilled trades)
  • High-touch human judgment (complex negotiations, crisis management)
  • Unpredictable problem-solving (emergency response, creative work)
  • Regulatory/licensing protections (some healthcare, legal, financial roles)

IV. WHAT HAPPENS WHEN ENTRY-LEVEL WORK DISAPPEARS?

Look at what’s being automated:

Already Happening (2025-2026):

  • Retail sales: 4.6 million jobs (Google Universal Commerce)
  • Customer service: Millions (Salesforce: 4,000 cuts citing AI)
  • Basic IT support: 500,000+ (ServiceNow + OpenAI)
  • Data entry/processing: Rapid automation
  • Manufacturing pick and pack: Robots handling warehouse fulfillment, assembly line work
  • Quality control inspection: Computer vision systems replacing human inspectors
  • Agricultural produce picking: Robots harvesting strawberries, apples, lettuce – the traditional “starter” farm labor
  • Food service prep: Automated cooking systems, robotic food assembly

Coming Soon (2-5 Years):

  • Healthcare administration: 1+ million jobs
  • Complex warehouse work: Humanoid robots reaching human-level dexterity
  • Remaining food service: AI ordering, routing, delivery coordination
  • Construction labor: Bricklaying robots, automated framing, 3D-printed structures
  • Landscaping/grounds maintenance: Autonomous mowers, robotic tree trimming
  • Cleaning services: Commercial cleaning robots becoming cost-effective

What’s LEFT for Entry-Level Workers?

  • Healthcare direct patient care (requires certification/training)
  • Skilled trades requiring problem-solving (requires apprenticeship, physical capability)
  • Specialized technical roles (requires education/credentials)

Notice what’s missing? The entire bottom rung of the economic ladder. The jobs people could get “tomorrow to pay rent this month.”

The Manual Labor Question

Palantir CEO Alex Karp recently stated that people will be doing manual labor in the future as AI advances. It’s worth examining this claim against current automation trends:

What the robotics industry is demonstrating:

Agricultural automation:

  • Strawberry picking robots (delicate work requiring dexterity)
  • Apple harvesting systems (reaching, grasping, damage detection)
  • Lettuce harvesting with precision cutting
  • Traditional “last resort” farm labor being automated

Manufacturing and warehouse:

  • Pick and pack robots in major warehouses
  • Quality control via computer vision (faster and more accurate than humans)
  • Assembly line automation accelerating
  • Chinese factories that replaced American manufacturing now automating

Construction:

  • Bricklaying robots: 3,000 bricks/day vs 500 for humans
  • 3D-printed structures requiring minimal labor
  • Automated framing and welding systems

The dexterity gap is closing:

  • Humanoid robots (Figure, Tesla, Boston Dynamics) reaching human-level hand control
  • Cost curves dropping toward economic viability
  • Industry projections: 5-10 year timeline for scaled warehouse/manufacturing deployment

The math problem:

  • Millions of workers will be displaced from both office AND manual labor
  • Remaining manual work requires unpredictable environments, creative problem-solving, or specialized skills
  • That’s a much smaller labor pool than current employment

The question isn’t whether some manual labor will exist – it will. The question is whether there will be enough manual labor jobs for the millions of workers being displaced from both knowledge work AND traditional manual work simultaneously.

The Double Displacement

Office workers think: “At least I can do manual work as backup” Manual workers think: “At least my physical work can’t be automated”

Both are wrong. The automation is happening on both ends:

  • Knowledge work: AI handles analysis, coordination, customer service
  • Physical work: Robots handle picking, packing, harvesting, assembly

There’s no “fallback” tier anymore.

The traditional economic ladder:

  1. Entry-level manual labor → save money
  2. Entry-level office work → build experience
  3. Skilled work → build career
  4. Specialized/management → stability

Being replaced with:

  1. ~~Entry-level manual labor~~ (automated)
  2. ~~Entry-level office work~~ (automated)
  3. Skilled work → requires 2-4 years training + physical capability OR credentials
  4. Specialized/management → small labor pool, high competition

The bottom two rungs are disappearing. You can’t “start at the bottom and work up” when the bottom doesn’t exist.

What This Actually Means

For the kid graduating high school in 2026:

  • Can’t get retail job (automated)
  • Can’t get fast food job (increasingly automated)
  • Can’t get warehouse job (robots)
  • Can’t get farm labor job (robots)
  • Can’t get entry office job (AI)

Options:

  • Healthcare training (if they can afford it and have aptitude)
  • Trades apprenticeship (if physically capable and can find one)
  • College degree (if they can afford it, 4-year delay)
  • ???

For the displaced 45-year-old retail worker:

  • Can’t transition to warehouse (robots replacing those jobs too)
  • Can’t transition to farm labor (robots)
  • Can’t transition to manufacturing (automated)
  • Can’t do trades (physical limitations, age discrimination)
  • Can’t do healthcare (training time + physical demands)

Options:

  • ???

Small Business: Necessary But Not Sufficient

Small businesses will remain more human-centered:

  • Local knowledge matters (recommendations, relationships built over time)
  • Flexibility and customization (can’t be easily standardized)
  • Community connection (people prefer local for many services)
  • 33 million small businesses represent capacity-building, not extraction

But they can’t absorb millions of displaced workers:

  • Most small businesses employ 1-10 people
  • One local hardware store (5 employees) doesn’t replace the Home Depot that automated 50 positions
  • Limited capacity to match corporate benefits or stability
  • Many still use automation where it makes economic sense

Small businesses are part of the solution – they build local capacity rather than extract value. But they’re not sufficient at the scale we’re discussing.

The Policy Vacuum

What’s needed but not happening:

  • Regulation on automation deployment speed
  • Mandatory retraining funded by companies automating positions
  • Profit-sharing from productivity gains with displaced workers
  • Expanded safety nets, not contracted ones
  • Public employment programs
  • The free market will not be able to react fast enough to address the elephant in the room – who will be buying and how?

What we’re getting instead:

  • Warner-Hawley bill: Requires REPORTING AI-related layoffs, not preventing them
  • Social program cuts while displacement accelerates
  • Companies keep all productivity gains
  • Workers bear all transition costs

What This Means For Under The Radar

What we CAN do:

  • Provide career intelligence for workers who have transition capability
  • Document displacement patterns so communities see them coming
  • Offer honest assessments without false hope
  • Help the 20-30% who can navigate this with proper intelligence

What we CAN’T do:

  • Solve systemic unemployment through individual career advice
  • Create entry-level jobs that no longer exist
  • Provide solutions for workers without financial runway or physical capability
  • Fix policy failures through career guidance

Why we’re still publishing:

Because millions of workers CAN benefit from career intelligence. Healthcare coordinator positions exist (52,000+ openings). Electrician apprenticeships pay while training. Strategic positioning matters for those who can use it.

But we won’t pretend individual solutions solve systemic problems. The worker with savings and capability can transition to skilled trades. The worker without either needs policy solutions we can’t provide through career advice.

V. TOP 5 CAREER OPPORTUNITIES THIS WEEK

Scoring Criteria:

  • Market Demand: 30%
  • Entry Speed: 25%
  • Income Potential: 25%
  • Future Viability: 15%
  • Scam/Risk Factor: 5%

Threshold: 70/100 minimum to make Top 5

Wonder why we rank the top 5 as we do? Click for full Top 5 Ranking Primer

#1. Healthcare Direct Patient Care (RN, Medical Assistant, Physical Therapy)

Score: 87/100 ⬆️ (Holding #1)

Market Demand (28/30):

  • BLS: 1.9 million healthcare openings projected annually through 2034
  • RN: 189,100 openings/year, 5% growth (faster than average)
  • Medical assistants: 16% growth through 2031
  • Healthcare + social assistance: Fastest growing sector at 8.4%
  • Monster 2026 report identifies healthcare as “strongest hiring engine”

Entry Speed (23/25):

  • Medical assistant: Certification in months, $38K-$48K entry
  • LPN: 12-18 months, immediate employment
  • RN (ADN): 2 years, $65K-$95K starting
  • Physical therapy assistant: 2 years, $75K+ starting
  • Multiple entry points, paid apprenticeships available

Income Potential (20/25):

  • Medical assistants: $38K-$48K
  • RNs: $93,600 median (BLS May 2024)
  • Nurse practitioners: $129,210 median, 46% growth projected
  • Physical therapists: $75K-$95K
  • Clear advancement path to higher-paying specializations

Future Viability (14/15):

  • Aging demographics (structural demand)
  • Cannot be automated (physical presence, human judgment required)
  • Chronic conditions increasing (60% adults have at least one)
  • Home care expanding 30% (2019-2029 projection)
  • Protected by licensing/HIPAA regulations

Scam/Risk (2/5): -3 points

  • Legitimate career with established credentialing
  • Some predatory for-profit programs exist
  • Verify school accreditation carefully

Why It Holds #1: ServiceNow + OpenAI automates IT support and operations roles this week. Healthcare patient care requires physical presence, human touch, clinical judgment. As automation eliminates administrative coordination, direct patient care becomes increasingly valuable.

#2. Skilled Trades with Clean Energy Specializations (Electricians, HVAC, Solar)

Score: 85/100 ⬆️ (Holding #2)

Market Demand (27/30):

  • Electricians: 9% growth (2024-2034), 81,000 openings/year (BLS)
  • HVAC: 6-8% growth, 40,100 openings/year
  • Solar installers: Fastest growing occupation, 48% growth
  • Data center construction driving demand (Wisconsin: 15 facilities)
  • EV charging infrastructure expansion
  • Shortfall: 10,000 electricians retire annually, only 7,000 enter

Entry Speed (22/25):

  • Apprenticeships: Paid while learning (4 years typical)
  • Starting wages: $35K-$45K while training
  • Journey-level: 4 years to full certification
  • Solar certifications: Months to add to existing electrical skills
  • No student debt (earn while learning)

Income Potential (21/25):

  • Entry apprentice: $35K-$45K
  • Journey electrician: $61,590 median (BLS), top 10% over $104K
  • Solar specialists: Premium pay for specialized skills
  • Master electrician: $82,500+
  • Business ownership potential: $100K+

Future Viability (15/15):

  • Physical work, can’t be done remotely
  • Problem-solving in varied environments
  • Clean energy expansion legislated (policy support)
  • Data centers, EV infrastructure, smart buildings all need electricians
  • Technology changes tools but doesn’t eliminate need
  • CHIPS Act manufacturing creating multi-year demand

Scam/Risk (0/5): No deduction

  • Legitimate union/non-union apprenticeships
  • Industry-funded training (not predatory schools)
  • Clear credentialing path

Why It Holds #2: Microsoft’s 15 Wisconsin data centers create construction demand. Clean energy mandates drive electrician needs. Physical work resists automation. This week’s infrastructure news confirms sustained demand.

#3. Healthcare Data/Care Coordinators (Clinical + Tech Skills)

Score: 78/100 ⬆️ (Up from #4)

Market Demand (24/30):

  • Monster: “Data-driven care coordinators” fastest-growing healthcare role
  • Patient care coordinators: 29% growth through 2033 (BLS via Nurse.org)
  • 52,000+ active positions nationwide (Indeed)
  • Bridges clinical knowledge with technology
  • Health systems deploying AI but need human oversight

Entry Speed (20/25):

  • Healthcare background + data training: 6-12 months
  • Care coordination certifications available
  • Health informatics programs: 1-2 years
  • Can transition from medical assistant or patient service rep
  • Faster than full clinical degree

Income Potential (18/25):

  • Range: $55K-$85K depending on setting and experience
  • Lower than clinical roles but higher than pure admin
  • Growth potential with specialization
  • Not top-tier earnings but solid middle class

Future Viability (14/15):

  • AI assists but doesn’t replace (human judgment needed)
  • ChatGPT/Claude for Healthcare create MORE coordination need
  • HIPAA protections limit full automation
  • Combines domain expertise (healthcare) + tech literacy
  • Not pure admin (automating) or pure clinical (expensive to train)

Scam/Risk (2/5): -3 points

  • Some predatory certificate programs
  • Verify accreditation and job placement rates
  • Legitimate path exists through established programs

Why It Moves Up: ChatGPT for Health and Claude for Healthcare launched this week (January 2 and 11, 2026). These tools create MORE need for coordinators who understand both clinical context AND technology. Pure administrative roles (medical secretaries, billing) face automation, but clinical + data combination remains valuable.

#4. AI/Cybersecurity Specialists (Data Governance, Security Architecture)

Score: 76/100 ⬇️ (Down from #3)

Market Demand (22/30):

  • Tech unemployment under 3% for core security roles
  • Information security analysts: Fast-growing occupation (BLS)
  • Federal AI partnerships (90,000+ workers) show government demand
  • Enterprise AI deployment requires security/governance
  • BUT: ServiceNow + OpenAI targets IT support (negative signal)

Entry Speed (18/25):

  • Cybersecurity certifications: 6-12 months (CompTIA Security+, CISSP)
  • Career changers from IT: Faster path
  • Data governance: Requires understanding compliance frameworks
  • Not as fast as trades apprenticeships
  • Requires technical foundation first

Income Potential (23/25):

  • Entry security analysts: $65K-$85K
  • AI governance specialists: $95K-$135K
  • Security architects: $120K-$160K
  • Top tier for knowledge work
  • Remote work possible (geographic arbitrage)

Future Viability (11/15):

  • AI augments but doesn’t replace (for now)
  • Requires staying current with threats
  • ServiceNow + OpenAI shows IT support automating
  • Security/governance more specialized than general IT support
  • Medium-term viability, must watch automation trends

Scam/Risk (2/5): -3 points

  • Bootcamp quality varies wildly
  • Expensive certifications sometimes don’t lead to jobs
  • Legitimate path exists but must vet programs carefully

Why It Drops: ServiceNow + OpenAI partnership shows automation coming for IT operations roles. Security/governance specialists have more protection than general IT support, but the trend is concerning. Still viable but requires closer monitoring.

#5. Construction Technologists (BIM, Digital Project Management)

Score: 73/100 ⬆️ (Holding #5)

Market Demand (21/30):

  • CHIPS Act: Multi-year construction demand
  • Microsoft Wisconsin: 15 data centers = sustained construction
  • BLS: Construction employment driven by AI data centers, EVs, renewables
  • Need people who understand construction AND technology
  • Smaller labor pool than general construction

Entry Speed (17/25):

  • Construction background + tech training: 6-12 months
  • BIM certification: 3-6 months for skilled workers
  • Project management + construction tech: 1-2 years
  • Requires existing construction knowledge first
  • Not as fast as direct trade apprenticeships

Income Potential (20/25):

  • BIM specialists: $60K-$85K
  • Construction technologists: $75K-$105K
  • Tech-focused project managers: $85K-$125K
  • Premium over traditional construction but not top-tier
  • Business ownership/consulting potential

Future Viability (13/15):

  • Technology changes how construction happens
  • Doesn’t eliminate need for oversight
  • Drones, digital twins, automation require human management
  • Physical infrastructure needs can’t be fully automated
  • CHIPS Act creates multi-year runway

Scam/Risk (2/5): -3 points

  • Some BIM/project management courses overpromise
  • Verify employer recognition of certifications
  • Legitimate paths exist through construction companies

Why It Holds #5: Microsoft Wisconsin expansion confirms infrastructure jobs are real (though fewer than promised). Need for tech-savvy construction oversight remains. Just makes 70/100 threshold.

NOT MAKING TOP 5 THIS WEEK:

IT Support Specialist – Previously borderline, now fails 70/100 threshold

  • ServiceNow + OpenAI directly automates this role
  • Market demand drops significantly
  • Score: 62/100 (below threshold)

Retail Sales – Never in Top 5, getting worse

  • Google Universal Commerce targets these jobs
  • 2-3 year displacement timeline confirmed
  • Score: 45/100 (well below threshold)

Key Pattern This Week: Positions requiring physical presence + human judgment (healthcare, trades) hold strong. Positions coordinating between systems and people (IT support, retail) face direct automation from this week’s announcements.

VI. CAREER INTELLIGENCE SKILLS: THREAT ASSESSMENT

The Uncomfortable Truth: The hardest career skill isn’t Python, cloud computing, or project management. It’s honest self-assessment followed by uncomfortable action.

Your company won’t warn you before the layoff announcement. The automation won’t wait until you’re ready. And “I’ve been doing this for 10 years” won’t protect you if AI can do it faster and cheaper.

This week proved it: ServiceNow + OpenAI = complete automation stack for IT support, HR coordination, business operations. Google Universal Commerce = AI layer between customers and merchants. OpenAI announcing plans to take cuts of customer innovations = extraction formalized.

Your timeline matters more than your experience.

THE FIVE TRAPS THAT KEEP PEOPLE FROM SEEING DANGER

1. Normalcy Bias

  • “It’s always been fine before”
  • “They need people with my experience”
  • “Customers prefer talking to humans”

Reality: Salesforce eliminated 4,000 customer service jobs in September 2025. CEO Marc Benioff didn’t apologize – he promoted it. “AI will handle customer support, humans still needed but fewer of them.”

2. Specialization Trap

  • “I’ve invested 10 years in this role”
  • “I’m an expert in our company’s systems”
  • “My skills are too specialized to switch”

Reality: Platform-specific skills become worthless when platforms automate. MIT research: Companies lose $24.8B staying trapped in expensive platforms because switching costs are too high. Workers face identical trap with specialized skills.

3. Complexity Shield

  • “My job is too complex to automate”
  • “AI can’t handle the nuance I deal with”
  • “They’d need someone to oversee the AI anyway”

Reality: 60% of your tasks might be complex. AI handles the other 40%, company eliminates your position, expects remaining workers to handle the complex parts plus their original workload. You just became cheaper to replace.

4. Income Dependency

  • “I can’t afford to retrain”
  • “I need this income right now”
  • “I’ll wait until I have more savings”

Reality: You also can’t afford to be laid off with no plan, no skills, and no timeline. ServiceNow + OpenAI deployment: 12-18 months to critical mass. If you wait until the layoff announcement, you’re competing with everyone else from your company for fewer positions.

5. Sunk Cost Fallacy

  • “I have so much experience here”
  • “I’m about to vest my retirement”
  • “Just one more year and I’ll have my certification”

Reality: Past investment doesn’t protect future employment. The automation doesn’t care about your tenure. The question isn’t “How much have I invested?” It’s “What’s my displacement timeline versus my transition timeline?”

YOUR THREAT ASSESSMENT CHECKLIST

🚨 IMMEDIATE DANGER (Move Within 6 Months)

Check all that apply:

  • [ ] Your company deployed AI in your department this year
  • [ ] Recent layoffs in your role cited “efficiency” or “AI”
  • [ ] 60%+ of your tasks could be done by ChatGPT/Claude/Copilot
  • [ ] ServiceNow + AI announced in your company’s workflow systems
  • [ ] You work in: retail sales, call center, basic IT support, data entry, customer service
  • [ ] Your company has “transformation” or “efficiency initiative” underway
  • [ ] No emergency fund, cannot afford job loss
  • [ ] Hiring freeze at your company while workload increases

3+ boxes checked = Start exit plan immediately. You have 6 months maximum.

⚠️ NEAR-TERM RISK (Plan Exit Within 12 Months)

Check all that apply:

  • [ ] AI being deployed in adjacent departments/roles at your company
  • [ ] Your industry conferences discussing automation extensively
  • [ ] Tasks becoming more tedious as “interesting parts” get automated (silent firing)
  • [ ] Your skills are platform-specific, not portable to other companies
  • [ ] You work in: healthcare admin, entry-level analysis, business operations coordination, HR support
  • [ ] Your company announced partnerships with OpenAI, Anthropic, Google (AI platforms)
  • [ ] Job postings in your field declining month-over-month
  • [ ] Training on “AI tools” that do significant portions of your job

3+ boxes checked = Begin serious planning. You have 12-18 months.

📊 MEDIUM-TERM RISK (Monitor & Prepare)

Check all that apply:

  • [ ] Your sector has automation pilots but not full deployment
  • [ ] Some tasks automated but core work remains human-required
  • [ ] You have transferable skills but need to document them
  • [ ] Financial cushion exists, career change requires planning
  • [ ] You work in specialized roles requiring judgment + domain expertise
  • [ ] Industry growing but your specific sub-role facing automation
  • [ ] You can list your skills without naming employer’s proprietary tools

3+ boxes checked = You have time, but don’t waste it. Start skill assessment.

THE QUESTIONS THAT ACTUALLY MATTER

Question 1: Can I list my skills without naming my employer’s tools?

Test: Write your resume replacing all company-specific systems with generic descriptions.

  • ❌ “Expert in XYZ Company’s proprietary CRM system”
  • ✅ “Customer relationship analysis and workflow optimization”

If your entire value proposition depends on Company X’s specific tools, you’re platform-locked. When those tools automate or the company eliminates your position, your skills don’t transfer.

Question 2: Would I hire someone to do my job if AI could do 60% of it?

Test: List your daily tasks. Mark which ones AI tools can handle right now (not theoretically – right now with ChatGPT/Claude/Copilot).

If 60%+ are AI-capable, the economics change dramatically:

  • Company pays you $70K to do 10 tasks
  • AI does 6 tasks for $500/month in API costs
  • Company eliminates your role, expects remaining workers to handle the 4 complex tasks

You’re not being compared to other humans. You’re being compared to AI + fewer humans.

Question 3: Do I have 12 months of expenses saved?

Reality check:

  • Average job search 2025: 5-8 months
  • Career transition training: 3-12 months
  • Income gap: 8-15 months potentially

Without savings, you can’t afford strategic transitions. You take whatever comes first, which is usually not the best long-term position.

Question 4: What would I do if I got laid off tomorrow?

If you don’t have an answer, you’re not prepared.

The answer should be specific:

  • ✅ “I’d immediately apply to healthcare coordinator roles because I have the training and there are 52,000 open positions”
  • ❌ “I’d figure something out” or “I’d update my resume”

THE SWITCHING COSTS CALCULATION

What’s REALLY keeping you in your current position?

Financial switching costs:

  • Salary drop in new field: $______
  • Training/certification costs: $______
  • Income gap during transition: $______
  • Total financial cost: $______

Time switching costs:

  • Training duration: _____ months
  • Job search duration: _____ months
  • Time to match current salary: _____ months
  • Total time cost: _____ months

Now calculate displacement cost:

  • Unemployment benefits: $______ for _____ weeks
  • Job search in automated market: _____ months
  • Salary of desperate job acceptance: $______
  • Total displacement cost: $______

The Real Question: Is the cost of transitioning NOW higher or lower than the cost of being displaced LATER?

MAKING THE CALL: THE DECISION FRAMEWORK

STAY AND ADAPT IF:

  • ✅ Your company invests in retraining for new roles
  • ✅ Automation creates adjacent opportunities you’re qualified for
  • ✅ Your specific sub-role is protected (licensing, regulation, physical presence)
  • ✅ You’re close to significant vesting/milestone worth the risk
  • ✅ You have concrete exit plan if adaptation fails

START EXIT PLANNING IF:

  • ⚠️ Your role is in immediate danger categories (IT support, retail, call center)
  • ⚠️ Company has “transformation” programs with no retraining offered
  • ⚠️ Tasks becoming tedious while interesting work automated (silent firing)
  • ⚠️ You checked 3+ boxes in immediate or near-term danger
  • ⚠️ No savings + high displacement risk = can’t afford to wait

EXECUTE EXIT IMMEDIATELY IF:

  • 🚨 AI deployment announced in your department
  • 🚨 Layoffs in similar roles citing automation
  • 🚨 Hiring freeze + increased workload = company testing lean operation
  • 🚨 You’re in retail sales with Google Universal Commerce deployment
  • 🚨 You’re in IT support with ServiceNow + OpenAI partnership

THE COURAGE TO ACT

Why people don’t move even when they see danger:

  1. “I’ll look foolish if I’m wrong” – You’ll look smart for being prepared
  2. “Maybe it won’t be that bad” – Salesforce: 4,000 jobs. Accenture: 11,000+. UPS: 48,000
  3. “I don’t know what else to do” – That’s why Top 5 exists. Healthcare, trades, specialized roles
  4. “I’m too old to start over” – Medical assistant: months. Electrician apprentice: earn while learning
  5. “What if I make it worse?” – Compare to being laid off with no plan

The Bottom Line:

Every week you wait without a plan is a week of preparation you’ve lost. ServiceNow + OpenAI deployments happen over 12-18 months. Google Universal Commerce already has 20 major partners. OpenAI revenue hit $2.7B proving enterprise adoption is real.

Your company is making automation decisions right now in procurement meetings you’re not invited to.

The meta-skill: Seeing danger signals clearly + having the courage to act before the announcement.

Next Week (Week 8): Switching Cost Analysis – What are YOUR specific switching costs? How to calculate whether to move now or later. How to reduce switching costs while still employed.

VII. ACTION ITEMS

This Week:

  • Complete your Threat Assessment checklist (Career Intelligence Skills section)
  • If you checked 3+ boxes in immediate danger: Start exit planning today
  • If you work IT support, retail, customer service: Assess your timeline seriously

This Month:

  • Calculate your switching costs vs displacement costs
  • Identify which Top 5 category matches your capability
  • Build 3-6 month emergency fund if possible
  • Document your transferable skills (not platform-specific ones)

Next Two Weeks:

  • Tuesday, January 28: “Conversations with Claude” – What happens to communities when entry-level work disappears? Full systemic analysis of the economic ladder problem
  • Friday, January 30: Under the Radar with Career Intelligence Skills Week 8: Switching Cost Analysis

VIII. RESOURCES & COMMUNITY

🎯 Complete Resource Library

PivotIntel Resources Hub: theopenrecord.org/resources/

Career Intelligence Tools:

  • Occupation Risk Tracker: pivotintel.org/app/occupation-risk
  • Top 5 Ranking Methodology: theopenrecord.org/Special%20Edition/top-5-ranking.html

This Week’s Reading:

All Previous Editions: Under the Radar Archive

IX. WHAT TO WATCH NEXT WEEK

Employment Data:

  • Next BLS Employment Situation: February 6, 2026
  • January initial jobless claims (weekly Thursday releases)
  • ADP private sector employment (weekly pulse reports)

Enterprise Deployment:

  • ServiceNow + OpenAI customer announcements
  • Google Universal Commerce merchant adoption
  • Healthcare AI platform integrations (ChatGPT Health, Claude Healthcare)

Policy Developments:

  • Warner-Hawley bill progress (AI job impact reporting)
  • State-level automation regulations (if any)
  • Social program changes affecting displaced workers

Infrastructure:

  • Microsoft Wisconsin data center development
  • Community responses to data center proposals
  • Federal grid connection acceleration implementation

X. BOTTOM LINE

This week proved platform consolidation is complete. ServiceNow + OpenAI automates enterprise operations. Google captures the commerce layer between every customer and merchant. OpenAI announces plans to extract value from customer innovations. Anthropic hits $2.7B revenue proving enterprise adoption speed.

For workers who can transition: Use career intelligence strategically. Healthcare direct patient care, skilled trades with clean energy specializations, and specialized roles combining domain expertise with technology offer viable paths. Top 5 positions scored honestly by our criteria show where demand exists.

For workers who can’t: Individual career advice isn’t enough. The single parent in retail with no savings, the 50-year-old call center worker with health issues, the person making $15/hour who can’t afford income loss during training – they need systemic solutions we can’t provide through career guidance. This requires regulation on automation speed, mandatory retraining funded by companies, profit-sharing from productivity gains, and expanded safety nets.

We’ll continue providing intelligence for those who can use it. But we won’t pretend individual solutions solve structural problems. The bottom rungs of the economic ladder are disappearing – entry-level manual AND office work both being automated. Small businesses can’t absorb millions of displaced workers. Policy responses remain inadequate.

The timeline is 12-18 months for enterprise deployment reaching critical mass. The economic ladder has lost its bottom rungs. And pretending otherwise doesn’t help anyone.

Next week: Career Intelligence Skills Week 8 focuses on calculating YOUR specific switching costs versus displacement costs. Plus Tuesday’s “Conversations with Claude” explores what happens to communities when entry-level work disappears – the full systemic analysis this newsletter format can’t accommodate.

Next Edition: Friday, January 30, 2026 at 5:00 PM ET

Subscribe: theopenrecordl3c.substack.com

XI. METHODOLOGY & SOURCES

Research Approach:

This analysis combines documented employment data, real-time enterprise announcements, and career market intelligence to track opportunities and risks created by AI deployment. We prioritize verifiable evidence over speculation and document our sources transparently.

This Week’s Major Announcements

ServiceNow + OpenAI Partnership:

  • Announced January 2026 for enterprise workflow automation
  • Targets IT service desk, HR support, business operations coordination
  • ServiceNow + OpenAI announcement (January 2026)

OpenAI Revenue Model:

Google Universal Commerce Protocol:

Anthropic Revenue:

Microsoft Wisconsin Expansion:

Infrastructure & Policy:

  • US power grid plan to accelerate data center connections (January 20, 2026)
  • $83B in energy department loans cancelled/revised (January 22, 2026)
  • Community resistance: Columbiana, Alabama data center town hall

Employment Data

Most Recent Official Data:

  • BLS Employment Situation (December 2025, released January 9, 2026)
  • Total nonfarm payroll employment: +50,000 jobs
  • Unemployment rate: 4.4%
  • Next Employment Situation report: February 6, 2026
  • BLS Employment Situation Summary

Healthcare Occupations:

Skilled Trades:

Patient Care Coordinators:

  • Indeed: 52,000+ active positions nationwide (January 2026 search)
  • BLS via Nurse.org: 29% growth projected through 2033
  • Monster: “Data-driven care coordinators” identified as fastest-growing healthcare role

MIT Research on Switching Costs

  • Nagle, F., & Yue, D. (2025). “The Latent Role of Open Models in the AI Economy.” MIT & Georgia Institute of Technology
  • Key findings: Companies systematically underutilize open AI models despite 89.6% capability match and 6x lower costs
  • Potential savings from switching: $24.8 billion
  • Switching costs trap companies in expensive platforms even when better alternatives exist
  • Referenced in context of workers facing identical platform lock-in with specialized skills

Top 5 Scoring Methodology

Scoring Criteria:

  • Market Demand: 30% (job openings, BLS projections, industry growth)
  • Entry Speed: 25% (time to employment, training requirements, income during training)
  • Income Potential: 25% (entry salary, median wage, advancement potential)
  • Future Viability: 15% (automation resistance, structural demand, regulatory protection)
  • Scam/Risk Factor: 5% (deductions for predatory programs, unclear credentialing)

Threshold: 70/100 minimum

Full methodology: Top 5 Ranking Primer

Robotics & Automation

Agricultural automation:

  • Industry demonstrations of strawberry, apple, lettuce harvesting robots
  • Delicate produce picking (previously thought too complex) now commercially viable

Manufacturing & warehouse:

  • Pick and pack robots: Amazon, major warehouse operators
  • Computer vision quality control systems
  • Humanoid robots: Figure, Tesla, Boston Dynamics reaching human-level dexterity
  • Industry timeline: 5-10 years for scaled deployment

Construction automation:

  • Bricklaying robots: 3,000 bricks/day vs 500 for humans
  • 3D-printed structures
  • Automated framing and welding systems

Palantir CEO Statement

Limitations & Transparency

Data Gaps:

  • October 2025 BLS data not collected due to government shutdown
  • Most recent comprehensive employment data is December 2025
  • Alternative data sources (ADP, Challenger Gray & Christmas) use different methodologies

Job Posting Fluctuations:

  • Numbers fluctuate daily/weekly
  • Reported figures represent point-in-time research (January 2026)
  • Some postings may be duplicates across platforms

Scoring Subjectivity:

  • Top 5 scoring involves judgment calls on future viability
  • We document reasoning transparently
  • Threshold (70/100) is strict to avoid false hope

Systemic vs Individual Solutions:

  • This newsletter can help 20-30% of workers with runway and capability
  • 70% need policy solutions beyond individual career advice
  • We acknowledge these limits explicitly

Human + AI Collaboration

This analysis uses AI (Claude, Anthropic) for:

  • Web search execution across news sources, job platforms, BLS data
  • Data synthesis from 50+ sources this week
  • Citation tracking and verification
  • Organizing complex information into accessible formats
  • Draft structure and initial research compilation

All strategic decisions are human-made:

  • Which developments matter for workers
  • How to score Top 5 opportunities
  • Editorial framing and tone
  • What constitutes actionable intelligence vs speculation
  • Acknowledging limits of individual solutions to systemic problems

Angela Fisher makes all final editorial decisions, verifies sources, and determines what information serves workers navigating displacement.

Sources Monitored This Week:

  • Financial Juice (real-time alerts)
  • BLS Occupational Outlook Handbook
  • The Information (AI industry coverage)
  • Bloomberg (enterprise adoption data)
  • American Banker (commerce layer analysis)
  • Seeking Alpha (corporate developments)
  • Milwaukee Journal Sentinel (infrastructure projects)
  • OpenAI, Anthropic, Salesforce corporate announcements
  • Monster 2026 Job Market Outlook

Under the Radar is published weekly, tracking career opportunities and displacement patterns created by AI deployment. We provide honest assessments for workers who can use career intelligence while acknowledging systemic problems require policy solutions beyond individual guidance.

Next week: Career Intelligence Skills Week 8: Switching Cost Analysis – calculating YOUR specific costs of transitioning now versus being displaced later.

Plus Tuesday’s “Conversations with Claude”: What happens to communities when entry-level work disappears? Full systemic exploration of the economic ladder problem and why small business capacity-building, while necessary, isn’t sufficient at scale.

Under the Radar is published weekly by The Open Record L3C. For career intelligence tips: contact@theopenrecord.org

Angela Fisher is founder of The Open Record L3C, publisher of PivotIntel Weekly and Under the Radar. She tracks AI deployment patterns and economic transformation from Michigan.

Published: Friday, January 23, 2026, 5:00 PM ET

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