Is Your Job at Risk from AI? How to Assess It
If you have asked yourself "is my job at risk from AI?" in the last six months, you are not alone. A recent Mercer survey of 12,000 professionals found that job loss concerns jumped from 28% in 2024 to a staggering 40% in 2026. That is not paranoia. That is pattern recognition. And the pattern is unmistakable: companies across every industry are making aggressive moves to replace human labor with artificial intelligence, and the pace is accelerating faster than almost anyone predicted.
I have spent the last several years advising professionals and organizations across the Rome, New York, and Miami markets through my work with Emotivae and Kealu. What I see every day is a widening gap between the speed at which AI is transforming work and the speed at which most people are adapting to it. This article is my attempt to close that gap for you, personally.
What follows is not a think piece filled with vague reassurances. It is a data-driven, practical framework you can use today to honestly assess whether your job is at risk, understand exactly why, and build a concrete plan to protect your career. Whether you are a mid-level marketing manager, a senior software engineer, or a paralegal fresh out of school, the five-dimension risk assessment I am about to share will give you clarity where the headlines only give you anxiety.
Let us get into the numbers first. Then we will build your plan.
---
The Hard Data: Why "Is My Job at Risk from AI?" Is the Right Question to Ask
There is a moment in every economic shift when the question changes from "will this affect me?" to "how badly will this affect me?" For millions of workers around the world, that moment arrived in 2025 and has only intensified through the first months of 2026.
Let us start with the headline numbers. In 2025, roughly 55,000 job cuts were directly attributed to AI out of a total 1.17 million layoffs globally, the highest total since 2020. In the first two months of 2026 alone, the tech sector shed over 32,000 positions. These are not abstract statistics. They represent real people, many of them highly skilled, clearing out their desks.
Goldman Sachs estimates that AI could eventually displace 6 to 7% of the entire US workforce. That may sound modest in percentage terms, but in absolute numbers, it translates to roughly 10 million jobs. And that estimate is considered conservative by many labor economists.
The IMF's Managing Director, Kristalina Georgieva, did not mince words either: she described AI as "hitting the labor market like a tsunami." When the head of the International Monetary Fund uses the word tsunami, it is worth paying close attention.
Meanwhile, a landmark study from the National Bureau of Economic Research (NBER) revealed a paradox that should concern everyone: 90% of C-suite executives said AI had no employment impact over the past three years. That disconnect between executive perception and on-the-ground reality is dangerous. It means the people making decisions about your job may fundamentally misunderstand how quickly the ground is shifting beneath them. Or worse, they understand perfectly and are simply waiting for the right moment to act.
The future of work artificial intelligence is not a chapter we are approaching. We are already deep into it. The question of whether your job is safe is not hypothetical. It is urgent. And the honest answer for most people is: probably more than you think, but less than the doomsayers claim, provided you take action now.
Harvard Business Review published a critical finding that underscores this nuance: companies are increasingly laying off workers for AI's potential, not for its current performance. In other words, organizations are making bets on what AI will be able to do in 12 to 18 months, and they are restructuring their workforces today based on those bets. That means the timeline for how to prepare for AI automation is shorter than most people assume.
Only 16% of workers had high AI readiness, measured by a composite score called AIQ, in 2025. That number is projected to rise to just 25% in 2026. Which means three out of four workers are entering the most transformative period in modern labor history without adequate preparation.
These are the facts. They are uncomfortable. But they are also actionable, and that is where we are headed next.
Block Layoffs AI: Jack Dorsey's Playbook and What It Signals for Every Industry
If you want to understand the corporate calculus behind AI job displacement 2026, look no further than Jack Dorsey's Block Inc. In one of the most telling moves of the past year, Dorsey laid off 40% of Block's workforce, and the stock surged 17% in the aftermath. Read that again. A company fires nearly half its people, and investors reward it.
This is not an anomaly. It is a signal. Wall Street is telling every CEO in every boardroom that replacing humans with AI is not just acceptable, it is desirable. The Block layoffs AI story crystallizes a new equation: fewer employees plus more AI equals higher shareholder value. Whether that equation is morally defensible is a separate conversation. Whether it is driving real decisions right now is not up for debate.
Block was not alone. Oracle executed what many analysts called the largest layoffs in its history, redirecting the savings to fund AI data centers. Amazon quietly cut 14,000 corporate roles, streamlining operations with AI-driven processes. Workday eliminated 1,750 positions, representing 8.5% of its entire workforce, explicitly citing the need to invest in AI capabilities.
Here is what makes these layoffs different from the usual corporate restructuring cycles: they are not primarily driven by poor company performance or economic downturns. They are driven by strategic repositioning around AI. As HBR noted, companies are laying people off for AI's potential, not because their current human workforce is underperforming.
Sam Altman, the CEO of OpenAI, himself warned about "AI washing" in layoffs, a practice where companies use AI as a convenient justification for cuts that are really about cost reduction or organizational politics. This is an important nuance. Not every layoff attributed to AI is genuinely about AI. But the trend is real, the direction is clear, and the distinction matters less to the person receiving a severance package.
What does the Block story mean for you specifically? It means that the market has signaled its preferences. Companies that aggressively adopt AI and reduce headcount are being rewarded. Companies that move slowly are being punished. That creates enormous pressure on every CEO and every board to accelerate AI replacing jobs across their organizations.
Interestingly, there is a counterweight to this narrative. Forrester Research found that 55% of employers who conducted AI-driven layoffs now regret them. The reasons vary: loss of institutional knowledge, drops in team morale, inability to manage the very AI systems that were supposed to replace the laid-off workers, and customer experience degradation. This regret is real, but it has not yet slowed the pace of new layoffs. The market incentive is too strong.
The lesson from Block's aggressive restructuring is not to panic. It is to act with the same strategic clarity that Dorsey applied to his company, but applied to your own career. You need to understand your exposure, build your defenses, and position yourself on the right side of this shift.
AI Job Displacement 2026: The Numbers Nobody Can Ignore
Let us get specific about the scale of AI job displacement 2026, because vague anxiety helps no one.
According to multiple converging data sources, 37% of business leaders plan to replace workers with AI by the end of 2026. That is not a far-future prediction. That is a decision many of them have already budgeted for. The plans are in spreadsheets. The timelines are on Gantt charts. The vendor contracts are signed.
At the same time, only 23% of organizations offered prompt engineering training in 2025. Think about that asymmetry: a third of companies plan to replace workers with AI, but less than a quarter even bothered to train their existing employees on how to use AI tools. The message could not be clearer. For many organizations, the strategy is replacement, not retraining.
The future of work artificial intelligence is being shaped by this exact imbalance. Organizations are investing billions in AI infrastructure while investing pennies in human adaptation. That creates a two-speed economy: one track for people who proactively develop automation-resistant capabilities, and another track for people who assume their current expertise will remain valuable without evolution.
FlexJobs reported that 43% of workers are actively trying to change career fields, the highest percentage ever recorded. This is not a coincidence. Millions of people can feel the ground shifting, even if they cannot articulate exactly what is happening. The instinct to move is correct. The challenge is knowing where to move and how.
The wave of AI-driven workforce displacement is hitting unevenly. Some sectors are being transformed almost overnight. Others are experiencing a slower, more gradual pressure. Understanding where your specific role falls on this spectrum is the purpose of the framework I am about to share.
But before we get there, I want to address something important. The data shows real disruption, real job losses, and real anxiety. But it also shows real opportunity. Every wave of technological transformation in history has created more jobs than it destroyed in the long run. The problem has never been the total number of jobs. The problem has always been the transition, the painful period when old roles disappear faster than new ones emerge, and when the people losing the old roles are not the same people gaining the new ones.
That transition is where we are right now. And your preparation strategy during this specific window will determine your professional trajectory for the next decade.
Is My Job at Risk from AI? The 5-Dimension Risk Assessment Framework
After months of research and working directly with professionals navigating this transition through Emotivae and Kealu, I developed a practical framework to answer the question "is my job at risk from AI?" with specificity rather than speculation.
This framework evaluates your role across five dimensions, each scored from 1 (lowest risk) to 10 (highest risk). Your total score ranges from 5 to 50 and places you in a clear risk category with corresponding action steps.
Grab a pen. Be honest with yourself. Let us go.
Dimension 1: Task Predictability
The core question: How predictable and repetitive are your daily tasks?
Score yourself from 1 to 10, where 1 means your work is deeply unpredictable and every day looks fundamentally different, and 10 means your work follows clear, repeatable patterns that could be documented in a detailed process manual.
High predictability equals high risk. AI systems excel at pattern recognition and process execution. If your job involves following established procedures, processing standardized inputs, or generating outputs that follow templates, you are squarely in AI's targeting zone.
Examples of high-predictability roles include data entry specialists, basic bookkeeping, standardized report generation, first-tier customer support with scripted responses, and routine quality assurance testing. These roles score 8 to 10 on this dimension.
Examples of low-predictability roles include crisis management, investigative journalism, emergency medicine, and experimental research. These score 1 to 3.
Most knowledge workers fall somewhere in the middle, which is precisely why this assessment requires all five dimensions rather than a single metric.
Dimension 2: Human Judgment Intensity
The core question: How much nuanced human judgment does your role require?
Score yourself from 1 to 10, where 1 means your role demands constant, complex human judgment that considers ethical nuances, emotional context, cultural sensitivity, and ambiguous trade-offs, and 10 means decisions in your role can be made by applying clear rules to available data.
Low judgment intensity equals high risk. AI can apply rules and optimize for defined objectives with superhuman speed. What it cannot do, at least not yet, is navigate the kind of messy, context-dependent judgment calls that define truly complex work.
If your role requires you to regularly make decisions where reasonable people would disagree, where the "right" answer depends on values and context rather than data alone, you have significant protection. If your decisions can be reduced to decision trees or scoring matrices, your protection is thin.
Dimension 3: Physical Presence Requirement
The core question: Does your job require you to be physically present in a specific location?
Score yourself from 1 to 10, where 1 means your work absolutely requires physical presence, manual dexterity, or in-person interaction, and 10 means your work can be done entirely from a laptop anywhere in the world.
This dimension contains a counterintuitive truth: jobs that can be done remotely are actually at higher risk from AI, because anything that can be done from a laptop is, by definition, digital work. And digital work is exactly the kind of work AI is learning to do. Trades, healthcare professionals who touch patients, construction workers, and chefs all have a form of protection that knowledge workers do not.
This does not mean remote work is bad. It means that if your job is fully remote, you need to score especially well on the other four dimensions to maintain a secure position.
Dimension 4: Creative Originality
The core question: Does your work require genuine creative originality, or does it involve applying templates and established patterns?
Score yourself from 1 to 10, where 1 means your work demands radical creative originality that produces things the world has never seen, and 10 means your work follows templates, formulas, or established creative patterns.
Template-based work equals high risk. AI is remarkably good at producing content, designs, code, and analysis that follows established patterns. It can write a decent blog post, generate a workable logo, produce functional code, and create a standard financial model. What it struggles with is genuine creative vision, the kind that breaks conventions, synthesizes unexpected influences, and produces work that surprises even its creator.
Be honest here. Most work that feels creative is actually combinatorial: it remixes existing ideas in familiar ways. That kind of creativity is highly automatable. True creative originality, the kind that defines artistic vision, breakthrough product design, or paradigm-shifting strategy, remains deeply human.
Dimension 5: Relationship Capital
The core question: How central are deep, trust-based human relationships to your role's value?
Score yourself from 1 to 10, where 1 means your role derives most of its value from long-term, trust-based relationships that took years to build, and 10 means your role could be performed by anyone with the right technical skills, regardless of personal relationships.
No relationships equals high risk. If your job is transactional, if the value you provide is purely functional and could be delivered by a stranger or a system without any loss of quality, AI is a direct substitute. But if your clients trust you specifically, if your colleagues depend on your particular way of navigating organizational politics, if your vendor relationships are built on decades of personal history, that relationship capital is a moat that AI cannot cross.
This is why roles like executive coaching, high-end sales, political advising, and community organizing are remarkably resilient to AI disruption. The value is in the relationship, not the information.
Scoring Your Risk Level
Add up your scores across all five dimensions. Here is what your total means:
5-15: Low Risk (The Resilient Zone) Your role combines unpredictability, deep judgment, physical presence, creative originality, and strong relationship capital. AI is a tool that will enhance your work, not replace it. Your action plan: become the person in your organization who leads AI integration for your function. Learn to use AI tools aggressively to amplify your already-protected capabilities.
16-25: Moderate Risk (The Adaptation Zone) You have genuine strengths that protect you, but also real vulnerabilities. Parts of your role will be automated. Your action plan: identify the 20-30% of your work that AI can do and proactively offer to lead that automation. Simultaneously deepen the human-intensive parts of your role. Invest heavily in developing durable human capabilities over the next 12 months.
26-35: High Risk (The Transformation Zone) A significant portion of your current role is automatable within 12 to 24 months. Your action plan: begin a serious career change AI strategy immediately. This does not mean quitting your job tomorrow. It means starting to build skills, credentials, and relationships in adjacent areas that score lower on this framework. Invest 5 to 10 hours per week in this transition starting now.
36-50: Critical Risk (The Reinvention Zone) Your current role is highly likely to be substantially eliminated or transformed beyond recognition within 12 to 18 months. Your action plan: treat career reinvention as your primary project. Every week should include concrete steps toward a fundamentally different professional identity. Seek mentorship, formal training, and community support. This is not a drill.
For a deeper dive into this topic, check out our agentic AI and how it works.
Top 10 Roles Most at Risk from AI Replacing Jobs
Based on the five-dimension framework and current displacement data from early 2026, these are the ten roles facing the most immediate threat from AI replacing jobs:
1. Data Entry Clerks (Framework Score: 45-50) — Fully automatable with current AI capabilities. If you are in this role, the timeline is not years. It is months.
2. Basic Bookkeeping and Accounting Clerks (Framework Score: 40-47) — AI-driven accounting software is already handling transaction categorization, reconciliation, and basic reporting with higher accuracy than humans.
3. Customer Service Representatives (Tier 1) (Framework Score: 38-45) — Scripted responses, FAQ handling, and basic troubleshooting are exactly what large language models are built for.
4. Paralegal and Legal Research Assistants (Framework Score: 36-43) — Document review, case law research, and contract analysis are being automated at breathtaking speed.
5. Junior Copywriters and Content Writers (Framework Score: 35-42) — Template-based blog posts, product descriptions, email copy, and social media content are AI's sweet spot.
6. Basic Financial Analysts (Framework Score: 34-41) — Standardized financial modeling, report generation, and data visualization are increasingly automated.
7. Medical Transcriptionists (Framework Score: 38-44) — Speech-to-text AI has already surpassed human accuracy in many medical transcription tasks.
8. Quality Assurance Testers (Manual) (Framework Score: 33-40) — Automated testing frameworks, now enhanced with AI, are replacing manual testers across the software industry.
9. Travel Agents (Generalist) (Framework Score: 32-39) — AI-powered booking platforms and personalized recommendation engines are displacing generalist travel agents who compete on information access rather than relationship depth.
10. Junior Graphic Designers (Framework Score: 30-38) — AI image generation tools are handling an increasing share of template-based design work, from social media graphics to basic marketing materials.
If you see your role on this list, do not despair. Remember, this assessment is about your current role configuration, not about you as a person. Every single one of these roles has adjacent career paths that score much lower on the risk framework. The key is to start moving now.
According to the World Economic Forum Future of Jobs Report, this trend is accelerating across industries.
Top 10 AI-Proof Skills and Roles for the Future of Work Artificial Intelligence
Now for the other side of the equation. These are the ten roles and skill sets that score lowest on the risk framework and represent the most promising directions for anyone wondering how to prepare for AI automation:
1. AI Strategy and Integration Specialists — The people who understand both the technology and the business context well enough to deploy AI effectively. Demand is exploding and supply is thin.
2. Mental Health Professionals and Executive Coaches — Deep human connection, empathy, and trust are the core product. AI cannot replicate the therapeutic relationship. Through my work with Emotivae, I see this demand increasing, not decreasing.
3. Skilled Trades (Electricians, Plumbers, HVAC) — Physical presence, manual dexterity, and unpredictable environments make these roles highly resilient. They also pay increasingly well as the college-educated workforce floods into white-collar AI competition.
4. Complex Sales and Enterprise Relationship Managers — High-value B2B sales depend on trust, negotiation, and deep relationship capital that AI cannot substitute.
5. Healthcare Providers (Nurses, Surgeons, Physical Therapists) — The combination of physical presence, complex judgment, and human empathy creates a triple moat against AI displacement.
6. Creative Directors and Artistic Visionaries — Not the people who execute templates, but the people who define creative vision. AI is a tool in their hands, not a replacement for their taste and judgment.
7. Ethics and Compliance Officers — As AI creates new ethical dilemmas, the demand for human judgment on values-based decisions is growing, not shrinking.
8. Senior Product Managers — The ability to synthesize customer empathy, technical feasibility, business viability, and organizational politics into coherent product strategy remains deeply human.
9. Specialized Educators and Trainers — Particularly those focused on AI literacy, adaptive learning, and the human skills that AI cannot teach. Through Kealu, I have seen firsthand how demand for high-quality human-delivered education is accelerating.
10. Emergency Response and Crisis Management Professionals — Unpredictable environments, split-second judgment, and the need for physical presence create strong protection.
Building durable, human-centered skills is not about avoiding technology. It is about positioning yourself at the intersection of human capability and AI leverage. The most valuable professionals in 2026 and beyond will be those who use AI as an amplifier for uniquely human strengths: judgment, empathy, creativity, and trust.
Career Change AI: How to Pivot Without Burning Everything Down
If your risk assessment places you in the Transformation or Reinvention zones, you are probably feeling a mix of urgency and overwhelm right now. That is completely normal. But before you do anything drastic, let me share a perspective that has guided much of my coaching work.
Megan Hellerer, one of the sharpest career transition thinkers I know, puts it perfectly: "Career change doesn't have to be dramatic. It often begins with small experiments." This is critical wisdom for anyone contemplating a major career pivot driven by AI anxiety.
The biggest mistake I see professionals make when they realize their role is at risk is swinging between two extremes: either they freeze and do nothing, or they make a dramatic leap into something completely unfamiliar. Both approaches have high failure rates. The path that works is incremental, strategic, and experimental.
Here is what a smart AI-driven career transition strategy looks like in practice:
Phase 1: Audit and Acknowledge (Weeks 1-4) Use the five-dimension framework to pinpoint exactly which aspects of your role are most vulnerable. Be specific. It is rarely the entire job that is at risk. It is usually specific tasks within the job. Map those tasks. Understand them. Accept the reality without catastrophizing.
Phase 2: Explore Adjacent Possibilities (Weeks 5-12) Look for roles that leverage your existing strengths but score lower on the risk framework. A junior copywriter might move toward brand strategy. A data entry specialist might move toward data quality management. A basic financial analyst might move toward client advisory. The best pivots are the ones that reuse 60 to 70% of your existing skills while adding new capabilities in the dimensions where you are most vulnerable.
Phase 3: Experiment and Build Evidence (Weeks 13-24) Take on side projects, volunteer for cross-functional work, pursue targeted certifications, and build a portfolio that demonstrates your new capabilities. Do not quit your current job. Use it as a platform for experimentation.
Phase 4: Transition with Confidence (Months 7-12) Once you have evidence that your new direction is viable, begin the formal transition. Update your positioning, network strategically, and make the move from a position of strength rather than desperation.
The FlexJobs data showing 43% of workers trying to change career fields tells us that you are far from alone in this journey. The professionals who succeed in this transition share three characteristics: they start early, they move incrementally, and they invest in skills that AI cannot replicate alongside their domain expertise.
The evolving AI-driven workplace does not belong exclusively to technologists. It belongs to anyone who combines deep human capability with the willingness to evolve. That combination is far more accessible than most people believe.
Related reading: leveraging AI in your business.
How to Prepare for AI Automation: Your Weekly Action Plan
Understanding your risk is step one. Taking consistent action is everything else. Here is a practical weekly framework to future-proof your career against automation, regardless of where you scored on the assessment.
Monday: AI Tool Practice (45 minutes) Spend 45 minutes actively using an AI tool in your workflow. Not reading about AI. Using it. Try prompting ChatGPT, Claude, or a domain-specific AI tool to do a task that currently takes you significant time. Document what works and what does not. The goal is fluency, not mastery.
Tuesday: Industry Intelligence (30 minutes) Read one substantive article about AI's impact on your specific industry. Not general AI news, which tends toward hype. Look for industry-specific analysis from trade publications, consulting firms, and academic researchers. Keep a running log of the trends you see.
Wednesday: Skill Building (60 minutes) Dedicate one hour to developing one of the AI-proof skills relevant to your target direction. This might be a communication course, a leadership workshop, a creative writing exercise, a coding tutorial, or a certification module. Consistency matters more than intensity.
Thursday: Network Investment (30 minutes) Reach out to one person in your network or your target field. Not with an ask. With value. Share an insight. Make an introduction. Offer help. Building relationship capital, the fifth dimension of the framework, is one of the most powerful long-term protections against AI displacement.
Friday: Reflection and Planning (30 minutes) Review what you learned during the week. Update your risk assessment if new information warrants it. Plan the following week's focus areas. Track your progress over time.
Weekend: Creative Exploration (Optional, 60 minutes) Work on a personal project that exercises your creative and strategic muscles in a low-stakes environment. Write, design, build, teach, or create something for its own sake. This is where unexpected career directions often reveal themselves.
This plan requires approximately four hours per week. That is less than the average person spends on social media in a single day. The return on this investment, in terms of career resilience and reduced anxiety, is enormous.
The question is my job at risk from AI deserves more than a worried thought at 2 AM. It deserves a structured, weekly response that compounds over time.
For more context, see the OECD AI Policy Observatory.
The Emotional Reality: What Leaders Are Getting Wrong About AI Job Displacement
I want to close the analytical portion of this article with something that rarely gets enough attention in the conversation about AI-driven workforce transformation: the emotional and psychological toll.
A striking statistic from recent research reveals that 62% of employees feel their leaders underestimate AI's emotional and psychological impact on the workforce. In my experience advising organizations through Emotivae, this number feels conservative. The emotional impact is massive, and it is being systematically ignored by most leadership teams.
Here is what that looks like on the ground. People are not just worried about losing their paychecks. They are experiencing identity crises. For many professionals, especially those who have invested years in developing expertise, the threat of AI is not just an economic threat. It is an existential one. "If a machine can do what I do, then what am I?" That question sits at the intersection of career and identity, and it deserves more than a corporate FAQ.
The NBER finding that 90% of C-suite executives reported AI had no employment impact over three years is not just analytically wrong. It is emotionally tone-deaf. Telling workers that AI is not affecting employment, while simultaneously restructuring teams, freezing hiring, and investing billions in automation, creates a trust crisis that compounds the anxiety.
The Forrester finding that 55% of employers regret their AI layoffs is partly driven by this emotional blindness. When you lay people off without adequate emotional support, communication, or transition assistance, you do not just lose the people who leave. You lose the engagement and trust of the people who stay.
For you, as an individual navigating this landscape, the emotional dimension matters because it affects your decision-making. Fear-driven decisions are almost always bad decisions. The professionals who navigate this transition most successfully are the ones who process the emotional reality honestly, whether through coaching, therapy, peer support, or structured self-reflection, and then make clear-eyed strategic choices from a grounded emotional state.
The future of work in the age of AI will be defined not just by technology, but by our collective emotional and psychological response to that technology. Organizations and individuals who invest in both the technical and the human dimensions of this transition will outperform those who focus on only one.
This is not soft thinking. It is strategic thinking. And it is the reason why emotional intelligence, adaptability, and psychological resilience are among the most important resilience skills you can develop in the AI era.
FAQ: Is My Job at Risk from AI?
What percentage of jobs are at risk from AI in 2026?
According to Goldman Sachs, AI could displace approximately 6 to 7% of the US workforce. However, the impact is highly uneven across roles and industries. A survey of business leaders found that 37% plan to replace workers with AI by the end of 2026. The actual displacement depends heavily on your specific role, your industry, and your organization's AI adoption timeline. Using the five-dimension risk assessment framework described in this article will give you a far more accurate picture of your personal exposure than any aggregate statistic can provide.
Which jobs are most safe from AI automation?
Roles that combine physical presence requirements, deep human judgment, strong relationship capital, creative originality, and task unpredictability are most resilient. Specifically, skilled trades, healthcare providers, mental health professionals, complex sales roles, creative directors, and crisis management professionals score lowest on the risk framework. The key insight is that safety does not come from any single factor but from the combination of multiple human-centric dimensions that AI cannot easily replicate.
How can I make my career more AI-proof?
Start by assessing your current risk using the five-dimension framework. Then invest consistently in building AI-proof skills: emotional intelligence, complex judgment, creative vision, relationship building, and AI tool fluency. The weekly action plan outlined in this article provides a concrete structure. Also consider a strategic career pivot if your current role scores above 35 on the framework. As Megan Hellerer advises, career change often begins with small experiments rather than dramatic leaps.
Are companies regretting AI-driven layoffs?
Yes. Forrester Research found that 55% of employers who conducted AI-driven layoffs now regret them. The primary reasons include loss of institutional knowledge, decreased team morale, inability to effectively manage AI systems, and degraded customer experience. This regret, however, has not significantly slowed the pace of new layoffs, because the financial incentives from markets continue to reward headcount reduction. The Block layoffs AI case, where Jack Dorsey cut 40% of staff and saw a 17% stock price increase, illustrates this dynamic clearly.
How long do I have before AI affects my job?
The timeline depends entirely on your role's risk profile. Roles scoring 40 or above on the five-dimension framework may see significant impact within 6 to 12 months. Roles scoring 25 to 39 likely have 12 to 36 months before material changes occur. Roles scoring below 25 may not see direct displacement for 5 or more years, though they will still need to adapt to AI-augmented workflows. The critical point is that regardless of your timeline, the time to start preparing is now, because building new skills and repositioning your career takes months, not days. Only 16% of workers currently have high AI readiness, and waiting until disruption arrives is the highest-risk strategy of all.
You might also find our practical AI implementation helpful here.
Final Thoughts
The question "is my job at risk from AI?" is one of the most important career questions of our generation. I hope this article has moved you from anxiety to clarity, and from clarity to action.
The data is real. The disruption is accelerating. But so is the opportunity for those who prepare. Whether you scored in the Resilient Zone or the Reinvention Zone, the most important thing you can do right now is take the first step. Use the framework. Start the weekly action plan. Invest in the human capabilities that no algorithm can replicate.
Through my work with Emotivae and Kealu, I have seen hundreds of professionals navigate this transition successfully. The common thread is not exceptional talent or perfect timing. It is the willingness to look at the data honestly, process the emotional reality, and take consistent, strategic action.
The future of work artificial intelligence is not something that happens to you. It is something you can shape, one dimension at a time.
If you want to discuss your personal risk assessment or explore how to build your career change AI strategy, reach out. This is the work I do every day, across Rome, New York, and Miami, and I have never seen it matter more than it does right now.
