Top tech roles growing with AI adoption

The Next Wave of IT Jobs Will Be Defined by Enterprise AI Artificial intelligence is not just changing the tools enterprises use. It is changing the structure of IT itself. For years, organizations have tried to fit AI into existing teams and existing job descriptions. That approach will not hold for much longer. As AI becomes operational across the enterprise, companies will need new roles that focus on integration, governance, security, platform operations, and the redesign of work between humans and machines. That is the focus of my latest article. I take a close look at five emerging IT roles that are likely to become far more common over the next three years: AI Integration Engineer, LLMOps Engineer, AI Security Engineer, AI Governance and Compliance Lead, and Human-AI Workflow Architect. These are not just new titles created for hype. They reflect real responsibilities that enterprises will need to assign as AI moves from experimentation to scaled business execution. The article also explores why these roles will matter, how they map to actual enterprise needs, and what compensation will likely look like as demand outpaces available talent. If you want to understand where IT careers are heading in the AI era, this is a trend worth watching now, not later. #ArtificialIntelligence #EnterpriseAI #GenerativeAI #ITCareers #CloudComputing #DigitalTransformation #AIGovernance #Cybersecurity #MLOps #FutureOfWork

Over the past year, I have had one consistent realization while speaking with data leaders, founders, and AI teams across conferences and interviews. AI is not just changing how we work. It is quietly creating entirely new job roles inside companies. Curious to know what the community thinks about it? When I started covering AI agents on The Ravit Show (www.theravitshow.com), most conversations were about automation. Faster reports. Smarter copilots. Less manual work. But now, what I see inside real teams is very different. Companies are not asking, “Which tasks can AI replace?” They are asking, “Who will design, supervise, and run these agents?” That shift is creating new roles that did not exist a few years ago. For example, I am now seeing teams actively look for people who can design how agents think and collaborate, not just write prompts. Roles like AI Agent Architects and Prompt-to-System Engineers are emerging because businesses need structured intelligence, not experiments. Future Job Roles Created by Age…. I am also seeing operations leaders move into workflow design roles. Instead of optimizing processes manually, they are turning onboarding, reporting, and customer support into agent-driven pipelines. This is where Agent Workflow Designers are becoming critical. Another big change is happening in production environments. Once agents go live, companies need people to monitor drift, control costs, handle failures, and improve performance continuously. That is where Agent Ops and Human-in-the-Loop Supervisors come in. These roles sit at the intersection of technology, risk, and business judgment. Even analytics teams are evolving. Analysts are no longer just querying data. Many are building agents that pull data, run analysis, generate insights, and draft reports. Their role is shifting from data pullers to decision accelerators. And perhaps the most interesting shift I am seeing is in consulting and product roles. AI Automation Consultants are helping companies find where agents actually deliver ROI. Agent Product Managers are thinking in terms of which agents do what, when, and why. Systems Integrators are becoming the bridge that connects agents to CRMs, databases, and enterprise tools. This is not a future prediction. It is already happening inside modern teams. If you work in data, product, operations, or engineering, the opportunity is not just to use AI. It is to become the person who designs, manages, and scales intelligent systems. I would love to hear from you. Which of these emerging roles do you think will become standard in every company over the next 3 years? #data #ai #agentic #promptengineering #designs #systems #jobs #agents #theravitshow

𝗧𝗵𝗲 𝗥𝗶𝘀𝗲 𝗼𝗳 𝗡𝗲𝘄 𝗔𝗜 𝗥𝗼𝗹𝗲𝘀 𝗜𝘀 𝗥𝗲𝘀𝗵𝗮𝗽𝗶𝗻𝗴 𝘁𝗵𝗲 𝗪𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲 Artificial Intelligence is no longer limited to research labs or engineering teams. It is becoming a core operational layer across management, business, and technical functions — and that shift is creating an entirely new category of careers. What’s interesting is that the AI job market is no longer centered around just “AI Engineers” or “Data Scientists.” Organizations are now building complete AI-driven structures with specialized leadership, governance, operational, and domain-specific roles. The evolution is happening across three major areas 𝟭) 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 & 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 Companies are introducing leadership positions such as:  • Chief AI Officer  • Head of AI  • AI Strategy Manager  • AI Ethicist  • AI Governance Specialist  • Director of AI Transformation These roles show that AI is becoming a boardroom-level priority, not just a technical initiative. Businesses now need leaders who can manage AI adoption, governance, compliance, risk, ethics, and long-term strategy. 𝟮) 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 & 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 AI is also transforming traditional business functions:  • AI Accounting Analyst  • AI Payroll Specialist  • AI HR Business Partner  • AI Compliance Analyst  • AI Business Intelligence Analyst  • AI Customer Success Manager This is a major signal that AI integration is moving into day-to-day enterprise operations. The future workforce will likely combine domain expertise with AI fluency across finance, HR, operations, and customer management. 𝟯) 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 & 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗥𝗼𝗹𝗲𝘀 On the technical side, the ecosystem is expanding rapidly:  • Prompt Engineer  • AI Architect  • Model Validator  • AI Redteam Engineer  • AI Automation Engineer  • AI Application Developer  • AI Cybersecurity Researcher The demand is shifting from simply building models to deploying, validating, securing, orchestrating, and governing AI systems at scale. The broader takeaway is clear: AI is not replacing entire industries overnight. Instead, it is reshaping how roles are defined, how teams operate, and what skills become valuable. The professionals who will stand out over the next decade may not necessarily be those who only know AI tools, but those who understand how to combine AI capabilities with business strategy, operational workflows, and human decision-making. We are entering a phase where AI literacy could become as fundamental as digital literacy became over the last two decades. #ArtificialIntelligence #FutureOfWork #AIJobs

More than half of U.S. professionals (56%) say they plan to look for a new job in 2026, yet 76% feel unprepared for the search. Our new hiring data helps to explain why the U.S. job market still feels sluggish as this new year begins: 📌 Hiring remains subdued. While national hiring accelerated 6% month-over-month in December, it’s still down just over 2% relative to a year ago and continues to be 20% slower than in pre‑pandemic times. 📈 Competition among job seekers remains elevated. U.S. applicants per open role have doubled since the Spring of 2022. And according to new research from LinkedIn, nearly two-thirds (64%) of people in the U.S. say finding a job has become more challenging, citing competition as the main hurdle, followed by uncertainty about which roles they’re qualified for and skills gaps. 📉 Worker confidence is low. Our Workforce Confidence Index continues to remain subdued, down -4 points in comparison to last year. Unsurprisingly, active job seekers are feeling the least confident, with their confidence levels hovering around all time lows. 📊 Certain corners of the labor market show signs of recovery. We saw hiring pick up year-over-year compared to December 2024 across industries like Manufacturing (+4%), Technology, Information and Media (+3%) and Entertainment Providers (+1%). And across metros, year-over-year hiring was strongest in Miami-Fort Lauderdale (+7%), and across the Midwest in Detroit (+6%), and Minneapolis-St. Paul (+5%). We've identified some of the fastest growing jobs across our platform and highlighted them in our new Jobs on the Rise list. Here are the key insights: 📍 AI continues to reshape the landscape. For the second year in a row, AI Engineers take the top spot, with additional AI-centric roles like AI Consultants, AI/ML Researchers and Data Annotators rounding out the list. This signals strong demand across both technical and AI-adjacent roles. 🔧 Jobs supporting AI infrastructure are growing. We’re seeing an influx of roles like Datacenter Technicians, Commissioning Managers, and Construction Project Leads, as they are essential to the expanding AI ecosystem. 📈 Entrepreneurial paths are increasingly common.  Founders, Independent Consultants and Strategic Advisors rank among LinkedIn's Jobs on the Rise, signaling more professionals are creating their own opportunities. In fact, over the last year, we’ve seen a 69% increase in LinkedIn members in the U.S. adding ‘founder’ to their profile.   📣 Sales and revenue roles remain essential. From roles like Field Marketing Representatives, and Advertising Sales Specialists to Fundraising Officers, businesses are continuing to invest in and hire for roles that help increase their bottom line, even as uncertainty persists. Even in a cooling labor market, opportunity is shifting, and better understanding where momentum is building can help job seekers feel more confident about their next move. https://lnkd.in/JOTR26US

'26 is looking like a tough job market: Steady but stagnant is probably the best way to put it. There are opportunities and growth, but it's uneven, with only certain sectors and roles growing. I was on the Today Show this morning unveiling our annual Jobs on the Rise list, which is designed to help everyone understand where the market is going — in good times and bad. Here’s what job seekers should know this year: 1️⃣ The AI boom is extending beyond technical roles. Artificial Intelligence Engineers rank #1 on nearly every global list. Go deeper into JoTR and you start seeing how AI is growing roles in strategy, opps, real estate and planning: from hands-on roles like Datacenter Technicians and Prompt Engineers, to leadership titles like Directors of Artificial Intelligence and AI Strategists. We’re also seeing AI move deeper into fields like finance and hiring – a signal that AI skills are quickly becoming foundational. 2️⃣ More people are betting on themselves. For the first time, Founders and Entrepreneurs appear on our list, with “founder” titles up 69% in the U.S. over the last year (and nearly 3x since 2022). In a stagnant market, more professionals are choosing to build instead of wait. 3️⃣ Growth-driving roles stay resilient. Sales and revenue jobs show up on half of the lists, from Advertising Sales Specialists to Chief Sales Officers. When companies are under pressure, roles tied directly to growth and ROI continue to matter. The big takeaway: Opportunity hasn’t disappeared, but it’s shifting fast. The people best positioned for what’s next are staying curious, building new skills and open to change. Check out the full list here: https://lnkd.in/dt8cdskk #JobsOnTheRise

At Box, we worked with the Harris Poll to survey 1,600+ IT leaders from enterprises across the US, Japan, and Europe about the state of AI adoption in the enterprise. The findings from the survey were incredibly interesting and align with many of the things we’re hearing every day from customers. Here are the most interesting takeaways from my perspective: * The leading edge uses AI for new work, not just cheaper work: What separates leading users of AI is that 41% of them (versus 21% of early-stage firms) cite doing entirely new types of work that simply weren’t feasible before. * Context is the bottleneck most often, not models: 96% of organizations say agents need access to company-specific data and context, but only 36% have actually connected agents to trusted internal content across many use cases. The hard problem is now making institutional knowledge in the enterprise usable. * Governance slows down companies at first, then can accelerate adoption: 76% of organizations say their current governance requirements are slowing agent deployment. However, 93% agree that better governance would help them move faster over time. * AI is actually expected to grow jobs for the most advanced AI adopters, not shrinking them: Despite headlines, 58% of organizations expect headcount to rise over the next three years. Interestingly, that figure climbs to 79% among the most mature adopters of AI. And only 9% say AI agents are primarily eliminating roles today. * The jobs growing fastest barely existed two years ago: The fastest-growing roles are agent operators in IT, AI security and compliance professionals, and workflow automation specialists. 44% of organizations are actively hiring AI agent operators in IT. And at the leading edge, 0% of companies report hiring for no AI-related role at all. * Nobody wants to bet on a single AI winner: 68% of respondents are concerned about being locked into a single AI provider, and that worry basically doesn’t change varies by company size, industry, region, or maturity. * Headless tools are the future: 79% of organizations say it’s important or critical that agents operate with tools in a headless fashion, connecting directly to systems, APIs, and data without a human interface. It’s clear this is how software will primarily be used in the future. Overall, super interesting set of results now being seen in the enterprise. You can read the full report here: https://lnkd.in/gmQ6K44Y

By 2030, we’ll see 92 million jobs lost, and 𝟏𝟕𝟎 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 jobs created, according to the latest WEF report. We’re heading toward a global churn of 22% of current jobs by then. And many of the new ones? They’re being shaped and accelerated by AI. Some of the fastest-growing roles globally, directly driven by AI adoption, include: - AI and Machine Learning Specialists - Big Data Analysts - AI-augmented UX Designers - Information Security Analysts - Fintech Engineers - Process Automation Specialists ... Many of these roles barely existed at scale just a few years ago. And they’re not all technical. We’re also seeing roles like prompt engineers, AI ethics leads, and AI product strategists gaining traction across different industries. 𝐎𝐧𝐞 𝐬𝐡𝐢𝐟𝐭 𝐭𝐡𝐚𝐭’𝐬 𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐦𝐨𝐫𝐞 𝐯𝐢𝐬𝐢𝐛𝐥𝐞 𝐧𝐨𝐰 𝐢𝐬 𝐭𝐡𝐞 𝐫𝐢𝐬𝐞 𝐨𝐟 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬. We’re moving from simple model outputs to systems that can take actions, use tools, and follow goals across multiple steps. That shift is bringing new types of roles with it: • Engineers and researchers building agent frameworks • Product teams defining how agents fit into user journeys • Decision engineers designing shared workflows between humans and machines • Governance and compliance leads ensuring safety and alignment ... And this shift isn’t limited to labs or big tech. Thanks to the growth of 𝐨𝐩𝐞𝐧-𝐬𝐨𝐮𝐫𝐜𝐞 𝐀𝐈 𝐭𝐨𝐨𝐥𝐬, agent development is becoming more accessible. And open source frameworks like LangChain are lowering the barrier for experimentation. 📍We also just open-sourced 𝐆𝐞𝐧𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐎𝐒, a lightweight framework we’ve been using internally to run multi-agent systems. If you’re playing around with agent workflows, feel free to check it out: GitHub: https://bit.ly/4kzE1Mt And if you’re into open source, a ⭐ would mean a lot! __________ For more on AI and Data Science, plz check my previous posts. I share my journey here. Join me and let's grow together. Alex Wang #technology #aiagents #agenticai #generativeai

2025 AI Career Guide: 12 High-Demand Roles in Artificial Intelligence As AI continues to transform industries, here are the most promising career paths for 2025: Technical Roles: 1. MLOps Engineer - ML infrastructure management - CI/CD for AI systems - Production deployment expertise 2. AI Architect - System design for AI solutions - Technology stack selection - Scalability planning 3. NLP Engineer - Language model development - Text analytics - Conversational AI 4. Computer Vision Engineer - Image/video analysis - Object detection systems - Real-time processing Emerging Specializations: 5. Prompt Engineer - LLM optimization - Context engineering - Response accuracy improvement 6. Edge AI Developer - Resource-optimized AI - IoT integration - Embedded systems Strategic Roles: 7. AI Ethics Officer - Responsible AI development - Bias mitigation - Compliance management 8. AI Data Strategist - Data architecture - Quality assurance - Pipeline optimization Advanced Positions: 9. AI Research Scientist - Algorithm development - State-of-the-art advancement - Technical publication 10. AI Performance Engineer - Model optimization - Latency reduction - Computational efficiency 11. AI Integration Specialist - System integration - API development - Infrastructure compatibility 12. AI Product Manager - AI product lifecycle - Requirement translation - Stakeholder management • Technical expertise remains crucial • Ethics and responsibility are increasingly important • Integration and optimization skills are highly valued • Product and strategy roles growing in demand Have I overlooked anything? Please share your thoughts—your insights are priceless to me.

If you're in tech, you're sitting on a goldmine right now. While everyone's debating AI job displacement, the engineering sector is quietly becoming the biggest AI beneficiary. The World Economic Forum projects 78 million net new jobs by 2030, and IT and Engineering is leading the charge. This shift is creating entirely new job categories that didn't exist two years ago. Here are five emerging growth areas for IT and Engineering: 1. AI-native product development → AI Product Managers who understand ML lifecycles and enterprise pain points. 2. AIOps infrastructure → MLOps engineers are moving companies from AI experiments to production. Every enterprise needs these skills. 3. AI cybersecurity → Red teamers for LLMs are literally paid to break AI systems.  4. Enterprise data infrastructure → Vector database engineers managing RAG pipelines are helping AI systems access the right information at the right time. 5. Vertical AI specializations → LegalTech AI specialists, FinTech AI analysts, HR tech AI specialists—domain expertise + AI fluency is the new superpower. The numbers back this up: $632 billion in AI spending (including applications, infrastructure, and IT services) by 2028. This will lead to new AI roles in engineering, product, data, and operations to maintain these AI systems. Bottom line: The engineers who adapt fastest will have the most opportunities. In my latest newsletter, I break down exactly how to transition into each of these roles, plus the specific tools and skills that matter most. What AI role are you most curious about? #AI #Engineering #IT #FutureOfWork

AI isn’t just creating new tools, it’s creating entirely new careers. And as I move deeper into my own AI journey, I want to take you with me. If you're building a team, hiring talent, or planning your own career path, understanding this new landscape is no longer optional. It’s a competitive advantage. Here's a breakdown of emerging AI roles that are essential for building the future of AI-driven systems: AI Roles: 1. Model Manager Oversees development, deployment, and performance of ML models. Tech Stack: Python, TensorFlow, Kubernetes, Docker. 2. ML Engineer Designs, develops, and deploys scalable machine learning solutions. Tech Stack: Python, PyTorch, AWS/GCP, SQL. 3. Data Engineer Creates and maintains data pipelines for model training. Tech Stack: Python, Spark, Kafka, AWS/GCP. 4. AI Architect Designs scalable AI systems integrated with existing infrastructure. Tech Stack: Python, Kubernetes, Microservices, Docker. 5. Data Scientist Analyzes data to build predictive models and generate insights. Tech Stack: Python, R, TensorFlow, Hadoop. 6. AI Developer Develops AI applications, integrating ML algorithms into production. Tech Stack: Python, Java, TensorFlow, Kubernetes. 7. Decision Engineer Builds systems to automate decision-making using AI models. Tech Stack: Python, ML frameworks, Cloud platforms. --- Emerging AI Roles: 8. Analytics Engineer Transforms data into actionable insights using analytics tools. Tech Stack: Python, SQL, Tableau, Apache Airflow. 9. AI Product Manager Manages the lifecycle of AI-driven products, bridging technical teams and stakeholders. Tech Stack: Jira, Python (basic), Agile methodologies. 10. UX Designer (AI) Designs user interfaces for AI applications, ensuring seamless AI-powered experiences. Tech Stack: Figma, Adobe XD, HTML/CSS, JavaScript. 11. Head of AI Leads AI strategy across the organization, ensuring alignment with business goals. Tech Stack: Leadership tools, Cloud platforms, Project management software. 12. D&A and AI Translator Translates business needs into technical AI solutions, bridging the gap between teams. Tech Stack: Python, SQL, Jira, Agile. --- Must-have AI Roles: 13. AI Risk and Governance Specialist Ensures compliance with legal, ethical, and regulatory standards for AI systems. Tech Stack: Compliance tools, Risk management software. 14. Model Validator Validates the accuracy and reliability of ML models in real-world environments. Tech Stack: Python, Scikit-learn, TensorFlow. 15. Prompt Engineer Optimizes large language models by fine-tuning prompts for better performance. Tech Stack: Python, NLP frameworks, Hugging Face. 16. AI Ethicist Ensures AI systems are fair, transparent, and ethically sound. Tech Stack: Ethical guidelines, Compliance tools. If you want to stay ahead of the AI curve, follow along. Let’s navigate the AI era together. Which of these roles fascinates you the most, or aligns with your next career move? Comment below. #AI