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Reshaping Every Career"],"type":"heading2",":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/blog/blog-hero"}},":itemsOrder":["blog_hero"]},"responsivegrid_content":{"columnClassNames":{"blog_text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-0815e1752b","text":"\u003Cp\u003E“AI is taking over jobs” has become a catchall phrase for a much bigger, more uneven shift. Some jobs will shrink. Some will disappear. This is what I like to refer to as “job churn.” Job churn is the rate at which employees leave roles and are replaced, and it has evolved over time. As far back as the early 20th century, high levels of job churn prompted studies on the cost of turnover as well as strategies for retention such as pay increases. From the 1920s through the 1970s, stability increased, with a long-term decline in turnover as organizations developed internal labor markets, seniority-based compensation, pension plans and formal training. From the 1980s through the 1990s, mobility increased. Research in this period, particularly in the United States and the United Kingdom, noted shortening job tenures, with a significant rise in employees staying at a job for less than two years. From the 2000s to today, long-term tenure has remained relatively high for older workers, while younger generations have exhibited much higher turnover rates. The 2010s saw a decline in labor turnover in some sectors, followed by disruptions from the COVID-19 pandemic and the rise of technology-driven “creative destruction.” Today, the drivers and patterns of job churn feel different. The question is why.\u003Cbr\u003E\r\n\u003Cbr\u003E\r\nWith new economies come new skills. The job landscape is transforming at unprecedented speed, with industries demanding skills that drive productivity, resilience and innovation. Many jobs will be redesigned. Many people may feel the change first through their workflow, not through their job title. Work is being decomposed into tasks, then rebuilt around data, automation and machine reasoning. That is what makes this moment different. Not only is it about new tools; it is about a new operating model for work. What skills will workers need to support economic transformation and enable businesses to compete and grow? According to the \u003Ca href=\"https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opportunities-by-2030-but-urgent-upskilling-needed-to-prepare-workforces/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EWorld Economic Forum’s Future of Jobs Report 2025\u003C/a\u003E, the global economy is expected to see a net increase of 78 million jobs by 2030. While 170 million new roles are projected to be created, approximately 92 million existing roles are expected to be displaced.  \u003C/p\u003E\r\n\u003Cp\u003ESo the practical career question in 2026 should no longer be “Will AI replace my job?” Rather, it is “Am I ready?” Ask yourself the following questions: \u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EWhich parts of my role are most exposed to automation?\u003C/li\u003E\r\n\u003Cli\u003EWhat new expectations are forming around data, metrics and evidence?\u003C/li\u003E\r\n\u003Cli\u003EWhere does human judgment still matter, and how do I demonstrate that I have it?\u003C/li\u003E\r\n\u003Cli\u003EWhat emerging tech skills will keep me credible, useful and mobile?\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EThis blog post explores \u003Ci\u003EAI’s impact on employment\u003C/i\u003E, the reality behind \u003Ci\u003EAI job loss and AI and job displacement\u003C/i\u003E, and what it means for the \u003Ci\u003Efuture of work\u003C/i\u003E across industries. It is also written with a practical call to action.\u003C/p\u003E\r\n\u003Cp\u003ETo set the context, here are some questions people are asking right now, along with practical answers.\u003C/p\u003E\r\n\u003Ch2\u003EWhat is AI’s impact on employment?\u003C/h2\u003E\r\n\u003Cp\u003EA practical way to frame it is this: AI is changing the content of work faster than it is changing job titles.\u003C/p\u003E\r\n\u003Cp\u003EA useful way to think about AI and jobs is across three layers.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003ETask automation\u003C/b\u003E: Some tasks are straightforward to automate, including triage, classification, summarization, extraction, basic drafting and simple reconciliation. When these tasks make up a large share of a role, people experience AI as “taking over jobs,” because it removes real working hours.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003ETask augmentation\u003C/b\u003E: Many jobs will not be eliminated but upgraded. AI becomes a copilot for analysis, writing, planning, coding, customer support and operational troubleshooting. The job remains, but the baseline output expected from the person rises.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003ERole redesign and displacement\u003C/b\u003E: Some roles shrink materially because a large proportion of their task inventory becomes automatable or because work is consolidated among fewer people overseeing systems. This is where AI job displacement becomes visible, particularly in roles built around predictable information handling.\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003ESeveral global institutions have argued for a similar framing. The \u003Ca href=\"https://www.ilo.org/publications/generative-ai-and-jobs-global-analysis-potential-effects-job-quantity-and?\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EInternational Labour Organization\u003C/a\u003E’s work on generative AI emphasizes that the dominant effect is likely to be augmentation rather than total automation for most occupations, but with higher exposure in clerical and administrative work, especially in higher-income economies. At the same time, the scale of disruption is not small. So yes, some categories may see AI-related job loss, depending on task mix, adoption pace and local labor conditions. However the bigger story is that roles are evolving in terms of what employers expect, how performance is measured and which skills signal future value.\u003C/p\u003E\r\n\u003Ch3\u003EThe shift in AI skills \u003C/h3\u003E\r\n\u003Cp\u003EYou will see a wide range of figures regarding AI in the workplace, because different studies measure different things, including:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003ETask exposure\u003C/b\u003E: What portion of tasks could be automated or augmented\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003ERole displacement\u003C/b\u003E: Jobs that could shrink or disappear\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EHours displaced:\u003C/b\u003E How much labor time could be automated even if jobs remain\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EA practical way to interpret the landscape is to stop looking for a single headline number and focus on two more useful measures:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003EHow much of employment is exposed to AI? \u003C/b\u003EThe \u003Ca href=\"https://www.imf.org/-/media/files/publications/sdn/2024/english/sdnea2024001.pdf\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EInternational Monetary Fund\u003C/a\u003E estimates that almost 40% of global employment is exposed to AI, rising to around 60% in advanced economies, largely because more work is cognitive and office based. It also notes that roughly half of exposed jobs may benefit from AI integration, while the other half may be negatively affected through substitution of tasks, reduced hiring or wage pressure. This tells you the reach is broad, especially for knowledge work.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EHow much disruption is expected? \u003C/b\u003EThe World Economic Forum’s employer-based outlook provides one of the clearest quantified estimates for displacement and creation in the 2025-to-2030 window. If you want a sensible working conclusion for your own career planning, it should be that \u003Ca href=\"https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opportunities-by-2030-but-urgent-upskilling-needed-to-prepare-workforces/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eby 2030\u003C/a\u003E a meaningful share of roles will be displaced or materially redesigned. Many more people are likely to experience a change in required skills than a change in job title.\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EThe next wave of AI integration makes clear that tech roles are changing quickly. Technical AI skills are essential as we move toward dynamic human-AI teams. The evolution of roles through technology isn’t new, but the speed and scale of innovation today are unprecedented. The real test is how we respond to gain needed skills instead of being left behind. To ensure that you continue to evolve and grow, think through which tasks in your current role are most exposed and what capabilities will help you move up the value chain. How can you prepare to meet the demands of this era and open doors to new possibilities and opportunities for yourself?\u003C/p\u003E\r\n\u003Ch2\u003EWhat types of jobs will AI affect most?\u003C/h2\u003E\r\n\u003Cp\u003EA useful rule of thumb is simple: Jobs built around repeatable information work are more exposed than roles grounded in physical variability, complex human interaction or high-accountability judgment.\u003C/p\u003E\r\n\u003Cp\u003EThe ILO’s global analysis above points to higher exposure in clerical work and administrative tasks, and it highlights that the effect can be gendered because clerical roles are an important source of female employment in many economies. The IMF adds an important nuance: Exposure is not destiny. Impact depends on whether AI complements the role or substitutes for the key tasks that justify the job.  \u003C/p\u003E\r\n\u003Cp\u003EWith that in mind, here are some practical categories to consider.\u003C/p\u003E\r\n\u003Ch3\u003ERoles at higher risk of AI job displacement\u003C/h3\u003E\r\n\u003Cp\u003EThese are not “low-value” roles. Many are essential. The issue lies in the task mix.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EClerical and administrative coordination roles built around scheduling, document preparation and standard communications\u003C/li\u003E\r\n\u003Cli\u003EEntry-level knowledge work that primarily involves summarizing, formatting or producing routine outputs\u003C/li\u003E\r\n\u003Cli\u003ECustomer support tiers that handle predictable queries without complex judgment\u003C/li\u003E\r\n\u003Cli\u003EBasic content production roles where differentiation is low and throughput is the main metric\u003C/li\u003E\r\n\u003Cli\u003ESome compliance preparation and reporting tasks that are checklist driven, where judgment still matters but the paperwork can shrink\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003ERoles that are changing, not disappearing\u003C/h3\u003E\r\n\u003Cp\u003EThese roles may become more valuable, but only if individuals adapt.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EAnalysts, finance partners, operations planners and product managers\u003C/li\u003E\r\n\u003Cli\u003EEngineers and developers (AI can accelerate output while raising the bar for verification)\u003C/li\u003E\r\n\u003Cli\u003ESales and marketing professionals working with data-driven segmentation and performance analysis\u003C/li\u003E\r\n\u003Cli\u003EHR and workforce planning professionals moving toward skills-based models\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003ERoles that remain harder to automate fully\u003C/h3\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EWork requiring physical dexterity in unstructured environments\u003C/li\u003E\r\n\u003Cli\u003ERoles where trust, care and human presence are central (health care, education, social care)\u003C/li\u003E\r\n\u003Cli\u003EComplex negotiations, leadership and accountable decision-making\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EOne additional nuance matters: AI can reshape early career pathways even if senior roles remain. Routine tasks have historically been how people learned the work. If those tasks shrink, organizations must redesign how junior employees build competence. If they do not, the future talent pipeline becomes fragile. How is AI reshaping jobs across industries?\u003C/p\u003E\r\n\u003Cp\u003ETo make this concrete, here are some examples of how automation is reshaping work by sector. If you work in these industries, you will recognize that this shift is already underway.\u003C/p\u003E\r\n\u003Ch3\u003EFinancial services\u003C/h3\u003E\r\n\u003Cp\u003EAI is being used for document processing, customer communications, internal coding acceleration and operational triage. In the UK, public commentary from financial leaders and policy discussions have increasingly\u003Ca href=\"https://www.theguardian.com/technology/2026/jan/23/ai-tsunami-labour-market-youth-employment-says-head-of-imf-davos\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E focused on reskilling and the risk to entry-level pathways\u003C/a\u003E, reflecting real concern about AI-driven labor shifts.\u003C/p\u003E\r\n\u003Cp\u003EWhat changes for people:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EHigher expectations of AI-supported productivity\u003C/li\u003E\r\n\u003Cli\u003EMore emphasis on oversight, risk and governance\u003C/li\u003E\r\n\u003Cli\u003ELess appetite for manual processing, as organizations shift from “Can we do this?” to “Should we still be doing this by hand?”\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003ERetail and ecommerce\u003C/h3\u003E\r\n\u003Cp\u003EAI is shifting forecasting, inventory optimization, pricing and customer service routing. This changes roles in merchandising, supply chain and service operations.\u003C/p\u003E\r\n\u003Cp\u003EWhat changes for people:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EAnalytics becomes embedded in daily decisions\u003C/li\u003E\r\n\u003Cli\u003EInterpreting signals correctly becomes part of professional competence\u003C/li\u003E\r\n\u003Cli\u003EDecision cycles speed up, with less time for manual reconciliation\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EMarketing and media\u003C/h3\u003E\r\n\u003Cp\u003EGenerative AI reduces the time to draft content, test variants and build assets. It also increases competition because output becomes cheap and abundant.\u003C/p\u003E\r\n\u003Cp\u003EWhat changes for people:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EDifferentiation shifts to judgment, strategy, experimentation design and measurement\u003C/li\u003E\r\n\u003Cli\u003EMeasurement literacy becomes more valuable, including attribution and incremental thinking\u003C/li\u003E\r\n\u003Cli\u003EBrand and regulatory constraints matter more, because risk travels faster when content creation is easy\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EConsulting, advisory and knowledge work\u003C/h3\u003E\r\n\u003Cp\u003EAI is increasingly used for research synthesis, proposal drafting, summarization of meetings and knowledge retrieval.\u003C/p\u003E\r\n\u003Cp\u003EWhat changes for people:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EBaseline output expectations rise\u003C/li\u003E\r\n\u003Cli\u003EVerification becomes a core professional skill\u003C/li\u003E\r\n\u003Cli\u003ETeams need clear standards for what can be automated and what must be reviewed\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EPublic sector and regulated domains\u003C/h3\u003E\r\n\u003Cp\u003EAdoption in government and regulated environments is shaped by accountability, procurement, privacy and auditability. That can slow things down, but it also makes the direction of travel clearer: AI tends to scale when it is governed, explainable enough for oversight and built on data foundations that stand up to scrutiny.\u003C/p\u003E\r\n\u003Cp\u003EAcross APAC, several governments are pairing adoption with formal governance and workforce capability building. \u003Ca href=\"https://www.tech.gov.sg/technews/how-ai-will-augment-human-labour-in-the-workforce\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESingapore’s GovTech\u003C/a\u003E has published a Government AI Blueprint that sets out an approach to moving toward an AI-enabled public sector in a way that aims to augment public officers and improve service delivery, rather than treating AI as a bolt-on tool. Singapore has also announced \u003Ca href=\"https://www.reuters.com/world/asia-pacific/singapore-invest-over-779-million-public-ai-research-through-2030-2026-01-24/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Elarge-scale public investment in AI research\u003C/a\u003E and talent through 2030, signaling that national capability building is being treated as core infrastructure. In Australia, the \u003Ca href=\"https://www.digital.gov.au/ai/ai-in-government-policy\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EDigital Transformation Agency \u003C/a\u003Ehas an AI in Government policy that sets expectations for responsible and accountable use of AI across agencies, and the Australian Public Service has been rolling out secure, government-controlled generative AI tooling for staff. \u003C/p\u003E\r\n\u003Cp\u003EWhat changes for people:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EStronger emphasis on defensible decision trails, transparency and accountability\u003C/li\u003E\r\n\u003Cli\u003EHigher value placed on data quality, lineage and governance\u003C/li\u003E\r\n\u003Cli\u003EPractical literacy needed across nontechnical roles, because risk and responsibility are distributed across the workflow\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch2\u003EWhat is actually changing in the AI job market?\u003C/h2\u003E\r\n\u003Cp\u003EWhen people talk about the AI job market, they often picture only new roles such as machine learning specialist or prompt engineer. Those roles exist, but the deeper change is that AI capability is becoming a requirement across many roles that are not labeled “AI.”\u003C/p\u003E\r\n\u003Cp\u003EThree shifts stand out.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003ESkills inflation\u003C/b\u003E: Roles start requiring new skills without title or pay band changes. You see it in job descriptions: “AI familiarity preferred,” “automation experience,” “data-driven decision-making,” “ability to work with AI tools.” This is one reason people feel pressure even when their job seems stable on paper.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EFaster skill turnover\u003C/b\u003E: The World Economic Forum has been clear that skill requirements will shift quickly across the 2025-to-2030 period, driven by technology adoption and changing business models. \u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EPolarization risk\u003C/b\u003E: People who combine domain expertise with data and AI literacy gain leverage. Those who cannot do so risk being pushed toward narrower execution work, which is often more exposed to automation and more vulnerable to wage pressure.\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EThis is where the negative impact of AI on employment becomes most visible. The harm is not only job loss. It can also be reduced mobility, weaker bargaining power and widening inequality between those who can steer systems and those who are managed by them. The IMF explicitly flags distributional risks and potential inequality effects as AI spreads. \u003C/p\u003E\r\n\u003Ch2\u003EAI-related job displacement impact is uneven\u003C/h2\u003E\r\n\u003Cp\u003EIt is worth saying plainly: AI-related job loss is real. But it will not land evenly across the economy, and it will not arrive at the same speed in every country, sector or job family.\u003C/p\u003E\r\n\u003Cp\u003EA clear APAC example is Singapore’s DBS Group. \u003Ca href=\"https://www.digital.gov.au/ai/ai-in-government-policy\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EIn February 2025, DBS stated \u003C/a\u003Ethat it expected AI to reduce the need to renew about 4,000 temporary and contract roles over the next three years, while also creating about 1,000 new AI-related roles. The impact is concentrated in specific task categories and employment types rather than across the entire workforce.\u003C/p\u003E\r\n\u003Cp\u003EAustralia offers another view of how uneven this can be. In\u003Ca href=\"https://www.digital.gov.au/ai/ai-in-government-policy\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E July 2025, Commonwealth Bank of Australia indicated\u003C/a\u003E role reductions as part of a shift toward using AI for certain tasks, prompting public scrutiny and union backlash. Even at a relatively small scale, it shows how quickly automation decisions can become visible when they affect frontline work.\u003C/p\u003E\r\n\u003Cp\u003EThe practical takeaway is that “AI is taking over jobs” usually means targeted substitution of tasks first, then broader redesign. For most people, the risk is not that a job disappears overnight. It is that parts of the role shrink, expectations rise and the remaining work shifts toward oversight, exception handling and judgment.\u003C/p\u003E\r\n\u003Ch2\u003ESo what can you do about it?\u003C/h2\u003E\r\n\u003Cp\u003EA more resilient approach for many professionals is to build capability that travels across tools.\u003C/p\u003E\r\n\u003Cp\u003EIn practice, that capability has five parts, and it maps closely to the emerging tech skills most organizations now need for sustainable digital transformation.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003EData literacy\u003C/b\u003E: You need to interpret metrics, question data and understand what is missing. If you cannot interrogate inputs, you cannot use AI outputs safely. Data literacy is also what keeps teams aligned on definitions, avoids rework and makes decision-making more consistent.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EAI literacy\u003C/b\u003E: You need a working mental model of what AI can do reliably, where it fails and why “confident” does not equal “correct.” You do not need to become a machine learning engineer, but you do need to understand the boundaries well enough to use AI responsibly.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EWorkflow fluency\u003C/b\u003E: AI changes how work flows. People who can redesign workflows, not just operate tools, become central. This is where many careers get reshaped: The value moves toward those who can integrate automation into real processes without breaking accountability.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EVerification and judgment\u003C/b\u003E: As output becomes cheap, judgment becomes expensive. Being able to validate, stress test and defend decisions is a differentiator. This is also where many organizations discover hidden risk: A “human in the loop” who cannot challenge outputs is not a safeguard but simply a tick in the box.\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EDomain expertise\u003C/b\u003E: AI amplifies domain expertise; it does not replace it. People who understand the business realities, constraints and trade-offs will outperform people who know only the interface. If you are building a data career, this is especially important: The market is shifting away from narrow tool fluency and toward applied competence, governance awareness and the ability to connect data to outcomes.\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch2\u003EIn-demand human skills\u003C/h2\u003E\r\n\u003Cp\u003EAI is shifting the workplace skill set. But human skills are still mandatory.\u003C/p\u003E\r\n\u003Cp\u003EAs AI transforms the workplace and reshapes the demand for technical skills, human skills remain not only relevant but increasingly essential. \u003Ca href=\"https://www.cisco.com/content/dam/cisco-cdc/site/m/ai-workforce-consortium/documents/2025-ai-workforce-consortium-full-report.pdf\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EAccording to the 2025 AI Workforce Consortium\u003C/a\u003E, in-demand human skills cluster around leadership and management, problem-solving and innovation, and collaboration and communication. These categories reflect a synthesis of skills that enables employees to lead change, navigate complexity and foster effective teamwork in an AI-augmented environment.\u003C/p\u003E\r\n\u003Ch2\u003EA personal invitation\u003C/h2\u003E\r\n\u003Cp\u003EIf this post has made you think “I need to get ahead of this,” I agree wholeheartedly. Thriving in an AI-driven job market requires a balanced development of skills. Embedding skills through real-world, scenario-based learning fosters problem-solving, innovation and adaptability in fast-changing environments. On Feb. 13, 2026, I’m hosting an online session to kick off the Data and AI Fast Track, a free webinar series by Snowflake. \u003C/p\u003E\r\n\u003Cp\u003EIt is designed for individuals who want practical clarity on:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EAI and job displacement, and what it really means in day-to-day work\u003C/li\u003E\r\n\u003Cli\u003EThe emerging tech skills that matter most for the next few years\u003C/li\u003E\r\n\u003Cli\u003EHow to build AI skills without having to be a specialist\u003C/li\u003E\r\n\u003Cli\u003EHow data literacy supports career resilience and better decisions\u003C/li\u003E\r\n\u003Cli\u003EHow organizations can approach change without leaving people behind\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EYou will not be doing it alone. Many people who begin with uncertainty end up discovering that these concepts are far more approachable than expected. Your career still has a long horizon, and building literacy in data and AI will support you at every stage of it. It strengthens your influence in conversations, helps you interpret complex information and reduces the uncertainty that comes with rapid change. Join me to build practical skills and confidence.\u003C/p\u003E\r\n\u003Cp\u003E\u003Ci\u003ERegister for the \u003Ca href=\"https://www.snowflake.com/data-and-ai-fast-track-webinar-series/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Elive broadcast series\u003C/a\u003E.\u003C/i\u003E\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"columnClassNames":{"premium_content_bann":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{"premium_content_bann":{"id":"premium-content-banner-9d5b0fa844","contentEyebrow":"Live Broadcast Series ","contentHeadline":"Data and AI Fast Track Series","contentDescription":"Fast Track Your Career with Data and AI 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