The Future of Work in the Age of AI

The world of work is entering a period of profound transformation. According to the World Economic Forum, roughly a quarter of all jobs could undergo significant changes over the next five years due to automation and the spread of AI technologies. Around 39% of the skills that workers possess today may be reshaped or partially lose relevance between 2025 and 2030.

A parallel trend is highlighted by McKinsey & Company, reporting that about 88% of the surveyed organizations already employ AI in at least one business function. Not only routine tasks — but also more complex activities — are increasingly being carried out or supported by algorithms now.

This convergence—widespread AI adoption combined with limited scaling and skills disruption—holds profound implications for the future of work. Tasks once considered uniquely human, such as analysis, synthesis, and creative conceptualization, are increasingly shared with or delegated to algorithmic systems.

The creative industries— design, advertising, and visual communication— provide a vivid illustration of this shift. The generative AI market in these domains was valued at around US$3 billion in 2024, with projections suggesting growth to over US$11 billion by 2029, expanding at about 30% annually. Creators now progressively focus on managing systems, picking directions, and formulating the right prompts, rather than producing everything entirely by hand.

Understanding these tendecies is no longer purely an academic exercise. For professionals, educators, and organizations, it is essential to identify which tasks may disappear, which new ones will emerge, and which skills will remain indispensable in order to stay in demand.

AI in Action: Real-Life Examples

With generative tools advancing rapidly, artificial intelligence is no longer just a support system—it’s becoming a true creative partner across industries. From marketing to film production, AI is helping professionals generate ideas, personalize experiences, and streamline workflows.

In advertising, AI is revolutionizing how campaigns are produced. A Forrester report finds that 91% of U.S. agencies are either actively using or exploring generative AI, signaling that these tools are now standard practice rather than experiments. For instance, Cadbury’s “Shah Rukh Khan - My - Ad” campaign, developed with Ogilvy India and Wavemaker Mumbai, used machine learning to create personalized video messages for individual stores and locations, selecting the right version for each audience. Similarly, Coca-Cola employed AI to analyze consumer data to help tailor experiences to different audiences, boosting engagement and contributing to sales growth. In their another initiative, fans could use an AI-powered platform to create custom digital cards by combining Coca-Cola’s images and brand elements.

The film industry is also embracing AI. The short film Sunspring (2016) was written entirely by the neural network Benjamin. More recently, in Emilia Pérez movie was used Respeecher’s AI technology to enhance actress Karla Sofía Gascón’s singing voice, blending it seamlessly with French pop star Camille’s vocals to create a natural, polished soundtrack.

In design and visual communication, technologies are used as an accelerator of ideas and prototypes. According to Creative Boom, agencies use tools like Midjourney to quickly generate mood boards, 3D scene concepts, and visual prototypes. Designers then refine and adapt these AI-generated ideas, which then serve as a starting point for discussions with clients and collaborative decision-making during the creative development process.

AI is transforming journalism as well. According to the 2025 State of the Media Report, 53% of journalists now rely on AI tools for automating repeated tasks, research, transcription, and data analysis. For example, the German newspaper Stuttgarter Zeitung uses machine learning to interpret police reports, classify events, and build a CrimeMap service, freeing journalists from the routine processing of incoming information and allowing them to focus on investigative work.

Evolving Roles and New Careers

These developments—driven by advances in AI—are causing raising concerns: many fear that machines could completely replace human jobs. A Pew Research Center survey found that 32% of U.S. workers believe AI could lead to the disappearance of their roles. However, the PwC report “2025 Global AI Jobs Barometer” shows a different picture: even in highly automatable occupations, the number of jobs is growing, and AI is making workers more valuable rather than less. And as former IBM CEO Ginni Rometty said: “AI will not replace humans, but those who use AI will replace those who don’t.”

This means that job loss is not the dominant scenario; instead, roles are being transformed and new ones are being created. For instance, completely new professions have appeared in recent years: prompt engineers, responsible for crafting and optimizing inputs to generative AI models, and AI ethics specialists, who ensures that algorithms operate transparently, safely, and fairly.

Many existing professions are evolving as well. Tasks that were once strictly “human” or “machine” are increasingly shared in hybrid roles. For example, the product manager role has transformed: previously focused on strategy, marketing, and product launch, today these professionals oversee AI-integrated products, manage development, evaluate AI capabilities and risks, coordinate teams, interact with users, and ensure ethical compliance.

The financial analyst role offers another example. Analysts once collected data, built forecasts, and prepared reports. Now, AI handles massive datasets, models scenarios, and identifies patterns, while humans remain essential for interpreting results, making strategic decisions, and validating AI outputs.

Learning AI: Training and Education for Tomorrow

Following these changes, programs entirely devoted to AI have started to appear, aiming to train specialists who can confidently use AI tools and algorithms across different fields. Both universities and online platforms now offer courses that not only cover the practical use of generative models but also discuss responsible and ethical AI practices.

For example, Stanford University and MIT have launched workshops and courses on generative AI, including “The World of Generative AI: An Immersive Exploration Workshop” and “Driving Innovation with Generative AI”. These programs let students experiment with models like ChatGPT and Stable Diffusion, turning ideas into concepts and even working on prototype projects.

Beyond individual courses, full degree programs focused solely on AI are also being introduced. The Mohamed bin Zayed University of Artificial Intelligence in Abu Dhabi, for example, offers a Master’s in Applied Artificial Intelligence. This program blends theory with hands-on, project-based learning and emphasizes collaboration with industry, research, and entrepreneurial initiatives.

Another interesting case is the University of York’s MSc in Artificial Intelligence for the Creative Industries. The program combines core technical topics, like neural networks, with creative and social perspectives. Students explore ethical challenges such as copyright, privacy, and the potential misuse of deepfakes, while also creating and testing intelligent systems that can either be interactive media projects or practical tools to support creative work.

With the rapid spread of educational programs aimed at training specialists to work with AI, it is becoming clear that professionals will need new, more specific skills. In the near future, these are primarily concrete competencies directly related to interacting with algorithms:

• Curating AI outputs
• Prompt engineering
• Multimodal integration
• Data interpretation & visualization
• AI model optimisation & quality control

Yet, as the World Economic Forum points out, at a higher level, generalized competencies that cannot be fully automated become especially significant.

The human of the future needs to be critically thinking, distinguishing valuable information from noise and evaluating AI outputs for quality, ethics, and social impact;

to be emotionally intelligent, working effectively with people, leading teams, and collaborating productively with AI;

and to be flexible and capable of synthesizing information, integrating diverse data, technologies, and experiences into innovative solutions.

How working with AI can look like

Mastering new skills helps people get ready for future hybrid roles, where humans and AI work side by side. But what is especially interesting is that different ways of working with AI exist and will continue to develop.

Researchers identified three distinct types of collaboration: Support, Synergy, and Symbiosis. Support is the most familiar and already common in many companies. AI helps speed up routine tasks, analyze customer data, or generate design and text options. While powerful, it primarily functions as a helper. Synergy and Symbiosis, in contrast, go deeper and still under active exploration.

A good example comes from a study “Exploring the Collaborative CoCreation Process with AI: A Case Study in Novice Music Production”. Over several weeks, students used AI to compose music, write lyrics, design album covers, and manage distribution. AI sped up idea generation, letting them explore many more options than they could on their own. At the same time, a new stage appeared in the creative process—what researchers called “collaging and refinement.” Participants had to choose, combine, and polish AI-generated fragments into a finished piece. They also noted that working with AI changed how team collaborated, as members adjusted roles and strategies to get the most out of the technology.

Adobe Research offers another example with its LACE system in Photoshop. LACE supports turn-taking, where users and AI alternate contributions, and parallel co-editing, where AI continuously suggests ideas in the background while users decide what to keep. This allows real-time experimentation and fine-tuning, so artists can merge AI-generated ideas with their own work without interrupting their creative flow. Tests showed that participants preferred this co-creative mode, producing designs that were both higher in quality and more diverse.

The Future of Work

This all leads to the conclusion: the workforce is changing — and quickly. But no, it isn’t about AI stealing our jobs. It’s about the kinds of tasks we do, the roles we take on, and the skills we need.

In the next 10–20 years, a lot of the routine work we do today will slowly disappear. What will count most are the skills that machines just can’t match — thinking creatively and strategically, making sense of complex information, and keeping things running smoothly. The changes will show up in almost all fields, from marketing and journalism to engineering, architecture, and education. Companies are already looking for people who can adapt easily and pick up new tools without hesitation. According to Aon, about 70% of organizations are now creating roles that focus on AI and tech-related skills.

Here are the steps you can take today to stay in demand:

• Learn new skills online

Use platforms for courses like LinkedIn Learning, edX, Microsoft Azure, HubSpot, and Adobe Creative Skills. Google also offers free programs. Moreover, YouTube and OpenCourseWare provide tutorials on almost every topic.

• Get certified

Pick courses with certificates that HR systems recognize and that you can add to LinkedIn. Research shows that people with verified certificates and digital portfolios get noticeably more attention from recruiters — sometimes up to 20% more.

• Stay updated about your field

Read news and industry reports to see which tasks are being automated and which tools are becoming more popular. Being informed allows you to stay on track.

• Use AI in practice

Try new tools, even on small personal projects — generate ideas, analyze data, or automate simple tasks. Explore popular platforms, from ChatGPT to Seedream, to get comfortable working with AI and understand the world of neural networks.

• Build a digital portfolio

Share these projects and certificates in a portfolio. It strengthens your resume, helping employers actually recognize your value.

So… jobs aren’t going anywhere. People who learn to work effectively with AI — not against it — will stay in demand and find new ways to grow professionally