By the end of the decade, artificial intelligence will contribute $20tn (£16tn) to the global economy, driving 3.5 per cent of global GDP according to a recent report by IDC.
AI and accelerated computing are transforming industries like healthcare, retail, banking, customer service, and manufacturing at an exceptional pace, with every dollar spent on AI generating $4.60 (£3.67) into the global economy.
Behind this phenomenal growth are two key pillars for continued success: AI skills training and ecosystem support.
Technology is evolving at an unprecedented pace, making continuous learning essential for organisations to stay at the forefront of innovation.
The rapid adoption of AI and accelerated computing have fuelled the need for a skilled workforce adept at leveraging these platforms to create solutions that positively impact society. AI leaders expect that AI will not replace the work of humans, but will assist them in their daily jobs instead – leading to more efficient and productive results.
According to the World Economic Forum’s 2025 Future of Jobs Report, big data specialists and artificial intelligence/machine learning experts top the list for fastest-growing roles globally, with AI predicted to create 11mn new jobs.
Training and upskilling is essential to progressing in the AI-driven world. Although the material may be complex, finding the opportunities to learn is not.
NVIDIA’s Deep Learning Institute, launched in 2016, equips people with the critical skills to navigate and lead the technology-driven future. AI education is more than a pathway to innovation – it’s a foundation for solving some of the world’s most pressing challenges.
Ten years prior, CUDA was created – a computing platform that can leverage the power of GPUs for accelerated general-purpose computing – which fast became the foundation of the GPU computing system. Every GPU application and framework uses CUDA, meaning a thorough understanding is fundamental for any AI developer.
Equipping developers with these opportunities to explore, understand and create with AI can help lead to professional advancement in a variety of areas, including medicine, engineering and more. A 2023 study by the University of Oxford found that workers with AI skills command salaries approximately 21 per cent higher than their peers, with potential increases of up to 40 per cent.
AI learning is becoming more prevalent in higher education, with universities now using AI to enhance accessibility, innovate teaching methods, and future-proof their curricula. Across Europe, the Middle East and Africa, universities from many countries are leveraging AI to provide innovation in education and research, benefiting faculty and students with the value of AI assistance.
AI is already becoming part of the classroom, thanks to education innovators like Evoke AI. A startup and member of NVIDIA Inception, their technology transforms lessons from textbook-based theory into vibrant, interactive scenarios to make learning engaging and relevant, bridging the gap between knowledge, student and teacher.
At NVIDIA’s GTC in March 2025, developers can enhance and build their skills by taking part in new training labs, workshops, self-paced courses, and professional certifications spanning key areas like accelerated data science and agentic AI.
At the heart of AI’s engine of global economic growth is the need for robust, open source AI infrastructure, along with an ecosystem of startups and developers to harness the potential of AI. Open source AI models and tools are fundamental for the ecosystem, enabling innovation, agility, better and faster problem-solving, and increased security.
Many European countries are now seeing the value in developing and deploying AI using their own infrastructure, data, workforce, and networks – also known as sovereign AI. By building AI infrastructures, countries are creating environments for AI to thrive. They can foster local startups, attract global talent and partnerships for their research hubs, spur new businesses by entrepreneurs, and speed development of AI-accelerated applications tailored to key markets, which can bolster global competitiveness and have long-term positive impact on GDP. By providing compute and training resources for their local ecosystems, countries are equipping researchers, innovators, and startups with critical tools to combat climate change, boost energy efficiency, and protect against cybersecurity threats.
AI infrastructure is the fabric for innovative, risk-taking startups, developers and researchers. By giving them cost-effective access to cloud platforms, high-quality open source AI models and tools, and access to high-performance hardware, startups can focus resources on innovation and scale rapidly. It allows them to access accelerated computing, create applications, implement use cases, and drive growth.
Technology isn’t only being democratised at country-level, but at a community level too. AI startup accelerator programs like NVIDIA Inception, Microsoft for Startups, and Google for Startups to name but a few are providing startups with access to resources like technical tools and training, hardware, and subject matter experts to scale quickly.
Adding $20tn to the global economy in the next five years isn’t surprising when AI is creating entirely new sectors that simply didn’t exist a decade ago. Emerging markets such as autonomous vehicles, smart factories, and personalised healthcare need strong AI foundations to thrive. Organisations are creating new job opportunities with smarter products and services and new business models, and are increasing overall profitability by reducing operating costs through efficiencies created by AI.
The landscape of technology is changing, quickly. Every day, new advancements are made, new technologies are invented, and new skills are ready to be learned.
