Five lessons for the next generation of AI engineers

As artificial intelligence (AI) continues to reshape industries worldwide, Kanishka Kumar, a Chevening alumnus working in the AI sector, offers five insights on the skills, mindset, and values that will define the next generation of AI leaders.

1. Stay curious about how the field is evolving

AI in 2026 will look very different from the systems we’re working with today. A shift toward smaller, specialised models designed for specific tasks, and multimodal systems that process text, images and sound. New governance frameworks that emphasise transparency and security mean that future engineers will often work with a combination of models rather than one large system.  

To thrive, you need to stay curious about how the field is evolving, not just in terms of tools, but in the values and priorities shaping their use.  

2. Build strong foundations in software and systems 

Behind every great AI solution is a solid grasp of software engineering. Understanding data structures, system design, and machine learning operations is essential. Learn how to deploy, monitor and improve models in production and get comfortable combining practical coding skills (Python ,Docker, Kubernetes) with infrastructure knowledge (cloud APIs, edge runtimes).  

 The more you understand how the whole system fits together, the more effective and employable you’ll be. 

3. Don’t underestimate the power of non-technical skills

AI engineering isn’t just about algorithms. You’ll need to turn abstract ideas into measurable problems, communicate clearly with non-technical teams, and understand how your work contributes to business or societal goals. Learn to talk about your projects in terms of impact – cost, safety, latency, and ethics. 

The best AI professionals blend technical fluency with empathy, communication, and domain understanding.   

4. Learn by doing – and showing

Employers value hands on experience over theory. Build two or three full projects that take an idea from data pipeline to deployment and monitoring. Open-source your work where possible and describe your design choices clearly – what you built, why it mattered, and what you learned.  

This not only develops your skills but signals curiosity, initiative and accountability, traits that stand out to hiring managers everywhere. 

5. Keep your mindset agile

The AI field moves quickly. What you know today might be outdated next year, but your ability to learn, adapt, and collaborate will always stay relevant. Stay inquisitive, approach technology with empathy, and think globally.  

Chevening taught me that leadership isn’t just about expertise; it’s about using your skills to create meaningful change for others.  

 In the end, the brightest AI professionals will be those who combine deep technical know-how with ethical awareness and human understanding. Keep learning, stay open-minded and mentor others along the way.  

Kanishka Kumar is a Chief Marketing Officer (CMO) with 18 years of experience in driving marketing for AI, B2B SaaS and digital transformation companies across global markets. A British Gas/ Strathclyde/Chevening Scholar with an MBA from the University of Strathclyde, he has led marketing functions that accelerated revenue growth, brand visibility and market expansion.