How to Survive AI

For the past few years, there have been an increasing number of layoffs where company management cites the reason being the need to invest more resources in artificial intelligence rather than people. Whether the companies are in technology, finance, or other sectors, there is an increasing emphasis on organizations flattening their structure to become more efficient and allocate more investment in AI infrastructure and tools.

Recently, Design News Senior Editor Spencer Chin conducted an email interview with Anant Kale, co-founder and CEO of AppZen, an AI-driven finance company. AppZen has pioneered the use of artificial intelligence. Kale's takes may not be comforting to those who have lost jobs, but his message is clear: AI is here to stay, and those who wrap their arms around AI tools and learn how to use them are more likely to be valued employees in the future.

DN: There's an increasing number of companies that say their need to invest in AI does not justify employing as many people. Why haven't some companies figured out a way to keep these workers and let them work with AI tools instead?

The assumption that every role can simply be augmented with AI isn't always correct. Some jobs will be transformed, some will become significantly more productive, and some will no longer be needed in their current form.

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What's changing is that companies are being asked to grow without proportional increases in headcount. In finance, we see organizations using AI agents to execute work that previously required large operational teams. The question becomes less about replacing people and more about reallocating human talent toward higher-value activities.

The organizations that will win are not necessarily those that eliminate the most jobs. They'll be the ones that successfully combine human expertise with AI execution. The future is hybrid teams, where AI handles repetitive and process-heavy work while people focus on judgment, strategy, innovation, and business partnership.

DN: If fewer recent graduates are hired, doesn't that weaken the future talent pipeline?

It's a legitimate concern. Historically, entry-level roles served as training grounds where people learned processes and developed expertise. If AI automates much of that work, companies will need new models for developing talent.

The good news is that AI can actually accelerate learning. Instead of spending years on repetitive administrative tasks, new employees can spend more time understanding business outcomes, decision-making, and strategy.

The challenge for leaders is to intentionally create development paths. Future talent won't be trained by processing transactions manually. They'll be trained by learning how to supervise, improve, and govern AI-driven systems while developing deeper business expertise.

The jobs may change, but the need for talent development doesn't disappear.

DN: What AI skills are needed as workplaces move toward agentic AI? How can workers acquire them?

The most valuable skill won't be prompt engineering. It will be understanding how work gets done.

Agentic AI operates best when there are clear processes, governance, and decision frameworks. Employees who understand workflows, business rules, compliance requirements, and operational outcomes will be incredibly valuable because they're the people who can help design, supervise, and improve AI-driven systems.

Process design and optimization: understanding how work flows across an organization.

AI governance and oversight: ensuring decisions remain compliant, explainable, and auditable.

Business judgment: knowing when humans should intervene and when AI can operate autonomously.

The best way to develop these skills is hands-on experience. Use AI tools today. Learn how they succeed, where they fail, and how to structure work so humans and AI can collaborate effectively.

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DN: Will today's in-demand AI skills eventually become obsolete?

Yes, some will. That's been true throughout every technology cycle. The specific technical skills that are valuable today will evolve as the technology matures.

What tends to endure are higher-order skills, including problem-solving, systems thinking, leadership, domain expertise, and business judgment.

As AI becomes more capable, the competitive advantage shifts from knowing how to use a particular tool to understanding how to apply technology to achieve business outcomes.

We're already seeing this shift. The conversation is moving from "How do I use AI?" to "How do I redesign work, teams, and operating models around AI?"

The organizations and individuals that thrive will be the ones that continuously adapt. The skill of learning may become more important than any individual AI skill itself.