Artificial intelligence is changing how work is done across industries. As companies automate tasks, many workers are losing jobs. At the same time, job losses are pushing more people to start businesses of their own.

Data from 2024 shows a 67% rise in new ventures launched by people after layoffs. With AI adoption expected to expand further in 2026, that number is likely to grow. While some roles are disappearing, new forms of work are emerging.

Read also: Five AI business ideas shaping small enterprise opportunities in 2026

Here are five business models that remain viable as AI reshapes the workforce.

1. Digital services

Many companies introduce AI in stages rather than all at once. During these transitions, human support is still required. This creates room for contract-based digital services.
Digital services cover a wide range of work. These include digital products such as e-books and online courses, as well as services like content moderation. In content moderation, people review user-generated material to check if it follows platform rules. This work relies on judgement, context and interpretation, areas where AI still struggles.

Another area is custom workflow automation. Small businesses often use several tools that do not work well together. Professionals who can connect systems and improve internal processes remain in demand. Niche services, such as healthcare compliance consulting for digital platforms, also require knowledge of regulations that AI cannot fully manage. Businesses continue to value clear communication and human-led support.

Read also: What’s next in AI: 7 trends to watch in 2026

2. Coaching

Large-scale layoffs often leave workers uncertain about their next steps. This creates demand for coaching services.

Career coaching helps displaced workers explore new paths. Many coaches draw on their own experience of job loss and career change. Coaching also extends to skills development, including coding, sales, public speaking and digital literacy.

Unlike automated advice, coaching involves accountability and emotional support. These human elements help people stay focused and move forward during periods of uncertainty. As industries shift, coaching remains a form of work that relies on trust and lived experience.

Read also: Five skills every leader needs in the age of AI
3. Virtual assistant services

Virtual assistants support business owners by managing daily operations. This allows clients to focus on their main objectives.

Common tasks include scheduling, calendar management, email handling, travel booking and document preparation. Many virtual assistants also support digital work such as social media management, newsletter production and website updates.
Some offer market research or basic bookkeeping. What clients value most is consistency, organisation and problem-solving. These skills remain difficult to automate fully, making virtual assistance a stable business option.
Read also: 7 CIO skills every business demands today

4. Micro-level and mid-size AI implementation

When people think of AI, they often picture large platforms like ChatGPT or Claude. However, smaller AI systems are becoming more common, especially for small and medium-sized businesses.

These tools can run on limited infrastructure and use business-specific data. Entrepreneurs who can install, manage and maintain such systems provide a needed service. Many small firms lack in-house expertise but still want to use AI.

Knowledge of mid-size AI tools such as Salesforce’s Einstein or Adobe Firefly can also create opportunities. Businesses pay for these platforms but may not know how to use their AI features fully. External specialists help bridge that gap.

5. AI-specific services

As AI remains new and loosely regulated, new roles are emerging. Two examples are “prompt engineer” and “AI ethicist”.

Prompt engineers design instructions that help AI systems deliver useful results. This work requires strong language skills and an understanding of how AI processes input.

AI ethicists focus on responsible AI use. They work with legal teams to address data use, privacy and copyright concerns. They also develop internal guidelines for staff.

AI ethics sits at the intersection of policy, accountability and law. Institutions such as Carnegie Mellon University, the University of Pennsylvania and MIT now offer training in this area, reflecting growing demand.