Rethinking Roles When AI Joins The Team

The way we work is changing fast. With AI and generative technologies advancing rapidly, traditional structures, processes, and hierarchies are giving way to a new approach where AI agents team up with a flexible, generalist workforce. But it’s not just about using new tools. It’s about rethinking how we organize work, manage tasks, and run teams. By understanding these shifts, leaders can start transforming their workforce to get the most leverage from AI and unlock new opportunities for upskilling their existing workforce and automate workflows.

• Figure out which tasks AI can help with - Don't think about replacing whole jobs. Just look at the everyday stuff your team does and spot what AI could make easier
• Teach people to talk to AI properly - It's weird, but knowing how to ask AI the right questions is becoming more valuable than all that knowledge people used to spend years building up
• Look for flexible people when hiring - Those jack-of-all-trades types who can work with AI across different areas are gold now, rather than super-specialised experts
• Rethink those starter jobs - Instead of having juniors do all the grunt work, have them check and improve what AI produces - it's actually more interesting for them
• Start with just one thing - Pick a single workflow where AI makes obvious sense rather than trying to AI-ify your entire company overnight
• Create some basic rules for humans and AI working together - You need a system where people and AI each do what they're best at‍
• Set up some AI training - Your current team needs to learn how to use these tools effectively in their everyday work

Generative AI is collapsing traditional role boundaries by enabling professionals to expand their skillsets exponentially through thoughtful crafting of prompts. By formulating precise questions and instructions, a single individual can manage responsibilities that previously required multiple experts. Skilled inquiry allows them to guide AI systems toward valuable insights, enabling them to address tasks beyond their original role. As a result, professionals who excel at defining problems and posing targeted questions often wear several hats within an organisation.

Consultants using Generative AI achieved 86% of expert-level coding outputs despite no prior programming experience, compressing years of skill development into real-time execution - BCG, 2024

As AI agents become part of daily operations, human-AI collaboration is becoming a key consideration for business leaders. The focus isn’t on identifying roles or jobs that can be entirely replaced but on understanding which specific tasks within each person’s daily workflow can be augmented or automated using AI. By mapping out existing workflows and pinpointing tasks that AI can handle, leaders can streamline processes, free up their teams for more strategic work, and build a more agile organisation. This approach allows human expertise and AI capabilities to complement each other, driving smarter ways of working.

At Heyra, we expect generative AI to influence hiring by encouraging organizations to prioritize individuals with broad abilities rather than focusing solely on narrow skill sets. As AI tools gradually take over tasks such as coding, data analysis, and content creation, adaptable generalists are likely to assume roles that previously required years of intensive training. By incorporating AI into daily work, these individuals can learn on the job and transition between different projects more easily.

Surface-level knowledge has long been overlooked, but this may be about to change. We anticipate that recruiters will place more value on people who show flexibility and feel confident collaborating with AI systems. In our view, this approach involves hiring individuals who blend knowledge from multiple fields and adapt to changing requirements. Rather than staffing every specialized role with a dedicated expert, organizations could discover that broader talents can tackle duties once reserved for specialists.

“Leaders may also find that an unlikely person inside
their organization can fill an open role” - BCG, 2024

We suspect that this way of working may also offer new paths for career growth. Generalists who are comfortable with generative AI could become essential in teams that combine human and AI skills. They can coordinate tasks efficiently and make the most of diverse resources, helping organizations remain flexible and competitive in a job market that continues to evolve.

Companies around the world are rethinking how work gets done as AI tools move into areas once handled exclusively by specialists. Rather than expecting AI to replace entire roles, the focus is on how humans and machines can complement each other.

Entry-level positions are also on the cusp of a significant transformation. Rather than being limited to routine tasks or time-consuming research, these roles are set to shift toward reviewing and refining outputs produced by AI tools, a change highlighted in a recent Capgemini report. As AI takes over many initial processes, new hires will increasingly focus on quality assurance, critical analysis, and ensuring that AI-generated work meets high standards. This evolution redefines the starting point of a career and lays the groundwork for faster progression into specialized functions, as early-career professionals develop the skills needed to work effectively alongside AI.

If you’re early in the process of upskilling your team in using AI, the highest-impact, lowest-effort task to focus on is teaching your workforce how to ask the right questions. By helping your team become skilled wordsmiths, their AI-generated output will improve significantly and reduce the time spent getting the AI to perform the desired task or generate the required response.

Knowledge was once the most important asset in many fields, but now it is more about asking the right questions. If you can figure out exactly what you need and phrase your request clearly for an AI tool, you can solve problems and discover solutions faster. This ability to think critically and communicate needs in writing is becoming a superpower. 

So, how do you “get good at prompting”? There is no shortage of articles on what to include in your prompt, and many of them have merit. From our perspective, you don’t need to overcomplicate it. Here’s the framework we use for the anatomy of a prompt.

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This framework was not created by Heyra; it is widely used and has been shared by people like Greg Brockman, Co-founder of OpenAI. To keep it brief, the first part involves clearly stating your goal. This can include the task you want the AI to perform and, perhaps more importantly, the objective behind your prompt. It’s not just about asking a question; it’s about explaining exactly what you need and why you need it. Every prompt you create should begin with a clear task and a well-defined objective. This is the foundation you should spend the most time considering before writing and expanding your prompt. We will not spend any more time on this framework in this article, but if you’re unfamiliar with it, it is worth keeping in mind when using generative AI.

In the coming years, workforce and workflow transformation will reshape the way we work as old structures, processes, and hierarchies break down to make room for a new model. AI agents will emerge as key team members, taking on routine tasks, while a flexible, generalist workforce drives innovation and adapts quickly to change. However, it’s important not to approach AI as a replacement for entire roles or departments. Instead, start small by identifying a single use case or workflow where AI can add value and build from there. As you scale, ensure that every step aligns with the workflows of your existing workforce.

1. Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
2. GenAI Doesn’t Just Increase Productivity. It Expands Capabilities.
3. Five Must-Haves for Effective AI Upskilling | BCG
4. Gen AI at work

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