Why Work Architecture starts with today's tasks, not future capabilities

In a recent session, an important question came up:

Why focus on analyzing today's jobs when AI will change the jobs of the future? Should we focus on the capabilities and jobs we will need instead?

My short answer: No. Tasks come first.

The longer answer is what we will cover in this newsletter.

Predicting future capabilities matters. But jumping ahead without understanding today's work is a missed opportunity. The tasks that make up each job matter most. The smartest people once guided us toward roles that won't survive rapid technological advancement. We poured time, energy, and money into building capabilities for jobs that no longer exist.

Before we prepare for imaginary future jobs, we need to assess the impact on jobs we do today. Only then will we see what future capabilities truly matter.

The foundation of our workforce lies in present tasks. AI will support work by automating the repetitive. It won't replace human ingenuity. To predict the future, we first need to understand the now.

AI capability is compounding. Work visibility is not.

Tasks first, jobs second

Simply analyzing jobs won't give us the full picture. AI reshapes industries. But remember: AI isn't replacing jobs. It's automating specific tasks. So how do we prepare?

AI automates tasks, not capabilities. Tasks form the core of every role. To create a future-ready workforce, we first need to understand today's tasks. Once we have that understanding, we:

• Identify tasks suited for AI automation. (It's rarely the whole job. Just certain tasks.)
• Determine the capabilities needed to complete those tasks.
• Build a roadmap for moving people into more meaningful, higher-value work.

This reinvention of work starts with understanding tasks. That's where AI steps in. People step up to take on more impactful, human-centered roles.

Capabilities are shaped by tasks and defined by the future

How do we predict the capabilities of the future? It takes more than analyzing today's roles. We need to deeply understand how tasks will evolve. Technology, customer needs, and regulations all shift.

Here's the key takeaway. You can't predict future capabilities without understanding today's tasks. "Future-proofing" is easy to talk about. The reality is more nuanced. Focus on what tasks people do now. Consider how AI supports them by automating some tasks. Free people up for creative, strategic, and uniquely human work.

Before we think about tomorrow's jobs, start at the task level. Understanding today's tasks builds a workforce ready to adapt, grow, and thrive.

Every enterprise is deploying AI. Almost none can see the work they're deploying it into.

Augmented workforces are the future. AI workers included.

Workforce planning can't focus on humans alone.

AI workers are becoming a key part of the operating model. They take over repetitive, task-based work. Humans focus on higher-value contributions. Companies need to rethink their strategies. They must integrate AI effectively.

The future isn't about replacing people. It's about creating a seamless partnership. Human creativity and AI efficiency, working together. Companies that succeed will prepare their human workforce to be AI-ready. The key is understanding which tasks to automate. And where to move people into roles that create more value.

From Job Architecture to Work Architecture.

Key takeaways

• Start with today's tasks. Understand the tasks people do now. This builds the foundation for the future.
• Identify where AI applies. Pinpoint which repetitive tasks AI automates. Free people for more valuable work.
• Invest in capability-building. Create a roadmap. Prepare your workforce for roles that require creativity, strategy, and human insight. These are the tasks AI can't replace.

This question opened an important discussion. You can't predict future capabilities without understanding today's tasks. By getting the foundation right, you build a future-ready, hybrid workforce. Humans and AI work together seamlessly.

Book a demo.

Siobhan 💜