From Prediction To Agency: How AI Becomes A Workforce

Machines that wait for our prompts are giving way to systems that plan, decide, and act. We unpack the three waves of AI predictive, generative, and agentic and explore how the newest wave is redefining work by turning software into autonomous collaborators. From forecasting to content creation to coordinated action across tools and networks, we trace what changes, what stays, and what leaders must do next.

TLDR / At a Glance:

• defining predictive, generative, and agentic AI
• why agency matters for decisions and actions
• the tech stack enabling autonomous agents
• where agents fit in real workflows
• trust, ethics, and safety guardrails
• workforce shifts, reskilling, and new roles
• staged autonomy from observe to execute
• the move from apps to agents
• leadership playbook for the agentic age

I walk through the tech convergence making agency real: large language models for reasoning and dialogue, cloud scale for memory and orchestration, and machine learning for perception and optimisation. We look at how agents break down complex goals, call APIs, coordinate with other agents, and adapt to feedback, delivering speed and quality that manual handoffs cannot match. Along the way, we surface hard truths about trust, safety, and ethics why guardrails, auditability, and clear accountability are non-negotiable when machines act on your behalf.

The conversation turns practical with a leadership playbook: map processes by risk and value, start with narrow pilots, use staged autonomy from suggest to execute, and measure outcomes you care about latency, quality, cost, and satisfaction. 

We dig into workforce transformation as the value of memorising and repeating knowledge declines, and highlight emerging roles like agent wranglers, policy designers, evaluators, and workflow architects. 

Expect frank talk on displacement, reskilling, and how to build an agent registry, permissions, and incident response so your digital workforce behaves like a reliable product, not a risky experiment.

If you’re ready to move from “there’s an app for that” to “there’s an agent for that,” this deep dive will help you design, supervise, and scale agents responsibly. 

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Want to buy the full book or audio copy? This excellent book is now available globally on Amazon and Audible. 

Chapters

• 0:00 Three Waves Of AI
• 0:29 Generative AI’s Limits
• 0:50 Enter Agentic AI
• 1:21 Tech Convergence Powers Agency
• 2:06 Opportunities And Risks
• 2:24 Work Disruption Accelerates
• 2:59 From Apps To Agents
• 3:23 Agents Transform Organisations
• 4:03 Replacement And Leadership Challenges
• 4:28 Lead The Agentic Age

Transcript

SPEAKER_00: 0:00

Conclusion. The evolution of AI from prediction to agency. The landscape of artificial intelligence, AI, has undergone significant transformation, evolving through three distinct waves. The first wave, predictive AI, focused on analyzing historical data to forecast trends and support data-driven decision making. It enabled organizations to predict outcome but lacked the capability for creativity or autonomous action. The second wave, generative AI, introduced the ability to create content, allowing systems to engage in human-like conversations, generate images, and produce written content. Generative AI captivated industries with its creativity and versatility, but remained fundamentally reactive to human input. Now, we stand on the cusp of the third wave, Agentic AI. Unlike its predecessors, Agentic AI is not just about automation, it is about endowing machines with agency. It represents a fundamental shift in capability, enabling AI systems to act autonomously, make decisions, and adapt dynamically to complex environments. The convergence of advanced machine learning, cloud computing, and large language models drives this evolution forward. Together, these advancements empower AI systems to not only understand human talent, but also to independently execute tasks and collaborate with other agents to achieve goals. The third wave of AI ushers in a new era of possibilities, where machines can autonomously execute tasks, collaborate with other agents, and adapt to dynamic environments. While the opportunities are immense, so are the challenges. Organizations must navigate the complexities of trust, workforce transformation, and ethical deployment to realize the full potential of agentic AI. The time to prepare for this transformation is now. By embracing responsible adoption and fostering collaboration between humans and AI, organizations can harness the power of agentic AI to drive innovation, efficiency, and growth. The future of work is here, and it is powered by agents. The future of work is digital. That said, we live in a time of extraordinary promise. The future of work and digital labor has always faced disruption. For example, there are far less saddlers today than there are software engineers, but the pace at which organizations, their leaders, and workers face disruption is accelerating like never before. The value by which we were once measured, our ability to collect, synthesize, and repeat learning, is now being removed thanks to generative AI and large language models' ability to do exactly that. Agentic labor markets and models are a feature, not of the future, but of today. Gone are the days when there was an app for that. Now there is, or soon will be, an agent for that. Whilst many will claim that agentic AI is a revolution, I consider it a continued and accelerating evolution of workplaces that has been wrought by technology over the ages. That said, this evolution of digital workers, agents, or agentic AI will have a much more dramatic impact on work and society than any AI we have seen to date. The fact that Agentic AI does not just execute tasks, it thinks, plans, actions, reasons, and adapts. Agents collaborate with each other and people across computer systems and networks, reshaping organizations and transforming how work gets done. In many instances, AI agents will enhance workforce capabilities by autonomously problem solving and completing complex tasks. Yet, increasingly, rather than assisting humans, as agents get smarter, they will increasingly replace human labor. This will have challenges for workers and leaders everywhere. The challenge for leaders is in reimagining how their organizations operate in an agentic age. This change has huge implications for workers, governments, educators, and workers everywhere. It is for you to lead the change, not be a victim of it. I wish you every success in your agencai journey. Here in Gilmurray.