Article 6

Agentic AI & the Future of Work

Agentic AI is changing how companies think about jobs, leadership, workflows, and organisational design. The key idea is not that most roles will disappear, but that most roles will be reshaped as people begin working with AI agents across the business.

The future of work is becoming less about performing every task manually and more about directing systems, applying judgment, and redesigning how value is created. As companies invest in AI, the real challenge is no longer simply adopting tools. It is learning how to reorganise teams, skills, and workflows around them.

Core idea: Agentic AI is not just another tool. It is a shift in how organisations operate, how teams work, and how humans create value above and around intelligent systems.

1) The Great AI Paradox

  • High expectations: many companies believe AI will drive major transformation.
  • Heavy investment: organisations are spending with long-term confidence in AI’s potential.
  • Limited returns so far: many still say they are not yet seeing strong bottom-line impact.
  • The reason: technology on its own does not transform a business.
  • The real challenge: companies must redesign roles, workflows, and decision-making systems.
Meaning: buying AI is easy; becoming an AI-enabled organisation is much harder.

2) What Agentic AI Actually Means

Agentic AI goes beyond traditional generative AI. Instead of only producing text or responding to a single prompt, it can act across multiple steps, support broader goals, and help complete parts of an end-to-end process.

Generative AI
  • Writes, summarises, and answers prompts
  • Useful for isolated tasks
  • Supports content creation and quick assistance
Agentic AI
  • Acts across multiple steps
  • Supports goals and workflows
  • Can coordinate parts of a wider process
Example: instead of only writing a report, an agentic system could gather inputs, organise findings, identify patterns, and prepare a recommendation for human review.

3) Most Roles Will Be Reshaped, Not Removed

  • Job titles may stay similar, but daily responsibilities will change.
  • Execution becomes more assisted, while oversight becomes more human-led.
  • Employees will still be needed, but their value shifts toward judgment and coordination.
  • Leadership roles are also affected, not just junior or operational roles.
Big shift: the future role is less “doing every step manually” and more “guiding, checking, improving, and deciding.”

4) The Skills That Rise in Value

Still important
  • Technical execution
  • Process knowledge
  • Functional expertise
Becoming even more valuable
  • Strategic thinking
  • Systems thinking
  • Judgment and oversight
  • Problem-solving
  • People management
  • Operational leadership
Why: as agents handle more execution, humans become more responsible for direction, quality, governance, and final decisions.

5) Human in the Loop vs Human Above the Loop

Human in the loop
  • AI does part of a task
  • Human reviews or adds to it
  • The workflow moves back and forth
Human above the loop
  • Teams of agents complete most of the process
  • Human supervises the system
  • Judgment is applied at critical points
Meaning: the human role shifts upward from task performer to system supervisor and decision-maker.

6) Why Junior Talent Still Matters

One of the hardest questions for companies is how new employees will build experience if AI takes over some of the repetitive or operational work that used to train people early in their careers.

  • Companies still need future senior talent, so junior roles cannot simply disappear.
  • Learning pathways must change, because development can no longer rely only on manual grunt work.
  • New employees gain an advantage, because they start with advanced tools from day one.
  • Learning and development must become central, not something occasional or secondary.
Main question: how do companies help people build judgment faster in an AI-augmented environment?

7) Organisational Structures May Become More Fluid

  • Traditional hierarchies will not vanish overnight, because companies still need reporting lines and evaluation structures.
  • However, talent movement may become more flexible, with people moving across projects more easily.
  • Pods and squads may increase, especially around specific workflows or transformation goals.
  • Organisations that support fluid talent flows may gain a competitive advantage.
Practical view: the future may be less about fixed departments and more about people assembling around problems to solve.

8) Culture Becomes a Competitive Advantage

  • Curiosity matters, because so much of this future is still uncertain.
  • Continuous learning becomes essential, not optional.
  • Collaboration across levels and functions becomes more important.
  • Optimism without naivety is the right mindset.
  • Risk must be managed, but fear cannot become the default response.
Leadership principle: organisations need two-way doors — experiments that can be tested, adjusted, or reversed — rather than too many irreversible one-way decisions.

9) Real Value Comes from End-to-End Workflow Redesign

The biggest gains from agentic AI are unlikely to come from isolated point solutions. They are more likely to appear when companies redesign an entire workflow from start to finish.

  • End-to-end workflows often cut across many teams and handoffs.
  • These processes contain delays, rework, and complexity, which agents can help reduce.
  • Examples include insurance underwriting, legal review, onboarding, and R&D support.
  • The work requires system thinking, not just task automation.
Unlock: the biggest transformation happens when companies stop asking “How do we improve one task?” and start asking “How do we redesign the whole process?”

10) Workflow Redesign Needs All Levels of the Organisation

Why frontline people matter
  • They understand day-to-day friction
  • They know where processes break
  • They see what is realistic in practice
Why leaders matter
  • They shape governance and risk controls
  • They decide strategic priorities
  • They enable change across the organisation
Best model: redesigning work should involve people from different levels at the same time, because AI changes both execution and oversight.

11) The Leadership Question

Leaders cannot treat AI as a side tool while keeping everything else the same. They must rethink how they spend their own time, how they communicate change, and how they help teams move with confidence instead of fear.

Lead changemodel new behaviours
Build trustbalance speed and risk
Invest in learningmake development continuous
Reality: AI transformation is not just a technology rollout. It is a leadership challenge, a talent challenge, and a design challenge all at once.

12) Final Reflection

Agentic AI is pushing organisations to rethink assumptions that have shaped work for decades. The future will likely belong to companies that combine intelligent systems with human judgment, strong culture, flexible talent models, and redesigned workflows.

  • Jobs are being reshaped, not simply erased.
  • Skills are moving upward, toward strategy, judgment, and systems thinking.
  • Workflows matter more than isolated tools.
  • Continuous learning becomes a permanent requirement.
  • The future of work is organisational, not only technological.
Conclusion: the real opportunity is not just to use AI faster, but to redesign work more intelligently.