In the AI Era, traditional "task monopolies" held by managers and specialists are rapidly dissolving. Sophisticated machine intelligence increasingly automates routine operations, information processing, and compliance workflows. With repetitive routines automated, the primary value-add of human professionals shifts from routine administration to orchestrating "the possible"—specifically, finding, selecting, and selectively exploiting promising, value-creating opportunities. Concurrently, decision velocity has collapsed, requiring managers to make immediate, highly informed, and courageous "judgment calls" under intense pressure.

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However, in this hyper-competitive landscape, striving for maximum agility everywhere is a dangerous trap. As research into corporate downfalls (such as Nokia's historic loss of dominance) shows, unconditional, "one-size-fits-all" agility can create a chaotic, near-hysterical corporate climate, draining energy and eroding focus. Agility is rarely cost-free and can be highly disruptive.

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Therefore, modern organisations must cultivate Requisite Agility—meaning they adapt "not too much, not too little, of the right type, in the right place, delivering wanted deliverables". Requisite agility ensures that flexibility is balanced with organisational order, strategic alignment, and financial prudence. By focusing human efforts on areas requiring ethical judgment, empathy, and creative synthesis, organisations can build a sustainable, highly productive "socio-technical" partnership with non-human AI actors.

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The Seven Steps to Becoming Requisitely Agile (summarised from the book 'Exploiting Agility for Advantage' by David L. Francis, published by De Gruyter)

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To transition from a vague strategic intention to a functional, hard-to-copy organisational capability, the Exploiting Agility for Advantage (EAfA) framework outlines a structured, seven-step developmental journey:

1. Orientating: The top management team (TMT) and sub-units study academic and practitioner research to establish a shared, evidence-based conceptual platform, ensuring everyone understands what true agility is and is not.

2. Predicting: Utilising foresight techniques to analyse emerging contextual change drivers (such as advanced AI), helping the team define future agility requirements over various time horizons.

3. Diagnosing: Conducting a rigorous audit of the organization's current capabilities to evaluate the balance of driving forces and identify hidden "agility blockages" or systemic bottlenecks.

4. Envisioning: Performing a collaborative thought experiment to co-create a clear, shared Agility Ambition statement, defining exactly what will—and will not—be happening when the unit operates with requisite agility.

5. Scoping: Translating the Agility Ambition into prioritised time horizons, specifying what local agility is needed urgently (1-year), in the foreseeable future (3-year), and in the middle-distant future (7-year).

6. Customising: Selecting and configuring the most appropriate of the eight specialized agility types (e.g., Top-Down, Socio-Technical, Skunk Works, or Granular Agility) to match the specific operational profile of each sub-unit, rejecting any rigid "one-size-fits-all" design.

7. Delivering: Developing a concrete capacity-building change agenda, selecting an appropriate theory of change, and setting "Mission Essential Tasks" with clear metrics to guide real-world execution