What recognises a Vector Leader™ - Identifying summary
Vector Leaders are able to create direction (clear aim), magnitude (material force on the metric), and pull (others align to the pattern). Sustains it until it becomes the default. Uses AI to widen options, improve decision quality, and compress the path from analysis to action. Builds visible patterns of work that peers copy, so personal practice becomes the organisational default.
Defining characteristics of how Vector Leaders work with AI
Decisions
They use AI to widen options, expose constraints, quantify trade-offs, check second-order effects, and capture a rationale before calling it.
Strategy
They simulate scenarios and counter-moves with AI, red-team assumptions, and compare against historical analogues before taking strategic decisions and committing resources.
Research
They brief fast with AI, pulling key facts, players, timelines, and open questions from internal materials and permitted external sources, with citations. They also use AI to validate their own research and analysis, checking sources, testing logic, and reducing fabricated outputs.
Preparation
They compress prep with AI, extract must-knows from long decks and threads, rehearse Q&A, surface likely objections with responses, and shape agendas that land decisions in-room.
Counsel
They appoint virtual advisory councils or mentors in AI to fit the situation, and use them as thought partners or for rehearsal. They may keep different councils for sales, personal leadership, the executive team, or any domain, and can simulate full board meetings, committee reviews, or customer panels, either as preparation or during live work.
Collaboration
They weave AI into team workflows. Shared AI workspaces and co-authored docs, shared note-taking and live meeting assistants to capture decisions and actions, shareable chats and threads others can inspect and extend, councils used live in leadership sessions to unblock decisions, and lightweight knowledge hubs that keep context current across functions.
Reliable use and judgment
They know when and how to use AI, pick fit-for-purpose tools, set clear boundaries, cross-check claims with sources, run second opinions, and bring the right humans into the loop for material calls. They treat AI outputs as hypotheses to be tested, not facts, and correct course quickly when signals conflict.
Personal cadence and velocity
They use AI to tighten the loop from idea to analysis to decision to action. Preparation compresses, follow-ups generate quickly, quality rises, and momentum holds across parallel workstreams without losing context.
What it means to be a Vector Leader
1
Right decision, sooner.
They surface more options, identify the right trade-offs, assess, test and validate them, understand the impact, and land the call faster with fewer reversals. The clarity reduces ‘let’s revisit next week’ meetings.
2
Information on tap.
They get to the key facts, players, and risks fast, with sources linked and figures aligned for like-for-like comparison, ready to show when challenged.
3
Wider set of options assessed, clearer thinking.
They see non-obvious routes, spot second-order effects, and kill weak paths early.
4
Preparation becomes faster and higher quality.
They use AI to simulate the people they will meet, rehearse what they will say, anticipate counterpoints and questions, refine responses and materials, and shape agendas that land decisions in-room. Hence, they walk in ready, with likely objections, crisp asks, and decision criteria already framed.
5
Meetings convert to action.
They make the decision in the room, record the choice and rationale, and ensure the right owners are responsible for the right tasks with committed timelines. AI generates high-quality summaries quickly and supports progress tracking against dates until done.
6
Execution speeds up.
Next steps, drafts, and follow-ups generate in minutes, handoffs tighten, queues shrink.
7
Friction with important stakeholders drops.
Evidence and traceability are delivered quickly and to a high standard, so approvals arrive faster.
8
Collaboration becomes more effective.
The leadership team co-thinks with AI, shares and extends individual thinking with AI, uses shared workspaces and assistants; alignment lands faster with higher precision, often by multiples, and collective velocity increases.
Why is this an important part of succeeding with AI adoption and transformation?
Leaders who attempt to drive AI adoption without first embodying the traits of a vector leader end up arguing from theory, not practice. Colleagues follow working patterns they can see, not slides.
Without the leader's own AI augmented habits, such as faster briefs, sharper decisions, better preparation, and quicker, tighter meetings, the leader cannot model the behaviour they expect others to adopt. Others will not trust what they cannot evidence, and will not prioritise what they cannot specify. Momentum slips.
Such leaders tend to drift into vendor-led tool choices, pilot sprawl, and meetings that end in 'let's revisit', while credibility bleeds away.
The result is time spent pushing uphill against politics, governance, and fatigue, usually ending with the transformation stalling right where it should have started.
Theory without Practice
Leaders argue from slides and unsubstantiated conviction, not experience
Credibility Erosion
Vendor-led choices, pilot sprawl, endless meetings
Transformation Stalls
Politics, governance, and fatigue take over