What (AI)
Time To Be
Alive.

Whether you believe this is the dawn of a new renaissance or the beginning of something more troubling, we are living through one of the biggest evolutionary leaps of our time.

01 — THE LEAP

Six years. A different world.

The technology did not inch forward. It accelerated.

The change is easiest to understand not in benchmarks, but in what suddenly became possible.

THEN · GPT-3

Human

How many eyes does my foot have?

GPT-3

Your foot has two eyes.
Basic questions. Confidently wrong.
THEN · IMAGE GENERATIONAn early AI image of Will Smith eating spaghetti with obvious biological and physical errorsBasic biology and physics broke.
NOW · MINUTESInteractive 3D product experience exploring a vehicle componentImmersive product experiences, generated in minutes.Customers can break down and understand every detail.

But the most consequential shift is not only what AI can do.

It is how our role changes as we hand it more of the journey between a prompt and an outcome.

02 — OUR CHANGING ROLE

Three eras. Each one gives AI more agency.

01

Era 01 · Execution

Do this

We gave AI a specific task. It executed — while we held the thinking and the decisions.

01
YOUSpecific task
AI
Output

Draft this copy

Summarise this document

Analyse this data

02

Era 02 · Judgement

Solve this

We brought AI a problem. It helped explore and recommend — while we still decided where to go.

02
PROBLEM
Option AOption BOption C
YOU DECIDE

Explore the options

Evaluate the trade-offs

Recommend a direction

03

Era 03 · Goals

Achieve this

Now we give AI an outcome. The choices between intention and result are increasingly its to make.

03
YOUR GOAL
PlanToolsBuildCheckAdapt
OUTCOME

Choose the tools

Sequence the work

Make decisions in-between

THE IMPLICATION OF ERA 03

As AI increasingly makes decisions on our behalf…

The intelligence it uses to make those decisions becomes critical.

03 — THE MISSING INTELLIGENCE

AI brings one kind of intelligence. We bring the other.

Model intelligence is reasoning, general knowledge and pattern recognition. Organizational intelligence is your data, audiences, context, experience, KPIs and institutional memory.

What the model brings

Model intelligence

Reasoning · General knowledge · Pattern recognition

MODELORGANIZATION

What your organization brings

Organizational intelligence

Data · Context · Experience · KPIs · Institutional knowledge

ORGANIZATIONAL CONTEXT28%
DECISION QUALITYPoor

The model moves quickly — without enough of your organization to know where it should go.

Move the control. Change the intelligence behind the decision.

Better AI cannot compensate for bad intelligence.

Powerful models×
Fragmented context=

Poor decisions,
faster.

No matter how advanced the model becomes, it cannot compensate for the intelligence it was never given.

So the question you need to ask yourself as a leader is…

NOT

Are my teams using AI?

BUT

Have I fostered a culture of data and intelligence to maximize its impact?

04 — THREE LEADERSHIP CHOICES

The real advantage is a culture of data and intelligence.

Not a slogan. A system shaped by what leaders measure, what they connect and what they give room to grow.

01

Responsibility

Change what we measure.

Teams naturally optimize for what leaders measure. If the message is simply ‘use AI to save time’, efficiency becomes the ceiling. Measure whether AI improved the decision, deepened stakeholder understanding or raised the value of the work.

EFFICIENCYDo more of the same work, faster.
  • Hours saved
  • Tasks automated
  • Volume produced
IMPACTRaise the business value of the work.
  • Better decisions
  • Deeper stakeholder understanding
  • More ideas tested
  • Greater trust created

Don’t ask what AI helped teams do faster. Ask what it helped them do better.

02

Integration

Let intelligence travel.

Integration is not putting disciplines in the same meeting. It is making what one team learns available to the next — so every decision starts smarter than the last.

THE OPPORTUNITYMove from reporting what happened to learning what worked — and use that intelligence in the next decision.
WHAT HAPPENED?WHAT WORKED, FOR WHOM?NEXT DECISION
TRADITIONAL MEDIA RELATIONSOften tracks output.
Activity
Contacts · Pitches · Conversations
Output
Coverage · Reach · Share of voice
Result
Sentiment · Message pull-through
EMAIL MARKETINGBuilds a behavioral loop.
Attention
Opened · Ignored
Engagement
Clicked · Didn’t click
Action
Converted · Dropped off

The takeaway: every discipline has intelligence the others can use.

03

Curiosity

Create permission to explore.

AI can give excellent answers, but the questions now matter more. Give teams the time, space and mental safety to test a hypothesis, be wrong, and turn every experiment into intelligence for the next decision.

AI can find patterns.Curiosity decides where we look.
ASK

What haven’t we thought to ask?

EXPERIMENT

What could we test and validate?

LEARN

What did we discover and can iterate from?

Time, space and mental safety turn every result — including failure — into intelligence for the next decision.

05 — ASK YOURSELF

Three questions.
Your answers shape the outcome.

01

Am I measuring impact, not just efficiency?

Responsibility
02

Am I breaking the silos that trap intelligence?

Integration
03

Am I creating the conditions to learn?

Curiosity