Helping leaders and teams integrate AI strategically, ethically and without overwhelm.

AI is reshaping how we work — but most leaders face two challenges:
❌ Uncertainty about where to start
❌ Fear of losing the human touch

I solve both.

With over 25 years of international experience in communications, sales, marketing and entrepreneurship, I help organisations and professionals adopt AI with confidence, clarity and measurable impact.

Through my Human-First AI methodology, I combine:

• Strategic AI adoption plans tailored to your industry and role
• Ethical frameworks embedded from day one
• Practical, no-code tools for immediate implementation
• Workflow-ready integration that boosts productivity without disruption

What I deliver:
• Corporate AI training and upskilling programs
• Workshops, masterclasses and keynotes
• One-to-one AI strategy sessions for leaders
• Ethical AI governance and policy guidance

Proven results:
• 30 percent average productivity boost after training
• 20 plus Fortune 500 and European companies served
• Recognised as one of LinkedIn’s Top 40 AI Influencers

In 2026 my work expands beyond Human-First AI.
I am integrating ethical AI adoption with the deeper leadership skills teams now need: clarity, courage, resilience and the discipline to stay human in a machine world.
This strengthens my corporate trainings and supports leaders navigating real change.

I believe AI should empower people, strengthen values and create lasting impact. My mission is to make AI usable, ethical and practical - for both business growth and human leadership.

📩 Let’s talk about how AI can drive your success:
https://calendly.com/aiclairefarwell/chat-with-ai-claire

⸻

If you want, I can refine the tone, shorten it, or make it more leadership-forward — but this version is the safest update for December.

The most important work I do doesn’t pay me.

This month marks 2 years of volunteering with 
Women in AI Spain.

When I started, it was just me in Barcelona.

One city. One person.

Doing everything alone.

Today, we’re around 35 volunteers across

Barcelona, Madrid, Zaragoza, Valencia, Alicante, Valladolid
& Gijon.

What keeps me saying yes isn’t a title.

It’s choosing to make time for something I believe in.

Creating space for women to
– speak honestly about AI
– ask the questions they’re not asking at work
– share fear, ambition, doubt, curiosity

This is about trust.

Community.

And using my experience in AI to help others feel 
more confident using their voice.

I’m deeply grateful for my teammates, especially 
Virginia Carreras and Teresa Villoslada Torres, 
and for the energy across every city team.

I couldn’t have imagined it growing like this.

But it proves something I care deeply about.

When women build together, momentum follows.

If this resonates:

Follow Women in AI Spain on LinkedIn.

See you at the next event perhaps?!

Claire Farwell

An enthusiastic global multilingual sales executive with more than 10 years of experience across several industries. From Edtech-Auto-Fashion-Toys-Entertainment-Real Estate. Specialized in both B2B & B2C & SAAS. From strategy-research-full sales cycle-account management-LSA. Have led small sales teams. Produced exclusive events with luxury brands. Lived in 20+ countries. Passionate, organized and loyal. 

Founder & CEO at AI Claire | Human-First AI & Leadership Strategist | Ethical AI Adoption | Keynote Speaker | Corporate Upskilling & Governance

AI training people on AI won’t fix this.

Most leaders are getting AI upskilling wrong.
Tis not because they don’t care.
Or because they’re behind.
Or even because they’re solving the wrong problem.

AI upskilling is treated as a skills gap.

Courses.
Certifications.
Tool training.
Tick the box.
Move on.

But that’s not what’s changing.

Work is changing.

Recent research from McKinsey makes this clear:
AI doesn’t replace skills.

It recombines them.
Human judgement + systems.
People + agents.
Decisions + automation.

That creates new questions leaders aren’t answering:
↳ Who decides when to trust AI?
↳ Who steps in when it’s wrong?
↳ Who is accountable when work is shared?

People aren’t confused about tools.
They are confused about their role.

This isn’t a training problem.
It’s a workforce design problem.

A leadership problem.

Where is AI creating role confusion in your organisation right now?

What do us ladies really get up to?

Women are scaling quietly with AI.

Not louder.

Not faster.

Smarter.

I’ve been reading about how women founders are using AI and digital tools to scale in 2026.

What stood out to me wasn’t the tech.

It was the intent.

AI is being used to:
↳ Buy back time
↳ Reduce overwhelm
↳ Build sustainable businesses
↳ Stay human while growing

❌ No silly hype.

❌ No “AI will save everything” nonsense.

Just practical choices.

✦ Tools that support thinking.
Not replace it.

✦ Systems that help women lead on their terms.
Not burn out trying to copy someone else’s playbook.

This is what Human-First AI actually looks like in the wild.

It’s why female-led adoption often works better.

✅ More questions.
✅ More reflection.
✅ Better judgement.

That’s not softness.
That’s strength.

Female-First Tuesday reminder:

AI doesn’t need louder leaders.
It needs more grounded ones.

If you’re building, scaling, or leading with AI right now,
you’re not behind.

You’re shaping what comes next.

Women in AI Spain is where these conversations continue.

We have some epic monthly WAI Cafe meetings coming up,
fab collaborations. 

So, come join me, Teresa Villoslada Torres, Virginia Carreras & our growing community here in Barcelona:)

Link to our community in the comment section.

Come on leaders!

Scaling AI doesn’t fail on technology.

It fails on leadership.

Pilots feel safe.
Small teams.
Clear use cases.
High oversight.

Then AI scales.
And behaviour changes.

Humans stop questioning.
Oversight becomes routine.

“Human in the loop” turns into rubber-stamping.
Bias doesn’t shout.
It scales quietly.

This is where ethical AI breaks.
Not because of bad intent.
But because of complacency disguised as efficiency.

Leaders often ask:
How do we govern AI?

The better question is:
How do we govern ourselves while using it?

Because AI doesn’t just scale productivity.
🫠 It scales judgement.
🫠 It scales bias.
🫠 It scales culture.

If values aren’t made visible inside workflows,
the machine will reflect whatever was left undefined.

That’s the real risk of enterprise GenAI.

If you’re scaling AI, start with leadership and judgement, 
not tools.

That’s the work I focus on.

AI governance isn’t a tech problem.
It’s a leadership one.

Most leaders ask:

How do we govern AI?

The better question is:
How do we govern ourselves while using it?
↳ Because AI doesn’t invent values
↳ It amplifies the ones already there

I’ve been reading a Fast Company piece on AI governance.

It confirms what I see in real teams.
↳ Clear tools
↳ Smart people
↳ Messy decisions

Why?

Because values were never made explicit.
If leadership isn’t aligned,

AI just scales confusion faster.

This is also why upskilling fails.
↳ Training changes skills
↳ Workflows stay the same
↳ Behaviour doesn’t shift

Human-First AI leadership means:
☑︎ Deciding what AI should never do
☑︎ Defining where humans stay accountable
☑︎ Designing workflows before deploying tools

Governance isn’t a PDF.
It’s what people do when no one is watching.

And trust is built there.
Not in the model.

AI Upskilling

You missed more than you think this week.

AI moved fast. Power moved faster.

Same pattern. Bigger stakes.

🔥 Meta locks in nuclear power
6GW deals to fuel AI expansion
Infrastructure is now a strategic weapon

🔥 Google pushes personal AI
Gemini shifts toward personal intelligence
Convenience grows as consent gets blurry

🔥 Microsoft scales agents and data centres
Slackbots act, Copilots sell, compute explodes
Governance struggles to keep up

🔥 NPR reports schools under pressure
AI floods classrooms without guardrails
Education becomes the next fault line

🔥 BBC tracks deepfake backlash
Countries block tools over abuse risks
Ethics turns into enforcement

Different sectors.

Same signal.

AI isn’t failing on capability.

It’s failing on responsibility.

Don’t miss my weekly newsletter.
I read the news you don’t have time for.

Welcome to a new week, and of course a new update on all the news from last week. I am head down preparing for workshops in the UK and locally + a few

Open article: Google, Meta and Microsoft scale AI as ethics catch up by Claire Farwell • 14 min read

Google, Meta and Microsoft scale AI as ethics catch up

You missed more than you think this week!

AI got closer.

Leadership got quieter.

Same pattern.

Higher stakes.

🔥 Apple rebuilds Siri
Deeper assistant. More context. More agency.
Control shifts by default, not consent.

🔥 OpenAI hints at physical AI
From screens to environments
Surveillance and consent enter daily life.

🔥 xAI tests AI employees
Agents mimic human roles
Trust breaks when accountability is unclear.

🔥 Waymo expands robotaxis
Autonomy goes mainstream
Safety moves from theory to streets.

🔥 Harvard Business Review flags AI anxiety
Employees feel it before leaders admit it
Fear fills the governance gap.

Different industries.

Same warning.
AI isn’t stalling on innovation.

It’s stalling on ownership.

When systems act,
someone still has to answer.

That’s the real leadership test.

Subscribe to my weekly newsletter.
I track the signals before they become consequences.

I’ve had to rethink what progress means.

I used to think it was about
↳ what’s happening in AI,
↳ what’s new,
↳ what I should be sharing.

And yes, I’ll keep my newsletter.

I’ll keep teaching.

But the more AI accelerates,
the more I’ve felt the need to slow down.

Working in ethical AI
and talking to teams about what AI really means
kept bringing me back to the same place.

The person.
✦ We’re all different.
✦ We all have different values.
✦ Different fears.
✦ Different ways of making sense of things.

And no amount of transparency or governance works
if we don’t stop and check in with ourselves first.

Now feels like the moment to do that.

Before we get lost in the rush.

Before we hand everything over to the machine
without really thinking.

Some of the progress I’ve made this year
no one can see.

2025 has been a hard year in many ways.

A year of change.

And it made me stop and ask questions
I hadn’t been asking enough.

- Do I want this?
- Is this helping me grow?
- Does this feel right?

I realised I’d been rushing.

So I stopped.

And there was a moment where I knew

I was exactly where I needed to be.

Not because it looked impressive.

But because I felt happy.

And I don’t think you can teach,
or communicate,
or lead responsibly in this AI era
unless you understand what makes you happy first.

Lately, progress for me has meant:
☑︎ Being honest with myself
☑︎ Taking time
☑︎ Getting clear

Because if I’m going to stand in a room
and talk about AI, leadership, and the future,
it has to come from that place.

Female First matters to me
because community matters.

That’s why I’m part of Women in AI Spain.
Not as a logo.
Not as a title.
But as a place.

A place where women can:
- learn about AI without pretending
- ask questions without judgement
- admit they’re curious, confused, or cautious
- build confidence through understanding
- learn from each other

I’ve seen this again and again.

At events last year with:
Google
HP
ADE Vallès
Zurich Technology Delivery Center Barcelona
IA Hub Barcelona
Juno Projects
Barcelona & Madrid Health Hub

-corporate leaders
-entrepreneurs
-women changing careers
-women deep in tech

Different roles.
Different backgrounds.
Same need.
➤ To feel safe learning.
➤ To feel less alone.
➤ To learn together.

There is strength in numbers.
Always has been.

That’s also why I’m so excited about our team in Barcelona.
Together with Teresa Villoslada Torres and Virginia Carreras,
we’re building spaces for women to:

Understand AI clearly
Build skills responsibly
Connect without pressure

We’ll be running more events in Barcelona
and sharing them here soon.

If you’re a woman looking for:
community
education
real conversations about AI

Or if you’re part of a women’s association or foundation
and want to explore collaboration, 
reach out.

And yes, men are welcome too.
This is about better leadership, not exclusion.
Every woman deserves a place to learn,
to ask,
and to grow.

Follow Women in AI Spain-link in the comments

Or message me if you have questions.

Most AI training fails before it starts.

Not because people are incapable.

But because organisations start in the wrong place.

The first mistake:

↳ AI gets handed to IT.
↳ A tool is rolled out.
↳ Access is switched on.
 & people are expected to “just use it”.

Non-technical teams are confused.
Technical teams are frustrated.

No one owns the outcome.

The second mistake:
↳ Too many tools
↳ Too fast
↳ No framework
↳ No pilot
↳ No feedback loop

AI training is not a tool drop.

It is a workflow decision.

In 2025, this showed up most clearly
in content workflows.

What actually worked was simple.

↳ One clear use case.
↳ One or two tools.
↳ One team.
↳ One owner.

- With space to test.
- With feedback.
- With communication before scale.

Content worked because it made problems visible.

↳ Ideas captured in one place.
↳ Drafted in their own voice.
↳ Sources checked.
↳ Outputs reviewed.
↳ Not more output.
↳ Better judgement.

This is where my C.R.E.A.T.E. framework fits:
✦ Clarity
✦ Responsibility
✦ Equity
✦ Alignment
✦ Transparency
✦ Evaluation

Not as policy.

Inside the workflow.
- Before you publish.
- Before you automate.
- Before you scale.

If you only fix one thing before scaling AI,
fix your values.

By values, I mean things like:
 – Where humans must stay in the loop
 – What we will not automate
 – Who is accountable for AI decisions
 – What “good enough” is not acceptable

Because workflows don’t fail on tools.

They fail on unclear leadership.

If you want a practical way to apply this,
my C.R.E.A.T.E. workflow shows how to embed
Human-First decisions into daily AI use.

DM me and I will send it to you!

You can’t upskill people
inside broken workflows.

The World Economic Forum just made this clear.

The future of work isn’t one new AI skill.

It’s a mix of:
✦ Technical skills
✦ Human judgement
✦ The ability to apply both inside real work

That’s where most AI training fails.

People learn the tools.

Then return to messy processes
and unclear decisions.

So nothing sticks.

Skills don’t fail.

Workflows do.

When learning isn’t built into daily work,
confidence drops.

Use fades.
Judgement weakens.

What works is simpler.

✅ Fix the workflow first.
✅ Then train AI inside it.

AI doesn’t replace skills.

It exposes how work is really done.

If you’re planning AI upskilling this year,
start with the work.

That’s Human-First AI.

AI keeps changing.

Learning has to as well.

I recently completed another programme
in data and technology with ISDI

Not because I want to become technical-imagine!

And not because I want to teach data
for the sake of it.

I did it because data matters.

I say this all the time when I teach AI,
but I wanted to go deeper for myself.

✦ How data is structured.
✦ How it is orchestrated.
✦ Why it has value.
✦ What we actually do with it.

As a non-technical AI educator,
this matters more than pretending
to know everything.

I’m always a student.

Over the summer,
I completed a digital leadership programme
for women.

Before that, others.

And now this.

Learning doesn’t make me uncomfortable.

It gives me confidence.

The more I learn,
the more clearly I see the whole picture.

And the better I can teach.

AI is not one thing.
➤ Systems.
➤ People.
➤ Ethics
➤ Data.
➤ Culture.
➤ Decisions.

Studying data properly
reinforced something simple
about leadership.

You don’t need to become technical.

But you do need enough understanding to:
ask better questions,
have better conversations,
lead with judgement.

Data is not as complicated
as people think.

Anything becomes clearer
when you take it step by step.

That matters for leaders.

Especially now.

Human-First leadership means
being willing to keep learning.

☑︎  Even when time is tight.
☑︎  Even when there is fear.
☑︎  Even when it happens
in small moments.

Those small steps
spark everything else.

DATA & TECH

What makes you think you don’t have an AI ethics problem?

Most leaders say they care about responsible AI.

Very few can explain what that actually means in practice.

❌ Ethical AI isn’t a policy.

❌ It’s not a slide.

❌ And it’s definitely not something you “add later”.

The real risk isn’t bad intent.

It’s good intent with no self-governance.

I see the same pattern again and again:

❌ Teams focus on speed and innovation

❌ Ethics gets reduced to compliance

❌ Humans assume the system will behave

That’s how trust erodes quietly.

Human-First AI leadership starts somewhere else.

Not with the model.

With the leader.

If you can’t answer these questions, you’re exposed:

↳ Where does human judgment step in?

↳ Who is accountable when AI influences decisions?

↳ What values are actually being enforced day to day?

This isn’t about slowing AI down.

It’s about being fit to lead while using it.

AI doesn’t remove responsibility.

It concentrates it.

2 weeks off?!

How dare I!

I am back, and here is the latest & greatest news in AI!

🔥 Google puts AI into classrooms
 Lessons turn into audio and AI support
 Education shifts from writing to reasoning

🔥 Grok scandal triggers policy backlash
 Fake images target women and girls
 AI harm forces faster regulation

🔥 Amazon pushes Alexa everywhere
 Always-on assistants expand quietly
 Consent becomes the real battleground

🔥 Courts test AI and pull back
 Legal chatbots fail under pressure
 Accuracy beats speed in justice systems

🔥 Women lead the AI ethics response
 Feminist AI movements grow globally
 Governance now comes bottom-up

This week showed one thing clearly.

AI progress without trust does not scale.

Don’t miss my weekly newsletter.

I read the news you don’t have time for.

Your AI pilot is lying to you.

Here’s the problem.

- Teams get trained on AI.

- Tools get approved.

- Pilots look promising.

But the way work actually happens
stays exactly the same.

↳  Same meetings.
↳  Same pressure.
↳  Same copy-paste habits.

Now the uncomfortable part.

✦ At scale, people stop checking.

✦ Responsibility gets fuzzy.

✦ Ethics becomes a slide deck, not a behaviour.

AI starts shaping decisions
without anyone clearly owning them.

Not because people are careless.

Because the workflow never changed.

That’s why so many AI initiatives stall after early success.

Here’s the fix.

Stop treating AI as a training problem.

It’s a workflow decision.

Ethical AI only works when it’s built into:

✅  how decisions are made
✅  where humans must pause
✅  who is accountable
✅  when AI supports vs decides

Upskilling sticks when people learn inside real work, not classrooms.

If you want AI to scale responsibly,
you have to redesign how work flows first.

Because AI doesn’t fail on tools.

It fails on unclear leadership.

your ai pilot didnt fail 

Does anyone actually hear you?

That question came up for me recently
during an interview with Gentlemen’s Collective.

We talked about modelling.

Leaving home at 16.

Living in 20+ countries.

Being seen everywhere.

And yet…

There were years when I was visible
but not really heard.

Expected to show up.
Perform.
Look the part.
Not to speak.

The real shift in my life
wasn’t a career change.

It was moving from being watched
to being listened to.

From fitting a role
to using my voice.

That’s what reinvention actually is.

And it’s why this matters so much in an AI era.
Because technology amplifies whatever is already there.

If you don’t know WHO you are,
WHAT you value,
WHAT you stand for,
the machine will fill in the gaps.


https://lnkd.in/eTAfSefZ

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