This past summer we sat across from a C-suite executive who asked a question that stopped me in my tracks:

“Should we just hire a new computer science grad and have them build us a bunch of AI agents?”

Our reaction?

A healthy dose of horror.

Let’s be honest: You wouldn’t hire a fresh-out-of-school graduate to be your Chief Financial Officer, would you?

You’re looking for experience, judgment, and a deep understanding of financial principles.

The same logic applies to AI and transformation.

AI isn’t just about coding; it’s about strategy, ethics, data governance, and business alignment first and technology second.

It’s about understanding the “why” behind the technology, not just the “how”.

Entrusting your entire AI strategy to a new hire, no matter how talented, is like handing the keys to the kingdom to someone who hasn’t even driven a car.

You will end up being technology focused and not value and outcome focused.

This is a big difference.

This isn’t about dismissing the skills of new grads;

it’s about recognizing the complexity of a successful organizational AI strategy.

It’s about building a team with diverse expertise and experience –

and giving them the strategic framework to succeed.

If your AI strategy is based on a new grad call us in 2 years to help you rebuild and course correct your failed AI transformation.

#AIStrategy #Leadership #ExecutiveThinking #DigitalTransformation #DearCEO #CEO #AI

For the past week, I’m sure many of you have seen a series of posts challenging conventional wisdom around AI, data transformation, and digital adoption.

They weren’t meant to be provocative for the sake of it – they’re a reflection of a growing concern I see time and time again when working with organizations at the executive level.

The uncomfortable truth is this – we have a glowing issue brewing in boardrooms and executive suites worldwide but mainly in Canada.

We’re rushing headlong into an AI-driven future without fully grasping the profound implications for our businesses, our people, and our society.

The enthusiasm is there.

The investments are partially flowing.

But the understanding?

That’s often lagging far behind.

Here’s what we are seeing:

A Misunderstanding of the Risks
We’re focused on the potential benefits of AI (efficiency, personalization, innovation) while underestimating the very real risks – algorithmic bias, data manipulation, erosion of trust, and the potential for unforeseen consequences.

A Lack of Critical Thinking
Too many leaders are accepting AI solutions at face value, without questioning the underlying assumptions, the data sources, or the potential for unintended consequences.

A Disconnect from Reality
The hype around AI is creating a disconnect between the boardroom and the front lines, where employees are struggling to adapt to rapidly changing workflows and feeling increasingly disempowered.

A Failure to Prioritize Ethics
Many organizations are treating AI ethics as a compliance box to be checked, rather than a fundamental principle guiding their AI strategy.

Unprepared Executives and Boards
We’re seeing a severe lack of preparedness when it comes to having the necessary discussions. This includes conversations about how AI will fundamentally reshape business models, redefine roles and responsibilities, and require a complete re-engineering of business operations to truly compete in the AI era. These aren’t incremental changes; they require a paradigm shift in thinking.

Insufficient Funding and Sustainment
Initial pilot projects and proof-of-concept initiatives often receive investment, but the crucial funding required for ongoing sustainment, scaling, and continuous improvement is frequently overlooked. AI is not a ‘one and done’ project; it requires a long-term commitment of resources.

Inability to Make Effective Decisions
A pervasive lack of clear accountability and decision-making frameworks is hindering progress. Too often, critical decisions are delayed, watered down, or simply avoided due to a fear of disruption or a lack of consensus. Transformational change demands bold leadership and a willingness to make tough calls.

These aren’t just theoretical concerns.

They’re impacting business performance, damaging reputations, and creating a climate of anxiety and distrust.

The posts I shared this week weren’t meant to be a lecture.

They were a call to action.

A challenge to boards and executives to up their game to ensure the medium to long term sustainability of their organizations.

#AI #DigitalTransformation #Leadership #Boardroom #ExecutiveLeadership #Ethics #CEO #DearCEO #FutureofWork

Decades ago, the golden rule for building a winning executive team was financial acumen.

MBA’s reigned supreme.

While financial literacy remains crucial, that era is officially over. Today’s executive team must be technology and data savvy – or risk becoming relics of a bygone era.

Think about it:
How many brilliant strategies have crumbled because the leadership team fundamentally misunderstood the underlying technology? I have personally watched 2 crumble in real time a direct result of technologically illiterate executive teams.

It’s not enough to simply approve a digital transformation; you need to understand it. Executives need to drive it.

The uncomfortable truth:
Your executive team’s skillset needs a radical overhaul. It’s not about replacing financial experts; it’s about augmenting their skills with a deep understanding of technology and data.

No one wants to talk about this but the time has come, the secret is out.

The New Executive Profile: Beyond the Balance Sheet
—
Data Fluency
Not just reading reports, but understanding algorithms, data biases, and the power of predictive analytics.

Technical Literacy
Grasping the fundamentals of AI, cloud computing, cybersecurity, and emerging technologies.

Agile Mindset
Embracing experimentation, iteration, and a willingness to challenge conventional wisdom.

Strategic Foresight
Anticipating future trends and adapting quickly to disruptive forces.

Action Items To Level Up Your Leadership Team
—
Skills Gap Assessment
Conduct a brutal honesty check – Where are the gaps in your executives team’s tech and data skills?

Executive Education Program
Invest in intensive training programs focused on AI, data science, and digital strategy. (No more generic “digital literacy” courses.)

Tech Shadowing Initiative
Have executives spend time embedded with engineering and data science teams to gain firsthand experience. Take it to the next level and have them manage a project or two.

Data-Driven Decision Framework
Implement a framework that mandates data-backed analysis for all major decisions.

Reverse Mentorship Program
Pair senior executives with younger, tech-savvy employees for knowledge exchange.

Are you prepared to embrace the future, or will your executive team become a roadblock to progress?

The time to act is now.

#ExecutiveLeadership #DigitalTransformation #AI #DataScience #FutureofWork #SkillsGap #Innovation #LeadershipDevelopment #TechSavvy #CEO #DearCEO

The biggest risk facing boards today isn’t technological complexity itself, but a misunderstanding of it. This disconnect leads to reactive technology decisions, stifled innovation, and a constant feeling of being one step behind.

Imagine a non-technical CEO and non-technical board seeking mentorship and guidance from a seasoned, business-focused technology executive – this isn’t just a good idea, it’s becoming essential.

This dynamic fosters a shared understanding of AI and digital transformation, moving beyond “thumbs-up / thumbs-down” decision-making to a dialogue-driven approach that unlocks innovation and builds lasting strategic alignment.

A tech leader at the Board-level who can translate complex concepts into tangible business value – identifying opportunities, mitigating risks, and shaping a future-ready organization – is invaluable.

Here’s what that mentorship looks like in action

Demystifying the Roadmap

The Tech Executive translates complex technical roadmaps into clear business outcomes, quantifying potential ROI and highlighting dependencies and deficiencies.

Risk Mitigation & Opportunity Identification

They proactively surface potential cybersecurity vulnerabilities and emerging technologies that can drive competitive advantage.

Data Literacy & Interpretation

They teach the board to critically evaluate data presentations, ensuring decisions are grounded in accurate insights, not just impressive visuals.

Strategic Alignment

They facilitate a shared understanding of how technology directly supports overarching business objectives, fostering a culture of collaboration and ownership.

Ultimately, this isn’t about turning your board into engineers; it’s about equipping them with the knowledge to ask the right questions and make informed decisions that drive lasting value.

Ultimately, it’s about cultivating a culture where technology empowers, rather than intimidates, leadership.

Are you proactively bridging this critical gap within your organization?

#ExecutiveStrategy #TechLeadership #Leadership #DigitalTransformation #AI #Innovation #CEO #DearCEO

Many organizations are relying on AI ethics checklists as a shortcut to responsible AI.

While AI ethics are a must have checklists are reactive, superficial, and ultimately ineffective. True AI ethics isn’t about ticking boxes; it’s about embedding responsible AI principles into the very fabric of your organization.

Relying on checklists creates a false sense of security and fails to address the underlying ethical considerations that drive AI development. To truly harness AI’s power responsibly, you need to cultivate a culture of ethical awareness and accountability.

Here’s your actionable roadmap to building a culture of responsible AI:

Promote Ethical Awareness Training: Equip all employees with the knowledge and skills to identify and address ethical dilemmas.

Establish Diverse AI Review Boards: Ensure a broad range of perspectives are considered during AI development and deployment.

Foster Open Dialogue & Transparency: Encourage employees to speak up about ethical concerns without fear of reprisal.

Embed Ethics into the AI Development Lifecycle: Integrate ethical considerations into every stage of the AI development process.

AI ethics isn’t a project; it’s a commitment.

Are you ready to move beyond checklists and cultivate a culture of responsible AI?

What’s the biggest obstacle preventing you from fostering a more ethical approach to AI development?

#AIStrategy #DigitalTransformation #Ethics #Leadership #AIgovernance #ResponsibleAI #CEO #DearCEO

AI’s power is undeniable, but its potential for harm is equally significant. At the Board level an often overlooked responsibility is establishing and monitoring robust AI ethics frameworks.

This isn’t just about compliance; it’s about safeguarding your firm’s reputation, mitigating risk, and building trust with customers and stakeholders.

Ignoring the ethical implications of AI – from bias in algorithms to data privacy concerns – can lead to devastating consequences: reputational damage, legal battles, and erosion of public trust.

Building a boardroom-ready framework isn’t just a “should do”; it’s a fundamental business imperative.

Here’s your actionable roadmap to building an AI ethics framework:

Establish an AI Ethics Committee
Composed of diverse perspectives (legal, ethical, technical, business).

Develop Clear Ethical Guidelines
Covering data privacy, algorithmic bias, transparency, and accountability.

Implement Bias Detection & Mitigation Techniques
Regularly audit AI systems for unintended consequences.

Promote Transparency & Explainability
Ensure stakeholders understand how AI decisions are made. This is a must an executive sponsor should be able to explain the algorithm(s) used.

AI ethics isn’t a constraint; it’s a competitive advantage.

Are you prepared to prioritize ethical considerations and build a framework that aligns with your values?

What are the biggest ethical challenges you’re facing in your AI journey?

#AIStrategy #AIethics #ResponsibleAI #Governance #DigitalTransformation #Leadership