AI at Work: Optional, Mandatory… or Simply the New Baseline?

In the previous posts, we explored innovation as a mindset, fractional leadership as a smarter operating model, and business model innovation as a strategic discipline.
Today, I want to connect those dots to one of the biggest accelerators of productivity and decision-making we’ve seen in decades:

Artificial Intelligence (AI) at work.

Not as hype. Not as fear. Not as “the next shiny tool.”
But as a practical capability that is quickly becoming a competitive baseline — for employees, entrepreneurs, freelancers, and leadership teams alike.

Is AI optional — or becoming mandatory?

Let’s be honest: “optional” depends on your context.

If your role is repetitive, operational, and heavily time-based, AI will likely reshape your tasks sooner.
If your role is strategic, creative, analytical, and leadership-driven, AI will reshape how you operate — how fast you learn, decide, test, communicate and execute.

The key idea is simple:

AI is not mandatory because someone says so.
AI becomes “mandatory” when your environment rewards speed, quality and adaptability — and the people around you start operating with those advantages.

AI is more than just ChatGPT

When many people say “AI,” they mean conversational tools. But AI is a broader ecosystem of capabilities that can strengthen how work gets done:

• Generative AI (writing, summarising, ideation, drafting, creating assets)

• Predictive AI (forecasting demand, churn risk, performance patterns)

• Automation + AI (workflows, triggers, assistants inside tools you already use)

• Computer vision (quality control, document extraction, visual recognition)

• Decision intelligence (turning data into recommendations, not just dashboards)

ChatGPT is one interface.
AI is the full engine room.

Is AI a threat?

AI is a threat only under two conditions:

1. When we treat it as a replacement for thinking

2. When we refuse to learn how to work with it responsibly

In reality, AI mostly replaces tasks, not people.

But tasks are a big deal — because tasks are what fill our calendars.

So the real risk is not “AI will take my job.”
The real risk is: “My job will be redesigned”

At the same time, AI has real risks that leaders and professionals must take seriously:

• Hallucinations (confident answers that can be wrong)

• Data privacy (what you share, where it goes, who owns it)

• Bias (AI can inherit patterns from imperfect data)

• Over-reliance (outsourcing judgement instead of strengthening it)

AI is powerful — but it still needs a human operator with context, standards and accountability.

How to embrace AI (without becoming an AI “expert”)

You don’t need to become technical.
You need to become intentional.

Here are practical ways to start using AI in daily work — regardless of your role:

If you’re an employee (any function):

• Turn long emails into clear action plans

• Summarise meetings into decisions + next steps

• Draft proposals, presentations, briefs and updates faster

• Create “first versions” of documents you can improve

• Prepare for meetings: background, questions, risks, scenarios

If you’re an entrepreneur / business owner:

• Generate product positioning options and test messaging

• Build customer personas and refine value propositions

• Improve pricing logic and bundle ideas (then validate)

• Create structured SOPs and internal playbooks

• Speed up research on competitors, channels and trends

If you’re freelance / consulting:

• Create sharper outlines and frameworks faster

• Improve clarity and structure in client deliverables

• Translate insights into different formats (slides, emails, one-pagers)

• Develop reusable templates for proposals and reports

• Increase throughput without sacrificing quality

The point is not “use AI for everything.”
The point is: use AI where it removes friction — so you can focus on higher-value thinking and execution.

A simple 3-step playbook to implement AI in your workflow

1) Start with one pain point
Pick one recurring task that consumes time (writing, reporting, summarising, analysing, preparing).

2) Create a repeatable prompt / template
Your goal is not random prompting. Your goal is a system:
Inputs → Instructions → Output format → Quality criteria.

3) Add guardrails
Define what AI can do and what it cannot do. Examples:

• “Draft, but I approve.”

• “Summarise, but I verify.”

• “Suggest options, but I decide.”

This is how you get value without losing control.

AI is a capability — people are the differentiator

This is the most important part.

AI is a multiplier.
But what it multiplies depends on who is using it.

If you have:

• Clear strategy

• Strong standards

• A culture of execution

• People aligned to the organisation’s values and vision

…AI will amplify results.

If you have:

• Confusion

• Poor leadership

• Misaligned teams

• Lack of accountability

…AI will amplify chaos.

AI doesn’t run the ship.

It accelerates the ship.

But someone still needs to set direction, make trade-offs, build trust, and lead people through uncertainty.

Looking ahead

In the next post, I’ll explore another topic that sits at the core of sustainable growth: Having (and attracting) the right people — and how technology + data can improve hiring decisions.

Because the companies that win in the next decade won’t just be the ones with the best tools.

They’ll be the ones with the best teams — making better decisions, faster, with more clarity.

#FutureOfWork #AI #Productivity #Leadership #BusinessTransformation