Using AI Creates New Risks To Manage

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We’re using AI more and more, as it takes centre stage in work and business.

Let’s go through the list.

I’m sure you’re using AI to help you read, write, analyse and summarise information.

So is your boss.

Your customer is using AI before they talk to you.

As is your customer’s customer.

All your competitors are leaning into this.

And your next hire, they’re building resumes with AI and practicing interviews on AI avatars.

We’re doing this to be more productive. But it also creates a whole new category of risks.

The recent Anthropic row is a preview. It’s fallen out with the DOD, federal agencies have been ordered to stop using it, and it’s been labelled a “supply chain risk”.

Any use of tools like Claude could bar a company from defense contracts.

Will all this happen or will there be a negotiated resolution?

We don’t know yet – but even the risk that it could – that the AI tool that’s central to the use of so many organisations could be banned with the stroke of a pen – is going to cause concerns.

If you’ve spent the last year building your services around the use of Claude, what are you going to do next? Wait and see? Pivot?

When AI becomes core infrastructure – and is exposed to regulatory and geopolitical risk – we need new controls and mitigations.

What are they going to look like?

If You Run Operations Like A Programmer

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We will start to run business operations like programmers – but that needs a shift in thinking.

You’re an FD or Sustainability Director and here comes a hot topic – new SRS rules in the UK. How are you processing what this means for your operations?

The way I’d have done this a few years ago is to assign an analyst – an individual contributor – to read the source material and create a brief. Key points? Align with IFRS S1,S2. More work coming your way. Get ready. Review the output and get it out to clients.

What changes if we bring AI into the process?

The picture shows a workflow that I’ve been testing.

First, we use a production agent, an intellectual chainsaw, to mine content and create work-in-progress output.

That output can be picked up by an IC who has two tasks.

First, they ought to have their own validation agent that checks the WIP against source material.

The IC also has to read and check the content – someone, somewhere has to take responsibility for actually knowing what’s going on.

Then, checked, validated content is used to produce the final output – which is reviewed by the leader and shared with a client.

If you’re a programmer looking at the revised process, you’ll see that there are more steps, and more opportunities for bugs.

And there are two ways to squish technical bugs.

Better reviews. And better tests.

If you are getting your organisation AI-ready – that means two actions.

  1. Build better group review processes
  2. Build test processes to improve automated validation and error detection

Systems, Skills and Speed – A 3S Strategy Framework

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If I have one fear, it’s missing the world changing around me while I have blinkers on.

Strategy is about seeing where things are going and getting in position.

And then, if you’re lucky, you’ll catch the next wave.

I think we have to do three things to get in position.

1. Think Systems

Complexity is everywhere now.

Systems approaches engage with the complexity.

They recognize that culture and power matter, uncover assumptions and hidden dynamics, and build consensus with stakeholders.

Want to bring your team along?

Teach them how to think in systems.

2. Think Skills

And that requires new skills – at every level of an organisation.

Leaders need to figure out how they’re going to drive change and where to allocate resources.

Individual contributors have to get good at using a combination of tools to augment their capabilities.

And they have to do it now.

3. Think Speed

The window to deliver outcomes is compressing. I’m using AI. You’re using AI. Our clients are using AI.

We’re all getting further faster. And the people who aren’t – they’re simply further back in the discussion.

We don’t have time to wait.

Given a choice between a slow option and a fast one – most people will need a good reason to pick the former.

If you’re in the business of running a firm, ask yourself – are you thinking in systems? Are you building a team with the right skills?

And above all, are you moving as fast as you should be… or are you already behind?

Consulting Is In Trouble

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Ok – I agree. Consultants are in trouble.

Given a choice between giving work to a person or AI – I’m going to pick AI first.

Have a question about a market, technology, location? Start with deep research.

Pre-AI, the bottleneck was hours spent doing research, looking up sources, and drafting decks.

Junior consultants did research and drafting. Senior ones did a review and Partners managed socialisation and communication.

Research and first drafts can be done with AI, moving the bottleneck downstream to the review process.

That’s the next pinch point – how can we tell if the information is good, or correct?

AI will come for that in time. For example, we can use multiple AIs on the same problem and get them to check each other’s work. The industry is going to solve the citation problem.

The bit that still needs people is for the human sense making and decision processes involved in socialisation and group consensus.

What are the implications?

  • Smaller teams able to do more.
  • AI-first firms raising the bar.
  • A focus on outcomes rather than outputs.

This is not going away.

Knowedge As Inquiry Rather Than Expertise

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Don’t you find bookshelves overwhelming these days?

Can anyone read them all?

For those of us who grew up before smartphones, social media and streaming, there was time to sit and read for hours.

But now the big shift, for me, is that books have stopped being definitive sources of knowledge.

The ideas in them often fail to connect with the complexity of reality.

Say you have a problematic situation at your firm. Can you roll out a 2×2 matrix and solve it? Will a SWOT be enough?

No. We know that the specifics of the situation matter. What you do depends on what you find when you go and look at what’s going wrong.

That’s why, as I get older, I am less willing to accept simple universal solutions to real-world problems, even if they’re fossilised in books.

We need to be willing to learn – and find knowledge, wherever that is now.

It’s a process of inquiry rather than an application of expertise.

The History and Foundations of SSM

Sunday, 8.48pm

Sheffield, U.K.

My methodology is not knowing what I’m doing and making that work for me. –Stone Gossard

This is a retake of a talk I did in 2025 at the EURO conference on the history and foundations of Soft Systems Methodology (SSM).

I go into:

  • The origins of SSM in Systems Engineering applied to problems faced by managers
  • SSM as a part of Soft Operations Research (OR), and views of Soft OR.
  • Key books that documented SSM’s development
  • SSM over the years, and the “definitive” version of the methodology
  • Issues and critical views of SSM
  • A summary of how to use OR for problem solving.

The AI transcription of this talk is laughable so I’m going to protect you from that summary.

Cheers,

Karthik

Use Roadblocks To Change Your Behaviour

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Change is really hard.

A road I use every day is shut. There are orange cones blocking entry and a big yellow “Diversion” sign.

It’s forced me to look at my options.

I tried a couple of new routes. They worked well.

I might never have tried these roads if my usual route had been open.

The old road is open again now.

And when I saw that muscle memory took over and I headed that way again.

It’s easier to keep doing things the way they’ve always been done.

We change only when we have to.

If you want to sustain new behaviour, put a roadblock in front of the old options.

Constraints Help Creativity

Friday, 10.39am

Sheffield, U.K.

I think frugality drives innovation, just like other constraints do. One of the only ways to get out of a tight box is to invent your way out. — Jeff Bezos

In these first few posts, I’m going to fumble my way around a video making process that works for me.

I’m also trying to figure out a workflow where AI helps and augments what I am doing, rather than being a replacement, or a dull and sanitized average that isn’t worth your time reading.

So here’s my starting approach.

  1. Think about the content and create a through line
  2. Practice saying it aloud and seeing if it works
  3. Record a one-take video of the content. Only re-record if it’s really bad.
  4. Trim and upload to YouTube

Then, it’s how to share the material.

My usual WordPress flow of org2blog doesn’t seem to work well with video, so I’m typing this straight into the WordPress editor.

Now, for AI.

I’m using Whisper to transcribe the text of the talk, and then using llama3.2 locally to create shownotes. I’m going to add these below with minimal editing. Feel free to ignore them, but you might like them more than the video! In which case let me know.

Cheers,

Karthik

AI Generated summary below

Summary: Ideas for Creating Video Content

The speaker aims to create video content focused on explaining ideas and
concepts, rather than entertaining or visually building up an idea. The
key goals are:

  • To focus on the core concept and keep it simple
  • To understand a particular message in detail
  • To stay on one particular idea and maintain a through line throughout
    the explanation

Choosing Topics

  • Select topics that are personal and important to the creator, rather
    than exotic or complex
  • Focus on explaining theory and then applying practical examples
    (practice)

Constraints for Improving Focus

  1. Technical Limitations
    • One-take video to improve clarity and communication of ideas in
      one go
    • Limited camera angles and drawing from a whiteboard or annotation
      tools

Approach to Ideas

  • Two levels: theory (overall umbrella of ideas) and practice (hands-on
    application)
  • Theoretical understanding informs practical experience, while
    practical experience informs theoretical understanding

Learning Cycle

  1. Thinking and conceptualizing
  2. Producing something (making a video in this case)
  3. Reflecting on the production to identify areas for improvement

Why We Need To Get Better At Explaining Ourselves

Success depends less on the structure you create than the story you tell.

When you’re working in a company does it often feel like the structure is working against you rather than for you?

I’ve been reading Jackson and Carter’s “Rethinking organisational behaviour: A poststructuralist framework” and think it has useful insights to sustainability managers – well, all managers in general.

It starts by getting clear on what we mean by structure.

There are three versions of structure.

First, there is structral functionalism.

This view is that structure is visible, most clearly in the org chart.

You change things by getting the right structure. If things aren’t working, then restructure.

This is a dominant view – many people think it’s the “natural” way to think about organisations.

But – does it work? If you look at your organisation do you see visible structure getting results?

If not, we turn to structuralism for an explanation.

Structuralism says that it’s the stuff under the surface that drives behaviour – that which you don’t see but exists.

This is the underlying logic – the relationships and dynamics between leaders and teams that result in one thing or the other.

What makes a difference is the less visible stuff – power relations, inequalities, differing levels of freedom to act.

And then we have the third view – poststructuralism.

The first two approaches suggest that structure is a real thing and exists – either above the surface or below – but it’s there.

Poststructuralism says that structure is constructed – from the way we explain things.

Explanation is the key – it helps us make sense of what is going on.

That explanation is the structure, not real and objective but a product of the human mind.

If you’ve read this far and are wondering why this matters, this is why I think it’s important.

If the poststructralism view is right, then success depends not on the structure you create but the story you tell.

I’m sure you’ve heard of the famous Amazon process where people are asked to write a plan rather than use PowerPoint.

This could be seen as an implementation of poststructuralism – tell me a story – get your thinking down on paper and explain what you want to do and why it’s going to help.

Help me make sense of what is going on, so I can decide what to do next.

My New Target, 1,000 Vlog Posts In 5 Years

Monday, 12.48pm

Sheffield, U.K.

What you get by achieving your goals is not as important as what you become by achieving your goals. – Zig Ziglar

A few days back, on the 11th of February I achieved a goal I set back in 2017 – to write a million words in ten years.

I have enjoyed that process – writing is not easy but it is rewarding.

I feel like this work has helped me discover what I was interested in and how I could explore and understand different topics using text and drawings.

Now it’s time to set a new goal. I’d like to get better at explaining ideas – and a good way to do that is by vlogging.

So that’s what I’m going to start doing now with this blog.

The goal is 1,000 videos in five years. And this post is the first one.

Let’s see how things work out.

Cheers,

Karthik

p.s I’m still experimenting with getting my tech setup working so there may be some problems with the first few posts as I figure things out.