business leaders are being let down
Still Buying Slide Decks? Demand the demo Instead
Part of my role and life is to connect with anyone and everyone, recently some industry influencers have started to share with me they’re observations about IT Executive Leadership across NZ and the Asia Pacific region. I’m here to help, as many of you know I have an open door policy, connect with me on LinkedIn, use the calendar stalking link to find a spot and the first coffee is on me. Go now, I’ll wait 😊
A concerning pattern is emerging. More conversations across the Asia-Pacific with my network are landing on the theme that, many IT leaders confidently discuss artificial intelligence in boardrooms yet privately admit they lack a concrete strategy. This disconnect isn’t merely about technical understanding, it reflects a broader failure to align AI’s potential with organisational DNA.
Whilst the headlines tout the amazing world of AI automation and other goodness, I’m watching teams squander months debating low impact use cases while ignoring foundational gaps in data literacy. The consultancy landscape (many of whom I consider friends) exacerbate this confusion, in their rush to capitalise on the hype, they’re pushing out “Consulting Slop”, generic boiler plate stuff. There are exceptions where there is genuine talent, but the majority still think that “deep research” is a new model.
Last quarter alone, I’ve had three separate firms pitched nearly identical “AI transformation roadmaps” to solve the issues they perceive us to have. (If you’re reading this to research me before your pitch here’s a hint: We’re 2-3 years ahead of your thinking and first deployed tradAI in 2004). This epidemic of recycled solutions raises uncomfortable questions:
when paying premium rates, why do so many proposals resemble templated decks rather than actionable plans?
The most valuable advisors I’ve encountered reject easy answers, instead forcing you to confront whether your infrastructure can even support basic machine learning workflows before promising ROI. Beneath the hype lies quieter opportunities, but the reality is that if you haven’t done your foundational data work, you will be leaving opportunity on the table. For companies lacking clean master data or cross-functional collaboration mechanisms, premature adoption often creates technical debt that outweighs short-term gains.
They’ll stay nameless but I’ve had a horror story relayed to me where a logistics provider learned painfully, when they rushed a Generative AI chatbot implementation that led to a 30% increase in customer complaints all because leadership ignored warnings about immature intent-classification models – in lay terms, the bot couldn’t work out what the customer wanted.
The path forward requires uncomfortable honesty.
Can your team articulate how AI differs from traditional analytics? Have you mapped existing workflows that could benefit from probabilistic systems rather than deterministic ones? When evaluating consultants, demand evidence of tailored problem-solving not just case studies with the serial numbers filed off. I terminate a lot of meetings the moment there isn’t a real demo I can poke a stick at.
If this article has raised uneasy questions, I invite you to discuss them face to face. I keep Friday mornings free for coffee at the Viaduct in Auckland. Bring your doubts, your procurement horror stories, and the last slide deck you received from a consultant. We will find the truth lurking between the bullet points, perhaps uncover the opportunity that was never listed at all.