An Unexpected Benefit of Ai Hype
Updated: 2 days ago
Serious Noise in the Boardroom in 2026
There is AI augmentation of product development, services, and company operations. And there is AI hype associated with it – a bubbling mix of marketing, aspiration for cost optimisation, and anticipation of sales growth. A balanced mixture that an old-fashioned pharmacist (like my beloved grandmother navigating the spacious, light-filled pharmacy against a background of long shelves of massive dark brown jars…) would prescribe to a patient for energy and invigoration, just like a consultant would offer to your business.
AI is changing the world, for which an economic model of prosperity and middle-class creation hasn’t yet been developed – neither by economists nor by policymakers. The accelerating valuations of AI companies on exchanges, driven by extensive marketing, remind us of the Gold Rush to the New World. The new world will be built and explored, not without a path of burst bubbles and both sovereigns and private enterprises going into insolvency.
Why I am bullish on everything Ai, still in NASDAQ language terms – because, to a degree, it reminds me of the phase of digitalisation of tax payments.
The UAE was one of the more recent examples of countries that introduced VAT. Like in many countries, according to official statistics, about 95% of registered businesses were represented by micro-, small-, and medium-sized enterprises. Those SMEs, by and large, were operating from their traditional “blue book”. There were conventions established within firms, often undocumented, on how accounting and general business operations were conducted.
Filing VAT returns required the installation of dedicated software. This is when a vast number of enterprises, for the first time, encountered the necessity of establishing rules and operating protocols for digital matters. Once technology companies/service providers introduced dedicated software, it required businesses to have an active email account, which in itself introduced many businesses to the concept of digital presence and the need to have a dedicated website. Those who adapted to the new norm and expanded their leverage of available tools and ecosystems – reformatted their businesses online, opened new opportunities, and scaled.
(Note, the above is a high simplification of change journey – if we were to do a complete systems-thinking analysis, we would have to spend many pages on multi-factor analysis, correlations, sensitivity testing, etc.)
A similar effect we observe today in businesses with AI (I hope one of the Gallop / PwC or BCG survey will cover this soon).
The large corporates have entered into strategic MoUs with Anthropic-like giants of the space.
Agile startups are likely, out of necessity, to take the agentic route.
The mid-sized tech companies / e-commerce businesses have in-house developments.
The large legacy organisations & family businesses stand uniquely in this space.
And it is for two latter groups the identified AI hype is likely to have the most positive effect.
The Boards and the CEOs are initiating an inquiry – "We are not "automating" processes we’ve already automated in the course of our normal business activity - in the end, why have we even have our internal IT teams / outsourced tech advisors?! - instead we want to know how do we AUGMENT our key operations from decision-making, governance, and reporting perspectives, and how do we establish a single source for the models to be trained with?"
Three key questions come into play:
1. To what extent do our documented governance frameworks reflect how decisions are actually made in practice?
Do we have sufficient data, traceability, and institutional knowledge to understand and augment real-world governance processes?
Do we have records of not only what decisions were made, but also why they were made, by whom, and with what outcomes?
2. How do we address gaps in training data?
Can we effectively leverage existing organisational data, external knowledge, and synthetic data to develop, adapt, and evaluate AI models?
Where can reliable synthetic datasets be sourced or generated, and how do we validate that they reflect realistic governance and operational scenarios rather than reinforce existing biases or flawed assumptions?
3. How do we preserve ultimate decision-making authority?
How do we ensure AI augments rather than replaces human judgment, particularly in matters involving governance, strategic decisions, financial commitments, risk, and accountability?
These are truly exciting and forward-looking questions. In my advisory practice, I see more CEOs and Boards looking for answers – which means it won’t be a technology-led journey, but rather a business-led journey of operational improvement and growth.
Today any given client of mine, CEO-level, is bombarded with information – from Government / NGO invitations to AI-focused roundtables, technology companies offering software, consultants proposing various use-case brainstorming workshops, to internal “advanced” users from Strategy to IT departments volunteering internal use cases for consideration.
In reality – if you are ready, internally or with external support (from the aforementioned ecosystem), to answer the ABOVE THREE questions first – everything that comes next is easy (and cost-effective in the long run). The Noise in the Boardroom is Serious, and it is a good sign in the end.
