What Should The Board Worry About Today?
This is one of the first times I apply the distilling framework to a recommendation, please let me know in the comments what you think.
(Also, this is a summary without sources or links, nor detailed analysis... if you think that would be useful... well, let's talk. I have a service that does that... Let's leave shameless plugs behind, focus on distilling).
I have spent the last two weeks going through vast noise repositories looking for the five topics that matter to a board right now. There are three caveats to these exercises: topics change almost daily given the global economic instability, there is too much content to analyze, and most of it does not correspond at the level (board members) of my focus. This makes the process long and tedious, almost impossible without a framework. The distilling framework helps me focus on a two-horizon recommendation (9-12 and 12-18 months) which are both actionable and plan-ready, and relevant to a board focus between near-term and short-term.
As I started this exercise, five topics appeared based on three key criteria: long-term investment, board-level interest, and reflecting the current "market interest" (you can read hype if you want...). The top five topics were:
- Cloud Infrastructure
- Cybersecurity
- Generative AI
- Supply?Chain
- Edge Computing
My friend ChatGPT and I had a back-and-forth conversation on this topic based on two different scenarios: one where I fed it the links of what I read and listened to, and one where I asked it to do the same exercise by "themselves". This is about validating my thinking more than lazily adjudicating it to "them"… and also about validating the process, methodology, and framework I am using.
(NE - without making a political statement, I will use they/them to refer to ChatGPT and other inanimate AI agents going forward. I will also always tell you when I used GenAI models to help with the distillation, that's part of the framework)
The results were interesting (as to modification of the investment priorities), and challenging (the difference between the final outputs were very close, but then again -- I had to feed the right information, caveats, and context to get the "right" output, that is one that matched what I had concluded).
Truth be told, I was hoping for something more controversial and different, more of a debate... my guess is we are not there yet, as GenAI has very limited critical thinking (read: none) and reasoning (real reasoning, not what we call it for the purpose of GenAI glorification) capabilities. If you feed it the right information, with its own biases, it will agree with your biases... that's a core feature of GenAI.
But I digress...
The investment allocation was then modified, bure more important - and this is something I got from ChatGPT and not my input - the order of the priorities did not change, the amount allocated from the total budget did.
This was a promising twist, and this is where we are... the table below reflects the change in priorities and budget allocation.
|
Area
|
Prior %
|
New %
|
?
|
|
Cloud Infrastructure
|
40 %
|
35 %
|
? 5 %
|
|
Cybersecurity &
|
25 %
|
20 %
|
? 5 %
|
|
Generative AI
|
20 %
|
30 %
|
+ 10 %
|
|
Supply?Chain
|
10 %
|
10 %
|
± 0 %
|
|
Edge Computing
|
5 %
|
5 %
|
± 0 %
|
The change was very interesting, but when I asked for justification, this is what It said
Why This Shift Matters
- Competitive Parity & Differentiation
With a significant portion of peers adopting generative AI today, under?investing risks ceding efficiency gains and new product capabilities.
- Acceleration of High?ROI Use Cases
Many organizations report measurable productivity boosts (up to 20–30 % time savings) once generative AI is embedded in workflows.
- PESTEL Alignment
- Technological: AI is no longer experimental—it’s core to digital strategy.
- Economic: High adoption drives down tooling costs and accelerates vendor maturity.
- Social: Customers and employees expect AI?enabled experiences.
By reallocating an additional 10 % of our IT budget to generative AI, we both defend against “AI laggard” risk and position ourselves to capture its outsized productivity and innovation dividends—while still safeguarding our cloud foundation, security posture, and supply?chain resilience.
Which, astonishingly… I agree. Investing in a mainstream technology is a safer alternative to investing in infrastructure for competitive reasons, better ROI, and meeting expectations. Those were my reasons for the change, I am glad ChatGPT agrees.
This was an exercise in validating my thinking. Remember that I fed it the information, and selection biases, as input. I also asked it to do the same exercise on its own – and provide sources for its thinking… and the sources were similar…. I like the results of the experiment, and like the validation of the methodology… non?
Is this framework and process interesting? Want to see the back notes and research on this? contact me... this is not a sales pitch; it's a search for interested parties to discuss the findings.
Thanks for reading, talk soon.
New C-Suite
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eme.