When the Bubble Wobbles, What Next?

Earlier this week Softbank sold its entire stake in the chip maker Nvidia, whose GPUs power the engine rooms of the AI and Generative AI revolution we are currently living through. This has further raised concerns that the AI bubble is about to, if not burst, then slowly deflate like the saddest balloon after a small child’s birthday party. Of course, the devil is in the detail and it would seem Softbank is merely moving the poker chips of its investment strategy to a new emerging application of AI – “Physical AI”, where AI systems interact with and manipulate the physical world, rather than operating purely in digital environments.

However, grey-hairs like me who lived through the dotcom collapse and its aftermath are prone to asking the awkward “what if?” questions. What if the financial engineering of capital can’t keep pace with the investment needs of these companies, particularly as they seem to be charging customers less than it costs to deliver the service? What if the bottom falls out? What can we learn from the past (and what if we can’t?).

What’s left behind?

I started my career in the telecoms sector back in 1998. The heady days of copper wire, 56k dial-up speeds, and people trying to figure out how to make money off this “World Wide Web” thing. A similar feeding frenzy of investment and massive valuations based on future speculative value of companies delivering things on the world wide web, but also companies delivering the ‘plumbing’ that made it work – the networking technology firms and the fibre optic technology providers.

When the tide went out, a lot of these companies collapsed as they had front loaded debt finance based on forecast future revenues in which the line was only going up. When that didn’t happen, things got messy. Many of these companies are still around today, albeit in different guises and at different scale. But the blast radius of the dotcom collapse wiped out many. But it left somethings behind that, over time, delivered value. Apart from the technical knowledge of how to make things like ecommerce work, in many countries there was a new abundance of ‘dark fibre’, unutilised or underutilised telecommunications network infrastructure which, over time has (albeit indirectly) helped support the development and roll out of faster mobile communications and internet use. After all, your 4G mast needs to connect to something for high-bandwidth backhaul sometime.

When Hope and History Rhyme

Of course, even though this is a revolution, we can’t expect history to repeat itself exactly as before. But it is worth considering what the equivalent ‘leave behind’ of any wobble in the AI and Generative AI revolution might be for organisations.

While it’s tempting to say the leave-behind will be dark data centres standing idling to take up some unforeseen slack, the pace of digital content generation over the past 20 years shows little sign of slowing. Much like the waste bin in your kitchen, having a second bin on stand-by doesn’t mean you’re going to make less waste and that second bin will get filled soon enough. After all, the dark fibre didn’t stay unused. It was put to use in different ways and indirectly supported the development of new technologies.

My Thought?

Personally, I think that the big ‘leave behind’, and the big long term win for organisations from the current AI hype cycle, will be the renewed focus on data and content not as ‘process exhaust’ but as the thing that powers organisations and enables people to get stuff done. Right now, organisations are adopting Generative AI with a frenzied mix of strategic intent and FOMO. The long term winners are likely to be the ones that:

• Take the opportunity to tame their disparate data and content, using AI to augment human efforts in tagging, categorising, and classifying data and improving quality of data.
• Take the chance to implement appropriate organisational and technical governance over data and AI, not as a technical competence or technology requirement but as an organisational capability.
• Invest in redesigning how staff learn how to do their (newly augmented) jobs while still developing the competences and capabilities to be good leaders and managers and have the knowledge and skill to identify defective outputs or intervene when the process is going wrong, including critical thinking and systems thinking skills for and about data and content.

Bluntly: if the leave-behind of the AI bubble is that organisations start doing the things we’ve been trying to get them to do for the last 30+ years in data and information management, then that would be a valuable legacy. And it is a legacy which would deliver organisational and social benefits through improved understanding of how data influences decisions and outcomes that impact people.

After all, even in the world of Physical AI there will still need to be appropriate management and governance of data and data related processes to enable appropriate interactions between AI systems and physical environments in a way that does not lead to harm or damage.

When the tide goes out, who will still have their swimming trunks on?

The dotcom boom had many justifiable failures. It also had many successes that just took a lot longer than they had thought to make things work, and perhaps not in the way that they had originally envisaged. Softbank moving their poker chips to a different table doesn’t mean that the AI bubble is going to collapse (yet), but it should be a signal that we need to start looking for what of value might be left behind.

For most organisations, it will be the investment in the human capital, paying down of technical and data debt, and thinking critically about data and its quality and governance, and the impact on business continuity and resilience of building in reliance on AI, Generative AI, and Agentic AI that will likely be the factors that mean your togs stay on when tide does go out.

But that’s the thing about tides. If you are still standing and hang around long enough, they usually come back in.

When the dotcom pioneers reached to develop a commercial model and innovative businesses for the internet, we got investment in communications infrastructure and the seeds of data analytics technologies and the mobile internet. Today’s pioneers are reaching to create a simulation of an intelligence that will either supplement us or supplant us. Perhaps what we’ll get is a move up the tech stack to the data layer in the wider thinking and longer term success there, even as the headline goal remains out of reach?

Want to learn more?

Castlebridge will be hosting our 3rd Annual Data Leaders’ Summit in Wexford next March where we will be digging into and exploring these topics with a critical strategic eye and a selection of international keynote speakers and panellists.

Details are at https://dataleadersummit.ie.